Fabrication of soy protein nanoparticles based on metal-phenolic networks for stabilization of nano-emulsions delivery system.

The use of soy protein isolate (SPI) nanoparticles as a stabilizer in nano-emulsion systems has garnered significant interest. While metal-phenolic networks (MPNs) have been explored for their multifunctional surface modification capabilities, their integration with food protein-based delivery systems remains less explored. In this study, we attempt to develop a novel strategy to encapsulate cinnamaldehyde using MPNs (EGCG-Fe3+) with self-assembling soy protein nanoparticles (SE-Fe NPs) as a stabilizer for nano-emulsions. UV, Raman, and X-ray photoelectron spectroscopy analyses demonstrated that SE-Fe NPs were generated through metal-phenolic coordination and covalent interactions. SE-Fe NPs had a narrower particle size distribution and enhanced radical scavenging (up to 3.35-fold), as well as thermal stability. Furthermore, the smaller droplet size, higher modulus, higher cinnamaldehyde encapsulation efficiency (from 63.5% to 84.2%), and improved bio-accessibility of SE-Fe NPs stabilized nano-emulsions delivery system demonstrated in this study shows promising future applications in the food industry.

Corn straw-saccharification fiber improved the reproductive performance of sows in the late gestation and lactation via lipid metabolism.

With the development of animal husbandry, the shortage of animal feedstuffs has become serious. Dietary fiber plays a crucial role in regulating animal health and production performance. The aim of this study was to investigate the effects of three kinds of corn straw-saccharification fibers (CSSF) such as high-fiber and low-saccharification (HFLS), medium-fiber and medium-saccharification (MFMS), low-fiber and high-saccharification (LFHS) CSSF on the reproductive performance of sows. Thirty-two primiparous Yorkshire sows were randomly assigned to 4 groups, 8 sows for each group. Group A was the basal diet as the control group; groups B - D were added with 6% HFLSCSSF, 6% MFMSCSSF and 6% LFHSCSSF to replace some parts of corn meal and wheat bran in the basal diet, respectively. The experimental period was from day 85 of gestation to the end of lactation (day 25 post-farrowing). The results showed that 6% LFHSCSSF addition significantly increased number of total born (alive) piglets, litter weight at birth (p < 0.05), whereas three kinds of CSSF significantly decreased backfat thickness of sows during gestation (p < 0.001), compared with the control group. Furthermore, CSSF improved the digestibility of crude protein, ether extract and fiber for sows. In addition, the levels of total cholesterol, total triglycerides, and high-density lipoprotein cholesterol in serum of sows were decreased by different kinds of CSSF. Further analysis revealed that CSSF regulated lipid metabolism through adjusting the serum metabolites such as 4-pyridoxic acid, phosphatidyl cholines and L-tyrosine. In summary, CSSF addition to the diets of sows during late gestation and lactation regulated lipid metabolism and improved reproductive performance of sows. This study provided a theoretical basis for the application of corn straw in sow diets.

Advancements in acne detection: application of the CenterNet network in smart dermatology.

Introduction: Acne detection is critical in dermatology, focusing on quality control of acne imagery, precise segmentation, and grading. Traditional research has been limited, typically concentrating on singular aspects of acne detection. Methods: We propose a multi-task acne detection method, employing a CenterNet-based training paradigm to develop an advanced detection system. This system collects acne images via smartphones and features multi-task capabilities for detecting image quality and identifying various acne types. It differentiates between noninflammatory acne, papules, pustules, nodules, and provides detailed delineation for cysts and post-acne scars. Results: The implementation of this multi-task learning-based framework in clinical diagnostics demonstrated an 83% accuracy in lesion categorization, surpassing ResNet18 models by 12%. Furthermore, it achieved a 76% precision in lesion stratification, outperforming dermatologists by 16%. Discussion: Our framework represents a advancement in acne detection, offering a comprehensive tool for classification, localization, counting, and precise segmentation. It not only enhances the accuracy of remote acne lesion identification by doctors but also clarifies grading logic and criteria, facilitating easier grading judgments.

Epigenetic regulation in adult neural stem cells.

