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Seven cubic spinel ferrite nanoparticles were successfully synthesized through the co-precipitation method. These nanoparticles include Fe3O4, Zn0.4Fe0.62+Fe23+O4, Mn0.4Fe0.62+Fe23+O4, Zn0.6Mn0.4Fe0.42+Fe1.63+O4, Zn0.4Mn0.6Fe0.42+Fe1.63+O4, Zn0.4Mn0.4Fe0.22+Fe23+O4, and Zn0.4Mn0.4Fe0.42+Fe1.83+O4. The Rietveld method was used to analyze X-ray diffraction data, confirming that all samples have a single-phase cubic spinel structure. The presence of zinc and manganese ions in magnetite lattice leads to changes in lattice parameters and crystallite size, resulting in a range of 7–12 nm crystallite sizes. Fourier transform infrared spectroscopy (FT-IR) analysis of nanoparticles reveals two significant adsorption peaks at 560-576 cm−1 and 437-449 cm−1, corresponding to metal ion stretching vibrations at tetrahedral and octahedral sites. The X-ray photoelectron spectroscopy (XPS) analysis revealed the presence of iron, zinc, and manganese in various oxidation states. Scanning electron microscopy (SEM) and Transmission electron microscopy (TEM) images showed spherical, agglomerated nanoparticles. The study confirmed the elemental composition and mapping images of prepared samples using energy-dispersive X-ray spectroscopy (EDS). The magnetic properties of the synthesized nanoparticles were meticulously examined utilizing a vibrating sample magnetometer (VSM) at room temperature. A direct correlation is established between the structural alterations induced by Zn2+/Mn2+ and their subsequent effects on magnetic characteristics, specifically through the reallocation of cations and the mechanisms of electron hopping occurring at the B-sites. The structural modifications result in enhanced superparamagnetic behavior, exhibiting saturation magnetization values between 46.01 and 69.38 emu/g. The sustainable characteristics of these materials render them highly viable options for applications in environmental remediation and green technology.

BackgroundThe production of D-lactic acid (D-LA) from non-detoxified corn stover hydrolysate is hindered by substrate-mediated inhibition and low cell utilization times. In this study, we developed a novel temperature-sensitive hydrogel, F127-IEA, for efficient D-LA production using a cell-recycle batch fermentation process.ResultsF127-IEA exhibited a porous structure with an average pore size of approximately 1 μm, facilitating the formation of stable Lactobacillus bulgaricus clusters within the gel matrix. It also maintains excellent mechanical properties. It also maintains excellent mechanical properties. F127-IEA immobilized Lactobacillus bulgaricus T15 (F127-IEA-T15) can be used in cell-recycle fermentation for over 150 days from glucose and 50 days from corn stover hydrolysate, achieving high production rates of D-LA from glucose (2.71 ± 0.85 g/L h) and corn stover hydrolysate (1.29 ± 0.39 g/L h). F127-IEA-T15 enhanced D-LA production by adsorbing and blocking toxic substances present in corn stover hydrolysate that are detrimental to cellular activity.ConclusionsThe newly developed hydrogels in this study provide a robust platform for large-scale extraction of D-LA from non-detoxified corn stover.

The effects of salt–enzyme–alkali progressive tenderization treatments on porcine cortical conformation and collagen properties were investigated, and their effectiveness and mechanisms were analyzed. The tenderization treatment comprised three treatment stages: CaCl2 (25 °C/0–30 min), papain (35 °C/30–78 min), and Na2CO3 (25 °C/78–120 min). The textural, microscopic, and collagenous properties (content, solubility, and structure) of pork skin were determined at the 0th, 30th, 60th, 90th, and 120th min of the treatment process. The results showed that the shear force, hardness, and chewability of the skin decreased significantly (p < 0.05), and the elasticity exhibited a gradual increase with the progression of tenderization. The content and solubility of collagen showed no significant change at the CaCl2 treatment stage. However, the soluble collagen content increased, the insoluble collagen content decreased, and the collagen solubility increased by 18.04% during the subsequent treatment with papain and Na2CO3. Meanwhile, the scanning electron microscopy results revealed that the regular, wavy structure of the pig skin collagen fibers gradually disappeared during the CaCl2 treatment stage, the overall structure revealed expansion, and the surface microscopic pores gradually increased during the papain and Na2CO3 treatment stages. The findings of the Fourier transform infrared spectroscopy analysis indicated that the hydrogen bonding interactions between the collagen molecules and the C=O, N-H and C-N bonds in the subunit structure of collagen were substantially altered during treatment and that the breakage of amino acid chains and reduction in structural ordering became more pronounced with prolonged treatment. In the tertiary structure, the maximum emission wavelength was blue-shifted and then red-shifted, and the fluorescence intensity was gradually weakened. The surface hydrophobicity was slowly increased. The salt–enzyme–alkali tenderization treatment considerably improved the physical properties and texture of edible pork skins by dissolving collagen fibers and destroying the structure of collagen and its interaction force.

