Study on Explosion Characteristics and Mechanism of Electrostatic Spray Powder.

In order to fully understand the explosion risk of electrostatic spraying powder, corresponding preventive measures are put forward. The explosion characteristics, ignition sensitivity, and flame propagation of three typical electrostatic spraying powders were tested using a 20 L spherical explosion test device, a G-G furnace test device, and a Hartmann tube test device, and the explosion process and mechanism of electrostatic spraying powders were discussed. The results show that the maximum explosion pressure and the maximum explosion pressure rise rate increase first and then decrease with the increase in mass concentration. The maximum explosion pressure and the maximum explosion pressure rise rate of acrylic powder coating are the largest, which are 0.75 and 85.4 MPa/s, respectively. The shortest burning time is 97.5 ms, and the highest explosion danger level is 23.46 MPa·m/s. The flame propagation of electrostatic spraying powder develops slowly; the flame front spreads linearly and the average flame velocity increases first and then decreases. The explosive development process of powder coating particles is concentrated in the three-phase system of solid particles, molten particles, and pyrolytic gasification combustible gas, which goes through the kinetic process of particle heating melting, cross-linking curing, pyrolytic gasification, combustion, and extinction.

Quenching residual H2O2 from UV/H2O2 with granular activated carbon: A significant impact of bicarbonate.

UV/H2O2 has been used as an advanced oxidation process to remove organic micropollutants from drinking water. It is essential to quench residual H2O2 to prevent increased chlorine demand during chlorination/chloramination and within distribution systems. Granular activated carbon (GAC) filter can quench the residual oxidant and eliminate some of the dissolved organic matter. However, knowledge on the kinetics and governing factors of GAC quenching of residual H2O2 from UV/H2O2 and the mechanism underlying the enhancement of the process by HCO3- is limited. Therefore, this study aimed to analyse the kinetics and influential factors, particularly the significant impact of bicarbonate (HCO3-). H2O2 decomposition by GAC followed first-order kinetics, and the rate constants normalised by the GAC dosage (kn) were steady (1.6 × 10-3 L g-1 min-1) with variations in the GAC dosage and initial H2O2 concentration. Alkaline conditions favour H2O2 quenching. The content of basic groups exhibited a stronger correlation with the efficiency of GAC in quenching H2O2 than did the acidic groups， with their specific kn values being 8.9 and 2.4 min-1 M-1, respectively. The presence of chloride, sulfate, nitrate, and dissolved organic matter inhibited H2O2 quenching, while HCO3- promoted it. The interfacial hydroxyl radical (HO•) zones were visualised on the GAC surface, and HCO3- addition increased the HO• concentration. HCO3- increased the concentration of persistent free radicals (PFRs) on the GAC surface, which mainly contributed to HO• generation. A significant enhancement of HCO3- on H2O2 quenching by GAC was also verified in real water. This study revealed the synergistic mechanism of HCO3- and GAC on H2O2 quenching and presents the potential applications of residual H2O2 in the H2O2-based oxidation processes.

Corrigendum: The immune factors have complex causal regulation effects on inflammatory bowel disease.

[This corrects the article DOI: 10.3389/fimmu.2023.1322673.].

Cananga oil inhibits Salmonella infection by mediating the homeostasis of purine metabolism and the TCA cycle.