Neural stem cells (NSCs) exhibit self-renewing and multipotential properties. Adult NSCs are located in two neurogenic regions of adult brain: the ventricular-subventricular zone (V-SVZ) of the lateral ventricle and the subgranular zone of the dentate gyrus in the hippocampus. Maintenance and differentiation of adult NSCs are regulated by both intrinsic and extrinsic signals that may be integrated through expression of some key factors in the adult NSCs. A number of transcription factors have been shown to play essential roles in transcriptional regulation of NSC cell fate transitions in the adult brain. Epigenetic regulators have also emerged as key players in regulation of NSCs, neural progenitor cells and their differentiated progeny via epigenetic modifications including DNA methylation, histone modifications, chromatin remodeling and RNA-mediated transcriptional regulation. This minireview is primarily focused on epigenetic regulations of adult NSCs during adult neurogenesis, in conjunction with transcriptional regulation in these processes.

Modulatory role of neuropeptide FF system in macrophages.

Neuropeptide FF (NPFF) is an octapeptide that regulates various cellular processes, especially pain perception. Recently, there has been a growing interest in understanding the modulation of NPFF in neuroendocrine inflammation. This review aims to provide a thorough overview of the regulation of NPFF in macrophage-mediated biological processes. We delve into the impact of NPFF on macrophage polarization, self-renewal modulation, and the promotion of mitophagy, facilitating the transition from thermogenic fat to fat-storing adipose tissue. Additionally, we explore the NPFF-dependent regulation of the inflammatory response mediated by macrophages, its impact on the differentiation of macrophages, and its capacity to induce alterations in the transcriptome of macrophages. We also address the potential of NPFF as a therapeutic molecule in the field of neuroendocrine inflammation. Overall, our work offers an understanding of the influence of NPFF on macrophage, facilitating the exploration of its pharmacological significance in future studies.

The transcriptomic landscape of canonical activation of NLRP3 inflammasome from bone marrow-derived macrophages.

The NLRP3 inflammasome has gained significant attention due to its participation in diverse cellular processes. Nevertheless, the detailed framework of the canonical NLRP3 inflammasome assembly still remains unrevealed. This study aims to elucidate the transcriptomic landscape of the various stages involved in the canonical activation of the NLRP3 inflammasome in BMDMs by integrating RNA-seq, bioinformatics, and molecular dynamics analyses. The model for the canonical activation of the NLRP3 inflammasome was confirmed through morphological observations, functional assessments (ELISA and LDH), and protein detection (western blot). Subsequently, cells were subjected to RNA sequencing following three groups: control, priming (LPS 500 ng/ml, 4 h), and activation (LPS 500 ng/ml, 4 h; ATP 5 mM, 1 h). A total of 9116 differentially expressed genes (DEGs) were identified, which exerted regulatory effects on various pathways, including cell metabolism, ion fluxes, post-translational modifications, and organelles. Subsequently, six hub genes (Sirt3, Stat3, Syk, Trpm2, Tspo, and Txnip) were identified via integrating literature review and database screening. Finally, the three-dimensional structures of these six hub proteins were obtained using the MD-optimized RoseTTAFold and Gromacs simulations (at least 200 ns). In summary, our research offers novel insights into the transcriptomic-level understanding of the assembly of the canonical NLRP3 inflammasome.

Quantitative energy spectrum CT in differential diagnosis of aldosterone-producing adenoma and cortisol-producing adenoma.

Background: Patients with aldosterone-producing adenoma (APA) and cortisol-producing adenoma (CPA) show some similar clinical symptoms, and a large overlap of conventional imaging manifestations, which make the differentiation difficult. The purpose of our study was to explore the value of gemstone spectral imaging (GSI) dual-energy computed tomography (DECT) in differential diagnosis of APA and CPA, screen out meaningful energy spectral indicators and provide theoretical basis for the differential diagnosis of the two. Methods: We retrospectively analyzed the imaging and clinical data of 30 patients with APA and 27 patients with CPA who underwent GSI DECT in The First Affiliated Hospital of Zhengzhou University (a tertiary care institution). Patients were consecutively enrolled in this study, and the quantitative DECT parameters were compared between the APA and CPA groups by two-sample test. The diagnostic efficacies were evaluated by receiver operating characteristic (ROC) analysis. Results: DECT parameters including CT (computed tomography) values at 40-70 keV in the arterial phase, concentrations of I (H2O) and fat (I) in the arterial phase, and the effective atomic number in the venous phase, were significantly different between the APA and CPA groups (all P<0.001), and the area under the curve (AUC) values are 0.80, 0.79, 0.88, 0.76, 0.82, 0.87, and 0.86. Conclusions: DECT quantitative parameters can effectively identify APA and CPA, the CT values at 40 and 60 keV in the arterial phase, the normalized CT value at 60 keV, the I (H2O), fat (I) concentration in the arterial phase and the effective atomic number parameter in the venous phase had valuable diagnostic performance.

