Lactoferrin-Chitosan Composite Hydrogels Induced by Microbial Transglutaminase: Potential Delivery Systems for Thermosensitive Bioactive Substances.

In this work, lactoferrin (LF)-chitosan (CS) composite hydrogels with good loading capacity of thermosensitive bioactive substances were successfully obtained by microbial transglutaminase (MTG)-induced cross-linking. We evaluated the rheological, textural, and microstructural characteristics of the composite hydrogels under different conditions. The results demonstrated that the concentrations of LF and CS as well as the amount of MTG could regulate the textural properties, rheological properties, and water holding capability. The results of FTIR and fluorescence spectroscopy indicated that the main interactions within the composite gel were hydrogen and isopeptide bonds. Additionally, in vitro digestion simulation results verified that riboflavin kept stable in stomach due to the protection of LF-CS composite hydrogels and was released in small intestine. These results suggested that thermosensitive bioactive substance could be encapsulated and delivered by the LF-CS composite hydrogel, which could be applied in lots of potential applications in functional food as a new material.

Mechanism on microbial transglutaminase and Tremella fuciformis polysaccharide-mediated modification of lactoferrin: Development of functional food.

Lactoferrin (LF) with various biological functions demonstrates great application potential. However, its application was restricted by its poor gelation and instability. The aim of this work was to explore the effect of microbial transglutaminase (MTGase) and Tremella fuciformis polysaccharide (TP) on the functional properties of LF. The formation of a self-supporting LF gel could be induced by MTGase through generating covalent crosslinks between the LF protein molecules. Meanwhile, TP was introduced into the gel system to improve the strength of LF-TP composite gels by enhancing non-covalent interactions such as hydrogen bond and electrostatic interactions during gel formation. Additionally, the LF-TP composite gel exhibited outstanding functional characteristics such as gastrointestinal digestive stability and antioxidant property. This work clarified the mechanism on MTGase and TP-mediated modification of lactoferrin, offered a novel strategy to increase the functional characteristics of LF, and enlarged the application range of LF and TP.

Unlocking high-efficiency decontamination by building a novel heterogeneous catalytic reduction system of thiourea dioxide/biochar.

Herein, we reported a new contaminant purification paradigm, which enabled highly efficient reductive denitration and dechlorination using a green, stable reducing agent thiourea dioxide (TDO) coupled with biochar (BC) over a wide pH range under anoxic conditions. Specifically, BC acted as both activators and electron shuttles for TDO decomposition to achieve complete anoxic degradation of p-nitrophenol (PNP), p-nitroaniline, 4-chlorophenol and 2,4-dichlorophenol within 2 h. During this process, multiple strongly reducing species (i.e., SO22-, SO2•- and e-/H•) were generated in BC/TDO systems, accounting for 13.3%, 9.7% and 75.5% of PNP removal, respectively. While electron transfer between TDO and H+ or contaminants mediated by BC led to H• generation and contaminant reduction. These processes depended on the electron-accepting capacity and electron-conducting domains of biochar. Significantly, the BC/TDO systems were highly efficient at a pH of 2.0-8.0, especially under acidic conditions, which performed robustly in common natural water constituents.

Effect of sanxan as novel natural gel modifier on the physicochemical and structural properties of microbial transglutaminase-induced mung bean protein isolate gels.

Mung bean protein isolate (MBPI) has attracted much attention as an emerging plant protein. However, its application was limited by the poor gelling characteristics. Thus, the effect of sanxan (SAN) on the gelling behavior of MBPI under microbial transglutaminase (MTG)-induced condition were explored in this study. The results demonstrated that SAN remarkably enhanced the storage modulus, water-holding capacity and mechanical strength. Furthermore, SAN changed the microstructure of MBPI gels to become more dense and ordered. The results of zeta potential indicated the electrostatic interactions existed between SAN and MBPI. The incorporation of SAN altered the secondary structure and molecular conformation of MBPI, and hydrophobic interactions and hydrogen bonding were necessary to maintain the network structure. Additionally, in vitro digestion simulation results exhibited that SAN remarkably improved the capability of MBPI gels to deliver bioactive substances. These findings provided a practical strategy to use natural SAN to improve legume protein gels.

Machine-learning intervention progress in the field of organic waste composting: Simulation, prediction, optimization, and challenges.