ETHNOPHARMACOLOGY RELEVANCE: Cananga oil (CO) is derived from the flowers of the traditional medicinal plant, the ylang-ylang tree. As a traditional antidepressant, CO is commonly utilized in the treatment of various mental disorders including depression, anxiety, and autism. It is also recognized as an efficient antibacterial insecticide, and has been traditionally utilized to combat malaria and acute inflammatory responses resulting from bacterial infections both in vitro and in vivo. AIM OF THE STUDY: The objective of this study is to comprehensively investigate the anti-Salmonella activity and mechanism of CO both in vitro and in vivo, with the expectation of providing feasible strategies for exploring new antimicrobial strategies and developing novel drugs. METHODS: The in vitro antibacterial activity of CO was comprehensively analyzed by measuring MIC, MBC, growth curve, time-killing curve, surface motility, biofilm, and Live/dead bacterial staining. The analysis of the chemistry and active ingredients of CO was conducted using GC-MS. To examine the influence of CO on the membrane homeostasis of Salmonella, we conducted utilizing diverse techniques, including ANS, PI, NPN, ONPG, BCECF-AM, DiSC3(5), and scanning electron microscopy (SEM) analysis. In addition, the antibacterial mechanism of CO was analyzed and validated through metabolomics analysis. Finally, a mouse infection model of Salmonella typhimurium was established to evaluate the toxic side effects and therapeutic effects of CO. RESULTS: The antibacterial effect of CO is the result of the combined action of the main chemical components within its six (palmitic acid, α-linolenic acid, stearic acid, benzyl benzoate, benzyl acetate, and myristic acid). Furthermore, CO disrupts the balance of purine metabolism and the tricarboxylic acid cycle (TCA cycle) in Salmonella, interfering with redox processes. This leads to energy metabolic disorders and oxidative stress damage within the bacteria, resulting in bacterial shock, enhanced membrane damage, and ultimately bacterial death. It is worth emphasizing that CO exerts an effective protective influence on Salmonella infection in vivo within a non-toxic concentration range. CONCLUSION: The outcomes indicate that CO displays remarkable anti-Salmonella activity both in vitro and in vivo. It triggers bacterial death by disrupting the balance of purine metabolism and the TCA cycle, interfering with the redox process, making it a promising anti-Salmonella medication.

Research on the Inhibition Effect of NaCl on the Explosion of Mg-Al Alloy Powder.

A study was conducted on the explosion overpressure and flame propagation law of magnesium-aluminum (Mg-Al) alloy powder, and the suppression mechanism of sodium chloride (NaCl) on the explosion of magnesium-aluminum alloy powder was explored. Adding NaCl powder can effectively reduce the explosion pressure, flame front position, and flame propagation speed. The higher the amount of NaCl powder added, the lower the explosion pressure of magnesium-aluminum alloy powder, the slower the flame propagation speed, and the lower the flame brightness. NaCl adsorbed on Mg-Al alloy powder isolated heat transfer and played a cooling role. The Cl- produced by NaCl decomposition will react with the free radicals H+ and OH- in the reaction system, which will reduce the concentration of H+ and OH- in the combustion process and hinder the propagation and expansion of the flame. The research results provide theoretical guidance for the explosion prevention of Mg-Al alloy powder and the preparation of a physical-chemical compound explosion suppressor in the later stage.

Comparative transcriptome profile analysis of granulosa cells from porcine ovarian follicles during early atresia.

At various stages of ovarian follicular development, more than 99% of follicles will be eliminated through a degenerative process called atresia. The regulatory mechanisms of atresia have been elucidated to some extent, involving hormones, growth factors, cytokines, and other factors. However, the stimuli initiating atresia in follicular granulosa cells remain unknown. In this study, we isolated the granulosa cells from porcine ovarian follicles (3-5 mm diameter) divided into healthy follicles (HFs) and early atretic follicles (EAFs). We applied high-throughput RNA sequencing to identify and compare differentially expressed genes (DEGs) between HFs and EAFs. A total of 31,694 genes were detected, of which 21,806 were co-expressed in six samples, and 243 genes (p < 0.05; FDR < 0.05) were differentially expressed (DEGs), including 123 downregulated and 120 upregulated in EAFs. GO analysis highlighted hormone metabolism, plasma membrane localization, and transporter activity. The pathway analysis indicated that 51 DEGs, involved in steroidogenesis, cell adhesion molecules, and TGF-beta signaling pathways, were highly related to atresia. Additionally, the interaction network of DEGs (p < 0.01; FDR < 0.05) using STRING highlighted LHR, ACACB, and CXCR4 as central nodes. In summary, this transcriptome analysis enriched our knowledge of the shifted mechanisms in granulosa cells during early atresia and provided novel perspectives into the atresia initiation.