A Novel Optimized iBeacon Localization Algorithm Modeling.

The conventional methods for indoor localization rely on technologies such as RADAR, ultrasonic, laser range localization, beacon technology, and others. Developers in the industry have started utilizing these localization techniques in iBeacon systems that use Bluetooth sensors to measure the object's location. The iBeacon-based system is appealing due to its low cost, ease of setup, signaling, and maintenance; however, with current technology, it is challenging to achieve high accuracy in indoor object localization or tracking. Furthermore, iBeacons' accuracy is unsatisfactory, and they are vulnerable to other radio signal interference and environmental noise. In order to address those challenges, our study focuses on the development of error modeling algorithms for signal calibration, uncertainty reduction, and interfered noise elimination. The new error modeling is developed on the Curve Fitted Kalman Filter (CFKF) algorithms. The reliability, accuracy, and feasibility of the CFKF algorithms are tested in the experiments. The results significantly show the improvement of the accuracy and precision with this novel approach for iBeacon localization.

Paenibacillus sedimenti sp. nov., isolated from freshwater wetland sediment.

A Gram-stain-positive, motile, rod-shaped, facultatively anaerobic bacterium, designated strain WST5T, isolated from sediment was characterized using a polyphasic approach. Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain WST5T was most closely related to Paenibacillus aestuarii CJ25T (96.8 % similarity). The genome size of the WST5T was 6.5 Mb, contained 4500 predicted protein-coding genes, and had a DNA G+C content of 46.6%. The values of whole-genome average nucleotide identity analysis and digital DNA-DNA hybridization between strain WST5T and its closely related type strains were less than 76 and 25.6 %, respectively. The predominant cellular fatty acids (>10 %) were anteiso-C15 : 0 and C16 : 1 ω5c and the main menaquinone was MK-7. The major polar lipids were identified as diphospholidylglycerol, phosphatidylethanolamine, phosphatidylglycerol and two unknown aminophospholipids. Based on the results of phenotypic, genotypic, chemotaxonomic and phylogenetic analyses, strain WST5T is considered to represent a novel species of the genus Paenibacillus, for which the name Paenibacillus sedimentum sp. nov. is proposed. The type strain is WST5T (=NBRC 115194 T=CGMCC 1.18706T).

Technical comparison of continuous versus intermittent perfusion computed tomography computed tomography scans of the human pancreas.