The use of plant-derived emulsified gel systems as fat substitutes for meat products has always been an important direction in the development of healthy foods. In this study, a composite matrix emulsion gel was prepared with soy protein isolate (SPI) and different concentrations of cassia bean gum (CG), and then the selected emulsion gel was applied to meat sausage as a fat substitute to explore its stability. Our results showed that the hardness, chewiness, viscosity, shear stress, and G′ and G″ moduli of the emulsion gel increased considerably with the cassia bean gum concentration, the thickness of the emulsion gel increased, and the pore size decreased. The gel strength of the 1.75% CG/SPI emulsion gel was the highest, which was 586.91 g. The elasticity was 0.94 mm, the masticability was 452.94 mJ, and the water-holding capacity (WHC) was 98.45%. Then, the 1.75% CG/SPI emulsion gel obtained via screening was applied as a fat substitute in meat sausage. With an increase in the substitution amount, the cooking loss, emulsification stability, pH, color difference, texture, and antioxidant activity of the meat sausage before and after freezing and thawing increased first and then decreased. The indexes of meat sausage with 50% fat replacement were not considerably different from those of full-fat meat sausage. This study can provide a theoretical basis for the application of plant-derived emulsified gel systems as fat substitutes in meat sausage.

This study aimed to develop a product that closely replicates the texture and appearance of tripe. The effect of three different proteins (soy protein isolate (SPI), pea protein isolate (PPI), and whey protein isolate (WPI)) at different protein levels and processing conditions (heating (90 °C, 1 h) followed by cooling (4 °C, 12 h) and heating (90 °C, 1h) followed by freezing (−18 °C, 12 h)) of konjac glucomannan (KGM) was analyzed. The optimal formulations for simulating tripe were screened by examining their similarity to real tripe in terms of texture, color, and sensory experience. The screened formulations were also subjected to a preliminary mechanistic investigation. The results show that all three proteins improved the gel’s textural properties to varying degrees. At the same concentration, the hardness and chewiness of the KGM/WPI composite gel were significantly higher than those of the other two KGM/protein composite gels, among which the composite gel obtained by adding 8% WPI and 5% KGM heating-frozen (FWK4) had the greatest hardness and chewiness of 4338.07 g and 2313.76, respectively, and the springiness differences in all of the composite gels were small. In addition, the addition of protein increased the whiteness of the hybrid gels, with WPI having the most significant effect on the whiteness of the composite gels (whiteness increased from 30.25 to 62.80 as the concentration of WPI increased from 0 to 10%). Freezing increased composite gel hardness and chewiness, but reduced gel springiness and whiteness. Cluster analysis showed that the composite gel obtained by heating–cooling 8% WPI and 5% KGM (WK4) was very similar to the real tripe in terms of chewiness and whiteness, and WK4 had the highest sensory scores for color, tissue morphology, tactile sensation, taste, and odor. The acceptability score in terms of tissue morphology reached 4.3. Meanwhile, the characterization results of WK4 indicate the presence of large junction areas in the gel network. Fourier transform infrared spectroscopy (FTIR) analysis, X-ray diffraction, and intermolecular force contributions indicated that the incorporation of WPI promoted integral interactions, and that hydrophobic interactions and disulfide bonding played a key role in the WK4 composite gel system. Moreover, scanning electron microscopy (SEM) also showed that the combination of WPI and konjac glucan resulted in a more compact gel structure. This study is informative for the development of the field of bionic tripe processing.

Abstract N6‐methyladenosine (m6A) modification has been implicated in the progression of obesity and metabolic diseases. However, its impact on beige fat biology is not well understood. Here, via m6A‐sequencing and RNA‐sequencing, this work reports that upon beige adipocytes activation, glycolytic genes undergo major events of m6A modification and transcriptional activation. Genetic ablation of m6A writer Mettl3 in fat tissues reveals that Mettl3 deficiency in mature beige adipocytes leads to suppressed glycolytic capability and thermogenesis, as well as reduced preadipocytes proliferation via glycolytic product lactate. In addition, specific modulation of Mettl3 in beige fat via AAV delivery demonstrates consistently Mettl3's role in glucose metabolism, thermogenesis, and beige fat hyperplasia. Mechanistically, Mettl3 and m6A reader Igf2bp2 control mRNA stability of key glycolytic genes in beige adipocytes. Overall, these findings highlight the significance of m6A on fat biology and systemic energy homeostasis.