Aerobic composting stands as a widely-adopted method for treating organic solid waste (OSW), simultaneously producing organic fertilizers and soil amendments. This biologically-driven biochemical reaction process, however, presents challenges due to its complex non-linear metabolism and the heterogeneous nature of the solid medium. These characteristics inherently limit the simulation accuracy and efficiency optimization in aerobic composting. Recently, significant efforts have been made to simulate and control composting process parameters, as well as predicting and optimizing composting product quality. Notably, the integration of machine learning (ML) in aerobic composting of organic waste has garnered considerable attention for its applicability and predictive capability in exploring the complex non-linear relationships of organic waste composting parameters. Despite numerous studies on ML applications in OSW composting, a systematic review of research findings in this field is lacking. This study offers a systematic overview of the application level, current status, and versatility of ML in OSW composting. It spans various aspects, such as compost maturity, environmental pollutants, nutrients, moisture, heat loss, and microbial metabolism. The survey reveals that ML-intervention predominantly focuses on compost maturity and environmental pollutants, followed by nutrients, moisture, heat loss, and microbial activity. The most commonly employed predictive models and optimization algorithms are artificial neural networks (47%) and genetic algorithms (10%). These demonstrate high prediction accuracy and maximize composting efficiency in the simulation and prediction of organic waste composting, alongside regulation of key parameters. Deep neural networks and ensemble learning models prove effective in achieving superior predictive performance by selecting feature variables in compost maturity and pollutant residue prediction of organic waste composting in a simpler and more objective manner.

Novel perspective on qualitative assessment of swine manure compost maturity using organic carbon density fractions.

Mature compost is safe and stable, yet quality assessments are challenging owing to current maturity indicators' limitations. This study employed density fractionation to separate organic carbon into light and heavy fractions, offering a new perspective for assessing maturity. Results showed that light fraction organic carbon progressively transitioned into heavy fraction during composting, reducing the proportion of total organic carbon from 82.82% to 44.03%, while heavy fraction organic carbon increased to 48.58%. During the first seven days, the reduction rate of light fraction organic carbon decreased slowly, while the increase rate of heavy fraction declined sharply, levelling off thereafter. Light/heavy fraction organic carbon ratio was significantly correlated with existing maturity indicators (carbon/nitrogen ratio, humic acid/fulvic acid ratio, biological growth-related indicators), with the ratio below 1.33 serving as a potential compost maturity marker. Thus, given its simplicity and reliability, organic carbon density fractions is an innovative indicator for compost maturity assessments.

Synergistic effects of microbial transglutaminase and apple pectin on the gelation properties of pea protein isolate and its application to probiotic encapsulation.

The low gelation capacity of pea protein isolate (PPI) limits their use in food industry. Therefore, microbial transglutaminase (MTG) and apple pectin (AP) were combined to modify PPI to enhance its gelling characteristics, and the mechanism of MTG-induced PPI-AP composite gel generation was investigated. PPI (10 wt%) could not form a gel at 40 °C, while MTG-treated PPI (10 wt%) formed a self-supporting gel at 40 °C. Subsequently, the addition of AP further promoted the crosslinking of PPI and significantly improved the water holding capacity, rheology, and strength of PPI gels, which was attributed to both hydrogen and isopeptide bonds in the composite gel. Additionally, the PPI-AP composite gel showed excellent protection ability, and the survival rate of probiotics could reach over 90%, which could be used as an effective delivery system. This study verified that MTG and AP were efficient in enhancing the functional quality of PPI gels.

Synaptotagmin 1 Suppresses Colorectal Cancer Metastasis by Inhibiting ERK/MAPK Signaling-Mediated Tumor Cell Pseudopodial Formation and Migration.

Although synaptotagmin 1 (SYT1) has been identified participating in a variety of cancers, its role in colorectal cancer (CRC) remains an enigma. This study aimed to demonstrate the effect of SYT1 on CRC metastasis and the underlying mechanism. We first found that SYT1 expressions in CRC tissues were lower than in normal colorectal tissues from the CRC database and collected CRC patients. In addition to this, SYT1 expression was also lower in CRC cell lines than in the normal colorectal cell line. SYT1 expression was downregulated by TGF-ß (an EMT mediator) in CRC cell lines. In vitro, SYT1 overexpression repressed pseudopodial formation and reduced cell migration and invasion of CRC cells. SYT1 overexpression also suppressed CRC metastasis in tumor-bearing nude mice in vivo. Moreover, SYT1 overexpression promoted the dephosphorylation of ERK1/2 and downregulated the expressions of Slug and Vimentin, two proteins tightly associated with EMT in tumor metastasis. In conclusion, SYT1 expression is downregulated in CRC. Overexpression of SYT1 suppresses CRC cell migration, invasion, and metastasis by inhibiting ERK/MAPK signaling-mediated CRC cell pseudopodial formation. The study suggests that SYT1 is a suppressor of CRC and may have the potential to be a therapeutic target for CRC.