Background: Pancreatic perfusion computed tomography (CT) imaging is increasingly used for neoplastic grading, predicting prognosis, and evaluating the response to therapy. To optimize the clinical pancreatic CT perfusion imaging methods, we evaluated 2 different CT scanning protocols concerning pancreas perfusion parameters. Methods: A retrospective study was conducted on 40 patients who underwent whole pancreas CT perfusion scanning in The First Affiliated Hospital of Zhengzhou University. Of these 40 patients, 20 patients in group A underwent continuous perfusion scanning, while 20 patients in group B underwent intermittent perfusion scanning. For group A, continuous axial scanning was performed 25 times, and the total scan time was 50 s. For group B, arterial phase helical perfusion scanning was performed 8 times, and then venous phase helical perfusion scanning was performed 15 times, with a total scan time of 64.6 to 70.0 s. A comprehensive list of perfusion parameters between different parts of the pancreas and the 2 groups were compared. The effective radiation dose for the 2 scanning methods was analyzed. Results: The parameter of the mean slope of increase (MSI) at different pancreatic parts in group A differed (P=0.028). The pancreas head had the lowest value, and the tail had the highest (about a 20% difference). In group A compared to group B, the blood volume of the pancreatic head was smaller (15.256±2.925 vs. 16.953±3.602), the positive enhanced integral was smaller (0.307±0.050 vs. 0.344±0.060) and the permeability surface was larger (34.205±9. 612 vs. 24.377±8.413); the blood volume of the pancreatic neck was smaller (13.940±2.691 vs. 17.173±3.918), the positive enhanced integral was smaller (0.304±0.088 vs. 0.361±0.051) and the permeability surface was larger (34.898±11.592 vs. 25. 794±8.149); the blood volume of the pancreatic body was smaller (16.142±4.006 vs. 18.401±2.513), the positive enhanced integral was smaller (0.305±0.093 vs. 0.342±0.048) and the permeability surface was larger (28.861±10.448 vs. 22.158±6. 017); the blood volume of the pancreatic tail was smaller (16.446±3.709 vs. 17.374±3.781), the positive enhanced integral was smaller (0.304±0.057 vs. 0.350±0.073) and the permeability surface was larger (27.823±8.228 vs. 21.509±7.768) (P<0.05). The effective radiation dose in the intermittent scan mode was slightly lower at 16.657±2.259 mSv than in the continuous scan mode (17.973±3.698 mSv). Conclusions: Different CT scanning intervals had a significant influence on whole pancreas blood volume, permeability surface, and positive enhanced integral. These demonstrate the high sensitivity of intermittent perfusion scanning for identifying perfusion abnormalities. Therefore, for the diagnosis of pancreatic diseases, intermittent pancreatic CT perfusion may be more advantageous.

Impacts of Random Atomic Defects on Critical Buckling Stress of Graphene under Different Boundary Conditions.

Buckled graphene has potential applications in energy harvest, storage, conversion, and hydrogen storage. The investigation and quantification analysis of the random porosity in buckled graphene not only contributes to the performance reliability evaluation, but it also provides important references for artificial functionalization. This paper proposes a stochastic finite element model to quantify the randomly distributed porosities in pristine graphene. The Monte Carlo stochastic sampling process is combined with finite element computation to simulate the mechanical property of buckled graphene. Different boundary conditions are considered, and the corresponding results are compared. The impacts of random porosities on the buckling patterns are recorded and analyzed. Based on the large sampling space provided by the stochastic finite element model, the discrepancies caused by the number of random porosities are discussed. The possibility of strengthening effects in critical buckling stress is tracked in the large sampling space. The distinguishable interval ranges of probability density distribution for the relative variation of the critical buckling stress prove the promising potential of artificial control by the atomic vacancy amounts. In addition, the approximated Gaussian density distribution of critical buckling stress demonstrates the stochastic sampling efficiency by the Monte Carlo method and the artificial controllability of porous graphene. The results of this work provide new ideas for understanding the random porosities in buckled graphene and provide a basis for artificial functionalization through porosity controlling.

Choroidal blood perfusion could predict the sensitivity of myopia formation in Guinea pigs.

In this study, we explored the predictive role of choroidal blood perfusion (ChBP) and choroidal thickness (ChT) on the development of myopia in guinea pigs. Optical Coherence Tomography Angiography (OCTA) was used to assess the baseline choroidal blood perfusion (ChBP) and choroidal thickness (ChT) in 4-week-old guinea pigs. Refraction and axial length (AL) were measured at baseline. Myopia was induced for one week using form-deprivation (FD) or negative lenses followed by measurements of refraction, axial length and choroidal parameters (ChT and ChBP). The correlations were evaluated between the baseline choroidal values and the magnitude of myopia induced, along with the magnitude of changes in ChT and ChBP after myopia induction. There was a significant correlation between the baseline choroidal parameters and ocular refraction. Myopia induction led to choroidal thinning and less ChBP as well as longer eyes. On the other hand, following exposure to the same non-obstructed visual induction period, the myopic shift was less, and it was associated with thicker choroids and more ChBP at baseline. One week of myopia induction also resulted in thinner choroids and less ChBP, and these declines also correlated with their baseline values. In conclusion, the present study shows that the changes in the baseline choroidal ChT and ChBP parameters are proportional to the magnitude of myopia development and axial elongation in guinea pigs. These significant correlations between baseline ChBP and ChT and myopia development suggest that they may be a viable predictor of this process in guinea pigs.