Designing a Hybrid Chain Reaction Probe for Multiplex Transcripts Assay with High-Level Imaging.

The hybrid chain reaction (HCR), an isothermal and enzyme-free amplification strategy, has found extensive use in fluorescent in situ hybridization (FISH) assays. However, the existing HCRs are limited, being time-consuming processes and low-efficiency imaging due to weak signal, significantly restricting their application in transcriptomic assays. To address the limitations, we developed nine orthogonal HCR hairpin-pair (hp) probes in this study to enable efficient signal amplification for multiplex assays. To enhance the efficiency and imaging quality of multiplex assays using these HCR probes, we employed two strategies. First, we coupled fluorescent molecules to HCR hairpins via disulfide bonds, facilitating easy removal through chemical cleavage. As a result, the workflow was greatly simplified. Second, we combined HCR with in situ rolling circle amplification (ISRCA), creating ISRCA-HCR, which achieved a 17-fold signal amplification. ISRCA-HCR demonstrated a high-level imaging capability for spatial cell type assays. This study shows the application for cell typing based on the developed HCR probes, enabling accurate and high-level signal amplification for multiplex FISH imaging. This provides an effective research tool for transcriptome and spatial cell type analysis.

Gut microbiota and common gastrointestinal diseases: a bidirectional two-sample Mendelian randomized study.

Background: Several recent studies have shown an association between gut microbiota and gastrointestinal diseases. However, the causal relationship between gut microbiota and gastrointestinal disorders is unclear. Methods: We assessed causal relationships between gut microbiota and eight common gastrointestinal diseases using Mendelian randomization (MR) analyses. IVW results were considered primary results. Cochrane's Q and MR-Egger tests were used to test for heterogeneity and pleiotropy. Leave-one-out was used to test the stability of the MR results, and Bonferroni correction was used to test the strength of the causal relationship between exposure and outcome. Results: MR analyses of 196 gut microbiota and eight common gastrointestinal disease phenotypes showed 62 flora and common gastrointestinal diseases with potential causal relationships. Among these potential causal relationships, after the Bonferroni-corrected test, significant causal relationships remained between Genus Oxalobacter and CD (OR = 1.29, 95% CI: 1.13-1.48, p = 2.5 × 10-4, q = 4.20 × 10-4), and between Family Clostridiaceae1 and IBS (OR = 0.9967, 95% CI: 0.9944-0.9991, p = 1.3 × 10-3, q = 1.56 × 10-3). Cochrane's Q-test showed no significant heterogeneity among the various single nucleotide polymorphisms (SNPs). In addition, no significant level of pleiotropy was found according to the MR-Egger. Conclusion: This study provides new insights into the mechanisms of gut microbiota-mediated gastrointestinal disorders and some guidance for targeting specific gut microbiota for treating gastrointestinal disorders.

Ethanol-diluted turbidimetry method for rapid and accurate quantification of low-density microplastics in synthetic samples.

Retention and transport behaviours of microplastics (MPs) and their associated pollutants in porous media are of great concern. The homogeneity of the studied MPs in artificially controlled lab-scale studies makes rapid and accurate MP quantification feasible. In this study, an economical ethanol-diluted turbidimetry method for polypropylene (PP) and polyethylene (PE) MPs was developed. With ethanol dilution, the MP dispersion system exhibited an excellent suspension performance. Strong linear relationships were observed between MP concentrations and turbidities in both low (<1.3 mg L-1) and high (<170 mg L-1) MP concentration ranges. Solution density and MP agglomeration governed the MP suspension performance. For low surface tension and high molecular mass, the addition of ethanol decreased the contact angles of PP-MPs with solutions from 81.73 to 15.5°, and consequently improved the MP suspension performance. The suspension system was optimised to an ethanol/water (v/v) ratio of 3:2 and 4:1 for PP- and PE-MPs, when the slopes of standard curves were determined to be 1.252 and 0.471 with the recovery of 100.54 ± 3.09% and 103.19 ± 1.66%, and the limit of detection and quantification values of 0.025 and 0.082 mg L-1, and 0.060 and 0.201 mg L-1, respectively. Solution pH, salinity, and dissolved organic matter in the selected range induced acceptable fluctuations in the MP recovery and matrix effect values. The Derjaguin-Landau-Verwey-Overbeek (DLVO) energy barriers were calculated to be > 20 kT, indicating excellent tolerance to the solution matrix. Additionally, applications in real water samples were validated to demonstrate the potential of the developed method.