Histone crotonylation of peripheral blood mononuclear cells is a potential biomarker for diagnosis of colorectal cancer.

BACKGROUND: Blood-based tests have public appeal in screening cancers due to their minimally invasive nature, ability to integrate with other routine blood tests, and high compliance. This study aimed to investigate whether certain epigenetic modulation of peripheral blood mononuclear cells (PBMCs) could be a biomarker of colorectal cancer (CRC). RESULTS: Western blotting of histones in the PBMCs from 40 colorectal cancer patients and 40 healthy controls was performed to identify the crotonylation sites of proteins. The correlation of crotonylation with tumor staging and diagnostic efficacy were analyzed. Crotonylation of H2BK12 (H2BK12cr) was identified significantly upregulated in the PBMCs of CRC patients compared to healthy controls, and were closely related to distant metastasis (P = 0.0478) and late TNM stage (P = 0.0201). Receiver operator characteristic curve (ROC) analysis demonstrated that the area under curve (AUC) of H2BK12cr was 0.8488, the sensitivity was 70%, and the specificity was 92.5%. The H2BK12cr parameter significantly increased the diagnostic effectiveness of CRC compared with the commercial carcinoembryonic antigen assays. CONCLUSIONS: The H2BK12cr level in PBMCs of CRC patients has a potential to be a biomarker for distinguishing CRC patients from healthy controls with the advantages of easy operation and high diagnostic efficacy.

Evaluation of mechanical and biological properties of akermanite/poly-ether-ether- ketone composite fabricated by high- temperature laser powder bed fusion.

High-temperature laser bed powder fusion (HT-LPBF) technology is an ideal method for processing poly-ether-ether-ketone (PEEK) implants with personalized bionic structures, but the biological inertia of PEEK limits its medical applications. In this study, we evaluated the mechanical and biological properties of a novel akermanite (AKM)/PEEK composite for HT-LPBF. The results showed that tiny AKM particles are evenly attached to the surface of the PEEK particle. The delayed peak crystallization temperature and stable sintering window ensure the processing feasibility of the AKM/PEEK composites. The tensile strength and Young's modulus are in the range of 30.83-98.73 MPa and 2.27-3.71 GPa, respectively, which can match the properties of cancellous bones and meet their implanting requirement. The CCK-8 experiments demonstrated the biocompatibility of the composites and the good proliferation of bone marrow stromal cells. The dense hydroxyapatite network layer and petal-like hydroxyapatite demonstrates biological activity, indicating that the composite has a good potential in the orthopedics fields.

External static magnetic field potentiates the reduction of antibiotic resistance genes during swine manure composting.

Livestock and poultry manure are repositories of antibiotic resistance genes (ARGs). Accumulating evidence suggests that composting is an important way to effectively attenuate ARGs, but how to reinforce the reduction in ARGs during composting needs to be further investigated. This study explored the influence of an external static magnetic field on ARG mitigation enhancement during swine manure composting. The results showed that a total of 12 high-risk ARGs were identified. A relatively high magnetic field intensity (14.81 mT) was more effective in reducing the abundance of high-risk ARGs, and the removal rate was 20.66-100 %. It also reduced the abundance of 27.14 % of integrons, 79.44 % of insertion sequences, and 8.78 % of plasmids. Partial least squares path modeling showed that a relatively high magnetic field intensity treatment promoted the reduction in ermB by reducing the abundance of Phascolarctobacterium, Streptococcus, and insertion sequences. It also mitigated sul1 expression by reducing the abundance of Acinetobacter and integrons, and it mitigated tetM expression by decreasing Lactobacillus, Streptococcus, insertion sequences, and plasmids. These findings demonstrate that an external static magnetic field is an effective method for intensifying the reduction in ARGs, providing a feasible reference for controlling the potential ARG risk of organic waste composting.

Review of explainable machine learning for anaerobic digestion.

Anaerobic digestion (AD) is a promising technology for recovering value-added resources from organic waste, thus achieving sustainable waste management. The performance of AD is dictated by a variety of factors including system design and operating conditions. This necessitates developing suitable modelling and optimization tools to quantify its off-design performance, where the application of machine learning (ML) and soft computing approaches have received increasing attention. Here, we succinctly reviewed the latest progress in black-box ML approaches for AD modelling with a thrust on global and local model interpretability metrics (e.g., Shapley values, partial dependence analysis, permutation feature importance). Categorical applications of the ML and soft computing approaches such as what-if scenario analysis, fault detection in AD systems, long-term operation prediction, and integration of ML with life cycle assessment are discussed. Finally, the research gaps and scopes for future work are summarized.