Mussel-inspired polydopamine (PDA) has attracted substantial interest in materials synthesis, energy storage, environmental governance, and biomedical science since it was first reported in 2007. PDA, owing to its excellent biocompatibility and photothermal conversion efficiency (η), has been used in photothermal therapy alone and in combination with photodynamic therapy, chemotherapy, radiation therapy, immunotherapy, and gas therapy for cancer treatment. This review summarizes the methods for synthesizing structurally diverse PDA-based nanomedicines and their applications in cancer therapy, to provide perspectives to guide future studies in cancer treatment.

The biosensor is an instrument that converts the concentration of biomarkers into electrical signals for detection. Biosensing technology is non-invasive, lightweight, automated, and biocompatible in nature. These features have significantly advanced medical diagnosis, particularly in the diagnosis of mental disorder in recent years. The traditional method of diagnosing mental disorders is time-intensive, expensive, and subject to individual interpretation. It involves a combination of the clinical experience by the psychiatrist and the physical symptoms and self-reported scales provided by the patient. Biosensors on the other hand can objectively and continually detect disease states by monitoring abnormal data in biomarkers. Hence, this paper reviews the application of biosensors in the detection of mental diseases, and the diagnostic methods are divided into five sub-themes of biosensors based on vision, EEG signal, EOG signal, and multi-signal. A prospective application in clinical diagnosis is also discussed.

Abstract Mangrove ecosystems play an important role in global carbon budget, however, the quantitative relationships between environmental drivers and productivity in these forests remain poorly understood. This study presented a remote sensing (RS)-based productivity model to estimate the light use efficiency (LUE) and gross primary production (GPP) of mangrove forests in China. Firstly, LUE model considered the effects of tidal inundation and therefore involved sea surface temperature (SST) and salinity as environmental scalars. Secondly, the downscaling effect of photosynthetic active radiation (PAR) on the mangrove LUE was quantified according to different PAR values. Thirdly, the maximum LUE varied with temperature and was therefore determined based on the response of daytime net ecosystem exchange and PAR at different temperatures. Lastly, GPP was estimated by combining the LUE model with the fraction of absorbed photosynthetically active radiation from Sentinel-2 images. The results showed that the LUE model developed for mangrove forests has higher overall accuracy (RMSE = 0.0051, R2 = 0.64) than the terrestrial model (RMSE = 0.0220, R2 = 0.24). The main environmental stressor for the photosynthesis of mangrove forests in China was PAR. The estimated GPP was, in general, in agreement with the in-situ measurement from the two carbon flux towers. Compared to the MODIS GPP product, the derived GPP had higher accuracy, with RMSE improving from 39.09 to 19.05 g C/m2/8 days in 2012, and from 33.76 to 19.51 g C/m2/8 days in 2015. The spatiotemporal distributions of the mangrove GPP revealed that GPP was most strongly controlled by environmental conditions, especially temperature and PAR, as well as the distribution of mangroves. These results demonstrate the potential of the RS-based productivity model for scaling up GPP in mangrove forests, a key to explore the carbon cycle of mangrove ecosystems at national and global scales.

Wastewater treatment plants (WWTPs) have been regarded as an important source of antibiotic resistance genes (ARGs) in environment, but out of municipal domestic WWTPs, few evidences show how environment is affected by industrial WWTPs. Here we chose Hangzhou Bay (HZB), China as our study area, where land-based municipal and industrial WWTPs discharged their effluent into the bay for decades. We adopted high-throughput metagenomic sequencing to examine the antibiotic resistome of the WWTP effluent and coastal sediment samples. And we proposed a conceptual framework for the assessment of antibiotic resistome risk, and a new bioinformatic pipeline for the evaluation of the potential horizontal gene transfer (HGT) frequency. Our results revealed that the diversity and abundance of ARGs in the WWTP’s effluent were significantly higher than those in the sediment. Furthermore, the antibiotic resistome in the effluent-receiving area (ERA) showed significant difference from that in HZB. For the first time, we identified that industrial WWTP effluent boosted antibiotic resistome risk in coastal sediment. The crucial evidences included: 1) the proportion of ARGs derived from WWTP activated sludge (WA) was higher (14.3 %) and two high-risky polymyxin resistance genes (mcr-4 and mcr-5) were enriched in the industrial effluent receiving area; 2) the HGT potential was higher between resistant microbiome of the industrial effluent and its ERA sediment; and 3) the highest resistome risk was determined in the industrial effluent, and some biocide resistance genes located on high-risky contigs were related to long-term stress of industrial chemicals. These findings highlight the important effects of industrial activities on the development of environmental antimicrobial resistance.