DNA methyltransferases are complementary in maintaining DNA methylation in embryonic stem cells.

ZFP57 and ZFP445 maintain genomic imprinting in mouse embryos. We found DNA methylation was lost at most examined imprinting control regions (ICRs) in mouse Zfp57 mutant ES cells, which could not be prevented by the elimination of three TET proteins. To elucidate methylation maintenance mechanisms, we generated mutant ES clones lacking three major DNA methyltransferases (DNMTs). Intriguingly, DNMT3A and DNMT3B were essential for DNA methylation at a subset of ICRs in mouse ES cells although DNMT1 maintained DNA methylation at most known ICRs. These were similarly observed after extended culture. Germline-derived DNA methylation was lost at the examined ICRs lacking DNMTs according to allelic analysis. Similar to DNMT1, DNMT3A and DNMT3B were required for maintaining DNA methylation at repeats, genic regions, and other genomic sequences. Therefore, three DNA methyltransferases play complementary roles in maintaining DNA methylation in mouse ES cells including DNA methylation at the ICRs primarily mediated through the ZFP57-dependent pathway.

The Uncertainty Propagation for Carbon Atomic Interactions in Graphene under Resonant Vibration Based on Stochastic Finite Element Model.

Graphene is one of the most promising two-dimensional nanomaterials with broad applications in many fields. However, the variations and fluctuations in the material and geometrical properties are challenging issues that require more concern. In order to quantify uncertainty and analyze the impacts of uncertainty, a stochastic finite element model (SFEM) is proposed to propagate uncertainty for carbon atomic interactions under resonant vibration. Compared with the conventional truss or beam finite element models, both carbon atoms and carbon covalent bonds are considered by introducing plane elements. In addition, the determined values of the material and geometrical parameters are expanded into the related interval ranges with uniform probability density distributions. Based on the SFEM, the uncertainty propagation is performed by the Monte Carlo stochastic sampling process, and the resonant frequencies of graphene are provided by finite element computation. Furthermore, the correlation coefficients of characteristic parameters are computed based on the database of SFEM. The vibration modes of graphene with the extreme geometrical values are also provided and analyzed. According to the computed results, the minimum and maximum values of the first resonant frequency are 0.2131 and 16.894 THz, respectively, and the variance is 2.5899 THz. The proposed SFEM is an effective method to propagate uncertainty and analyze the impacts of uncertainty in the carbon atomic interactions of graphene. The work in this paper provides an important supplement to the atomic interaction modeling in nanomaterials.

Applications of functionalized magnetic biochar in environmental remediation: A review.

Magnetic biochar (MBC) is extensively applied on contaminants removal from environmental medium for achieving environmental-friendly remediation with reduction of secondary pollution owing to its easy recovery and separation. However, the summary of MBC synthesis methods is still lack of relevant information. Moreover, the adsorption performance for pollutants by MBC is limited, and thus it is imperative to adopt modification techniques to enhance the removal ability of MBC. Unfortunately, there are few reviews to present modification methods of MBC with applications for removing hazardous contaminants. Herein, we critically reviewed (i) MBC synthetic methods with corresponding advantages and limitations; (ii) adsorption mechanisms of MBC for heavy metals and organic pollutants; (iii) various modification methods for MBC such as functional groups grafting, nanoparticles loading and element doping; (iv) applications of modified MBC for hazardous contaminants adsorption with deep insight to relevant removal mechanisms; and (v) key influencing conditions like solution pH, temperature and interfering ions toward contaminants removal. Finally, some constructive suggestions were put forward for the practical applications of MBC in the near future. This review provided a comprehensive understanding of using functionalized MBC as effective adsorbent with low-cost and high-performance characteristics for contaminated environment remediation.

Zfp57 Exerts Maternal and Sexually Dimorphic Effects on Genomic Imprinting.