Effective adsorption and catalytic reduction of nitrophenols by amino-rich Cu(I)-I coordination polymer.

Nitrophenols are identified as the priority organic pollutants due to the chemical stability, water solubility, persistence, and toxicity to human health and the environment. Hence, removal of nitrophenols from waste water is vitally essential. In this study, amino-rich coordination polymer Cu2I2(MA)2 (MA = melamine) has been applied for efficient adsorption and catalytic reduction of nitrophenols, like 4-nitrophenol (4-NP), 2, 4-dinitrophenol (DNP) and 2, 4, 6-trinitrophenol (TNP). The effect of various parameters like contact time, initial concentrations, pH, and temperature on adsorption were investigated. The adsorption of nitrophenols fitted the pseudo-second-order kinetic model and Langmuir isotherms model well. The maximum adsorption capacities were 285.71, 232.02, and 131.57 mg g-1 for 4-NP, DNP, and TNP when initial concentrations were 50 mg L-1 at 293.15 K, respectively. The adsorption of nitrophenols is a spontaneous, endothermic, and entropy-driven process. The reduction reaction followed the pseudo-first-order kinetics, and the kinetic rate constants were 0.4413, 0.3167, and 0.17538 min-1 for 4-NP, DNP, and TNP, respectively. The effect of initial nitrophenols concentration, anions, and temperature on reduction process was investigated. The mechanism of adsorption and catalytic reduction of Cu2I2(MA)2 was studied. The results demonstrated that Cu2I2(MA)2 exhibits excellent adsorption and catalytic activity to remove nitrophenols.

Transcriptomics and Metabolomics Analysis of Sclerotium rolfsii Fermented with Differential Carbon Sources.

Scleroglucan is obtained from Sclerotium rolfsii and is widely used in many fields. In this study, transcriptomics combined with metabolomics were used to study the global metabolites and gene changes. The results of the joint analysis showed that the DEGs (differentially expressed genes) and DEMs (differentially expressed metabolites) of SEPS_48 (fermented with sucrose as a carbon source for 48 h) and GEPS_48 (fermented with glucose as a carbon source for 48 h) comparison groups were mainly related to cell metabolism, focusing on carbohydrate metabolism, amino acid metabolism, and amino sugar and nucleoside sugar metabolism. We therefore hypothesized that the significant differences in these metabolic processes were responsible for the differences in properties. Moreover, the joint analysis provides a scientific theoretical basis for fungal polysaccharides biosynthesis and provides new insights into the effects of carbon sources on the production. As an excellent bioenergy and biological product, scleroglucan can be better applied in different fields, such as the food industry.

Crosslinking Mechanism on a Novel Bacillus cereus Transglutaminase-Mediated Conjugation of Food Proteins.

Until now, Streptoverticillium mobaraense transglutaminase (TG) is the only commercialized TG, but limited information is known about its selection tendency on crosslinking sites at the protein level, restricting its application in the food industry. Here, four recombinant Bacillus TGs were stable in a broad range of pH (5.0−9.0) and temperatures (<50 °C), exhibiting their maximum activity at 50−60 °C and pH 6.0−7.0. Among them, TG of B. cereus (BCETG) demonstrated the maximal specific activity of 177 U/mg. A structural analysis indicated that the Ala147-Ala156 region in the substrate tunnel of BCETG played a vital role in catalytic activity. Furthermore, bovine serum albumin, as well as nearly all protein ingredients in soy protein isolate and whey protein, could be cross-linked by BCETG, and the internal crosslinking paths of three protein substrates were elucidated. This study demonstrated Bacillus TGs are a candidate for protein crosslinking and provided their crosslinking mechanism at the protein level for applications in food processing.

Predictors of the Public's Aversion to Patients Infected with COVID-19 in China: The Mediating Role of Negative Physiology.