Transmembrane kinases (TMKs) play important roles in plant growth and signaling cascades of phytohormones. However, its function in the regulation of early leaf senescence (ELS) of plants remains unknown. Here, we report the molecular cloning and functional characterization of the WATER-SOAKED SPOT1 gene which encodes a protein belongs to the TMK family and controls chloroplast development and leaf senescence in rice (Oryza sativa L.). The water-soaked spot1 (oswss1) mutant displays water-soaked spots which subsequently developed into necrotic symptoms at the tillering stage. Moreover, oswss1 exhibits slightly rolled leaves with irregular epidermal cells, decreased chlorophyll contents, and defective stomata and chloroplasts as compared with the wild type. Map-based cloning revealed that OsWSS1 encodes transmembrane kinase TMK1. Genetic complementary experiments verified that a Leu396Pro amino acid substitution, residing in the highly conserved region of leucine-rich repeat (LRR) domain, was responsible for the phenotypes of oswss1. OsWSS1 was constitutively expressed in all tissues and its encoded protein is localized to the plasma membrane. Mutation of OsWSS1 led to hyper-accumulation of reactive oxygen species (ROS), more severe DNA fragmentation, and cell death than that of the wild-type control. In addition, we found that the expression of senescence-associated genes (SAGs) was significantly higher, while the expression of genes associated with chloroplast development and photosynthesis was significantly downregulated in oswss1 as compared with the wild type. Taken together, our results demonstrated that OsWSS1, a member of TMKs, plays a vital role in the regulation of ROS homeostasis, chloroplast development, and leaf senescence in rice.

Urban regeneration (UR) has been a leading concern in urban studies globally. China’s rapid urbanization has undergone profound urban decay and social contestation, for which UR has emerged as a viable solution. However, UR is not without its drawbacks. It has caused emerging spatial and planning problems; however, few studies have explored the characteristics and issues of UR from the view of spatial analytics on the city scale. This study aims to depict the distribution characteristics of UR projects in Chinese cities and to reveal whether it meets the requirements of urban development from the planning perspective. The nearest neighbor index and its hierarchical clustering, as well as kernel density estimation are used in conjunction to investigate the spatial distribution characteristics; and the relationship between project distribution and each urban development indicator is explored using mixed spatial characteristics analyses, such as buffer analysis, space syntax, and heat mapping. Considering Shenzhen as the empirical study city, this research is based on all officially released data of implemented UR projects between 2010 and 2021. The findings imply that the UR projects in Shenzhen are mostly located in areas with higher economic development levels and accessibility with areas witnessing industrial restructuring and severe urban decay being prone to be designated for UR initiatives. The spatial distribution characteristics disclose the challenges inherent in the mix of top-down and market-driven UR approaches as well as the dilemma of the center-periphery pattern in UR implementation. Furthermore, the contradiction between the growing population and limited land resources as well as the barriers to industrial clustering formation are also revealed. This study enriches the methodological framework for spatial and visualization studies of urban regeneration in worldwide cities and sheds light on how to promote UR in regard to urban sustainability with ramifications for future urban development in other Chinese cities.

Neural networks have greatly promoted the development of hyperspectral unmixing (HU). Most data-driven deep networks extract features of hyperspectral images (HSIs) by stacking convolutional layers to achieve endmember extraction and abundance estimation. Some model-driven networks have strong interpretability but fail to mine the deep feature. We propose a variable-iterative fully convolutional neural network (VIFCNN) for sparse unmixing, combining the characteristics of these two networks. Under the model-driven iterative framework guided by sparse unmixing by variable splitting and augmented lagrangian (SUnSAL), a data-driven spatialspectral feature learning module and a spatial information updating module are introduced to enhance the learning of data information. Experimental results on synthetic and real datasets show that VIFCNN significantly outperforms several traditional unmixing methods and two deep learning--based methods. On real datasets, our method improves signal-to-reconstruction error by 17.38%, reduces abundance root-mean-square error by 25.24%, and reduces abundance spectral angle distance by 31.40% compared with U-ADMM-BUNet. [ABSTRACT FROM AUTHOR]

To study the biocompatibility of nanohydroxyapatite (nmHA)-SiO2 fiber material and its efficacy in guided bone regeneration. ① The cytotoxicity of the nmHA-SiO2 fiber material to MC3T3-E1 cells was determined by CCK-8 assay. The adhesion of cells on the surface of the material was observed. ② Bone defects were prepared in the skull of three groups of New Zealand white rabbits. The following treatments were administered: implantation of nmHA-SiO2, implantation of Bio-Oss, and no treatment. The defects were then covered with nmHA-SiO2 membrane or Hai’ao oral repair membrane. Animal samples were analyzed by gross observation, micro-computed tomography, hematoxylin-eosin staining and Masson staining. The data were statistically analyzed by multivariate analysis of variance to evaluate the repair of bone defects. ① The nmHA-SiO2 fiber material has suitable biocompatibility. ② The nmHA-SiO2 fiber material performed more effectively as a barrier membrane than other bone substitute materials in GBR model rabbits. [ABSTRACT FROM AUTHOR]