Zfp57 has both maternal and zygotic functions in mouse. It maintains genomic imprinting at most known imprinted regions and controls allelic expression of the target imprinted genes in mouse embryos. The DNA methylation imprint at many imprinting control regions (ICRs) is lost when both maternal and zygotic Zfp57 are absent in Zfp57 maternal-zygotic mutant mouse embryos. Interestingly, we found that DNA methylation at a few ICRs was partially lost without maternal Zfp57 in Zfp57 heterozygous mouse embryos derived from Zfp57 homozygous female mice. This suggests that maternal Zfp57 is essential for the maintenance of DNA methylation at a small subset of imprinted regions in mouse embryos. This maternal effect of Zfp57 was applied to allelic expression switch as well as expression levels of the corresponding imprinted genes. It is rather surprising that DNA methylation imprint was affected differently at Rasgrf1 and AK008011 imprinted regions in the female or male Zfp57 maternal-zygotic mutant embryos, with more significant loss of DNA methylation observed in the male mutant embryos. Loss of ZFP57 resulted in gender-specific differences in allelic expression switch and expression level changes of some imprinted genes in female or male mutant embryos. These results indicate maternal and sexually dimorphic effects of ZFP57 on genomic imprinting in mouse.

The Fingerprints of Resonant Frequency for Atomic Vacancy Defect Identification in Graphene.

The identification of atomic vacancy defects in graphene is an important and challenging issue, which involves inhomogeneous spatial randomness and requires high experimental conditions. In this paper, the fingerprints of resonant frequency for atomic vacancy defect identification are provided, based on the database of massive samples. Every possible atomic vacancy defect in the graphene lattice is considered and computed by the finite element model in sequence. Based on the sample database, the histograms of resonant frequency are provided to compare the probability density distributions and interval ranges. Furthermore, the implicit relationship between the locations of the atomic vacancy defects and the resonant frequencies of graphene is established. The fingerprint patterns are depicted by mapping the locations of atomic vacancy defects to the resonant frequency magnitudes. The geometrical characteristics of computed fingerprints are discussed to explore the feasibility of atomic vacancy defects identification. The work in this paper provides meaningful supplementary information for non-destructive defect detection and identification in nanomaterials.

The correlation between graphene characteristic parameters and resonant frequencies by Monte Carlo based stochastic finite element model.

The uncertainty and fluctuations in graphene characteristic parameters are inevitable issues in both of experimental measurements and numerical investigations. In this paper, the correlations between characteristic parameters (Young's modulus, Poisson's ratio and thickness of graphene) and resonant frequencies are analyzed by the Monte Carlo based stochastic finite element model. Based on the Monte Carlo stochastic sampling procedure, the uncertainty in the characteristic parameters are properly propagated and quantified. The displacements and rotation modes of graphene under the resonant vibration computed by the finite element method are verified. Furthermore, the result robustness of stochastic samples is discussed based on the statistic records and probability density distributions. In addition, both the Pearson and Spearman correlation coefficients of the corresponding characteristic parameters are calculated and compared. The work in this paper provides a feasible and highly efficient method for the characteristic parameter correlation discussion by taking uncertainty into consideration.

The Effects of Random Porosities in Resonant Frequencies of Graphene Based on the Monte Carlo Stochastic Finite Element Model.

With the distinguished properties in electronics, thermal conductivity, optical transparence and mechanics, graphene has a powerful potential in nanosensors, nano-resonators, supercapacitors, batteries, etc. The resonant frequency of graphene is an important factor in its application and working environment. However, the random dispersed porosities in graphene evidently change the lattice structure and destroy the integrity and geometrical periodicity. This paper focuses on the effects of random porosities in resonant frequencies of graphene. Monte Carlo simulation is applied to propagate the porosities in the finite element model of pristine graphene. The statistical results and probability density distribution of porous graphene with atomic vacancy defects are computed based on the Monte Carlo finite element model. The results of porous graphene with atomic vacancy defects are compared and discussed with the results of graphene with bond vacancy defects. The enhancement effects of atomic vacancy defects are confirmed in porous graphene. The influences of atomic vacancy defects on displacement and rotation vector sums of porous graphene are more concentrated in local places.