COVID-19 has had a lasting impact on the public's mental health. Understanding the mechanism of the formation of the public's aversion to COVID-19-infected people can not only help eliminate the irrational stigma, rejection, and aversion of the public but also promote the creation of a harmonious and healthy social atmosphere. Based on stimulus-organism-response theory, this study explored the relationships between environmental stimuli, public negative physiology, and aversion responses. A cross-sectional, online-based survey study was conducted in April 2022. A total of 1863 effective questionnaires from respondents of various ages, genders, incomes, and education levels were acquired. Structural equation modeling was used to test the proposed model. The environmental stimuli including the use of social media and the perception of risk communication aggravated the negative physiology of the public, while the public's perception of prevention measures reduced the public's negative physiology during the epidemic. The negative physiology of the public increases the public's aversion responses, including disgust, stigma, and avoidance, toward patients infected with COVID-19. The negative physiology of the public plays a mediating role in the relationship between the environmental stimuli and the public's aversion to patients infected with COVID-19. The emergence of excessive information in social media and strict prevention measures in daily life, as well as the dissemination of a large amount of risk information in pseudo-environments and realistic environments, have all exerted an impact on public sentiment and cognition. In the case of the prolonged spread of the epidemic, the accumulation of negative physiology, such as anxiety, panic, and depression, is more likely to lead to the public's aversion to people with COVID-19.

Values of OAS gene family in the expression signature, immune cell infiltration and prognosis of human bladder cancer.

BACKGROUND: Bladder cancer (BLCA) is one of the most common genitourinary malignancies in the world, but its pathogenic genes have not been fully identified and the treatment outcomes are still unsatisfactory. Although the members of 2', 5'-oligoadenylate synthetase (OAS) gene family are known involved in some tumorous biological processes, the roles of the OAS gene family in BLCA are still undetermined. METHODS: By combining vast bioinformatic datasets analyses of BLCA and the experimental verification on clinical BLCA specimen, we identified the expressions and biological functions of OAS gene family members in BLCA with comparison to normal bladder tissues. RESULTS: The expression levels of OAS gene family members were higher in BLCA than in normal bladder tissues. The expression levels of most OAS genes had correlations with genomic mutation and methylation, and with the infiltration levels of CD4 + T cells, CD8 + T cells, neutrophils, and dendritic cells in the microenvironment of BLCA. In addition, high expressions of OAS1, OAS2, OAS3, and OASL predicted better overall survival in BLCA patients. CONCLUSIONS: The highly expressed OAS genes in BLCA can reflect immune cells infiltration in the tumor microenvironment and predict the better overall survival of BLCA, and thus may be considered as a signature of BLCA. The study provides new insights into the diagnosis, treatment, and prognosis of BLCA.

A Numerical Simulation Method Considering Solid Phase Transformation and the Experimental Verification of Ti6Al4V Titanium Alloy Sheet Welding Processes.

A prediction model of the welding process of Ti-6Al-4V titanium alloy was established by using the finite element method, which was used to evaluate the phase composition, residual stress and deformation of the welded joints of Ti-6Al-4V sheets with different processes (including tungsten inert gas welding, TIG, and laser beam welding, LBW). The Ti-6Al-4V structures of TIG welding and LBW are widely used in marine engineering. In order to quantitatively study the effects of different welding processes (including TIG welding and LBW) on the microstructure evolution, macro residual stress and deformation of Ti6Al4V titanium alloy sheets during welding, a unified prediction model considering solid-state phase transformation was established based on the ABAQUS subroutine. In this paper, LBW and TIG welding experiments of 1.6 mm thick Ti-6Al-4V titanium alloy sheets were designed. The microstructure distribution of the welded joints observed in the experiment was consistent with the phase composition predicted by the model, and the hardness measurement experiment could also verify the phase composition and proportion. From the residual stress measured by experiment and the residual stress and deformation calculated by finite element simulation of LBW and TIG weldments, it is concluded that the effect of phase transformation on residual stress is mainly in the weld area, which has an effect on the distribution of tensile and compressive stress in the weld area. The overall deformation of the welded joint is mainly related to the welding process, and the phase transformation only affects the local volume change of the weld seam. Importantly, the phase composition and residual stress, which are scalar fields, calculated by the established model can be introduced into the numerical analysis of structural fracture failure as input influence factors.

Defect-Free Arbitrary-Geometry Assembly of Mixed-Species Atom Arrays.

Optically trapped mixed-species single atom arrays with arbitrary geometry are an attractive and promising platform for various applications, because tunable quantum systems with multiple components provide extra degrees of freedom for experimental control. Here, we report the first demonstration of two-dimensional 6×4 dual-species atom assembly of ^{85}Rb (^{87}Rb) atoms with a filling fraction of 0.88 (0.89). This mixed-species atomic synthesis is achieved via rearranging initially randomly distributed atoms by a sorting algorithm (heuristic heteronuclear algorithm) which is designed for bottom-up atom assembly with both user-defined geometries and two-species atom number ratios. Our fully tunable hybrid-atom systems with scalable advantages are a good starting point for high-fidelity quantum logic, many-body quantum simulation, and single molecule array formation.