A machine learning-based model for predicting distant metastasis in patients with rectal cancer.

Background: Distant metastasis from rectal cancer usually results in poorer survival and quality of life, so early identification of patients at high risk of distant metastasis from rectal cancer is essential. Method: The study used eight machine-learning algorithms to construct a machine-learning model for the risk of distant metastasis from rectal cancer. We developed the models using 23867 patients with rectal cancer from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2017. Meanwhile, 1178 rectal cancer patients from Chinese hospitals were selected to validate the model performance and extrapolation. We tuned the hyperparameters by random search and tenfold cross-validation to construct the machine-learning models. We evaluated the models using the area under the receiver operating characteristic curves (AUC), the area under the precision-recall curve (AUPRC), decision curve analysis, calibration curves, and the precision and accuracy of the internal test set and external validation cohorts. In addition, Shapley's Additive explanations (SHAP) were used to interpret the machine-learning models. Finally, the best model was applied to develop a web calculator for predicting the risk of distant metastasis in rectal cancer. Result: The study included 23,867 rectal cancer patients and 2,840 patients with distant metastasis. Multiple logistic regression analysis showed that age, differentiation grade, T-stage, N-stage, preoperative carcinoembryonic antigen (CEA), tumor deposits, perineural invasion, tumor size, radiation, and chemotherapy were-independent risk factors for distant metastasis in rectal cancer. The mean AUC value of the extreme gradient boosting (XGB) model in ten-fold cross-validation in the training set was 0.859. The XGB model performed best in the internal test set and external validation set. The XGB model in the internal test set had an AUC was 0.855, AUPRC was 0.510, accuracy was 0.900, and precision was 0.880. The metric AUC for the external validation set of the XGB model was 0.814, AUPRC was 0.609, accuracy was 0.800, and precision was 0.810. Finally, we constructed a web calculator using the XGB model for distant metastasis of rectal cancer. Conclusion: The study developed and validated an XGB model based on clinicopathological information for predicting the risk of distant metastasis in patients with rectal cancer, which may help physicians make clinical decisions. rectal cancer, distant metastasis, web calculator, machine learning algorithm, external validation.

The immune factors have complex causal regulation effects on inflammatory bowel disease.

Background: Although a correlation between immune cell phenotypes and inflammatory bowel disease (IBD) has been established, a causal relationship remains unestablished. Methods: To assess causal associations between immune cell phenotypes and IBD and its subtypes, we employed Mendelian randomization (MR) methods and genome-wide association studies (GWAS) summary statistics. The primary outcomes were determined based on the inverse variance weighting (IVW) results, with the assessment of heterogeneity and pleiotropy conducted through Cochrane's Q-test and MR-Egger. The stability of the MR results was then examined using leave-one-out analysis, and false discovery rate (FDR) correction was applied to evaluate the strength of the causal relationship between exposure and outcome. Furthermore, to identify immunophenotypes strongly associated with IBD, a meta-integration of the effect values of all positive results in both datasets was conducted. Results: The analysis of 731 immune cell phenotypes and IBD using MR techniques revealed potential causal associations between 26 phenotypes and IBD. Subsequent meta-integration of the two datasets provided evidence of solid causal associations between 18 immune phenotypes and IBD and its subtypes. Nominal causal associations were also identified in the remaining eight immune phenotypes and IBD and its subtypes. Conclusion: Our study confirms causal solid associations between 18 immune phenotypes and IBD, thus guiding future clinical studies.

Effective Quality Breeding Directions-Comparison and Conservative Analysis of Hepatic Super-Enhancers between Chinese and Western Pig Breeds.

The transcriptional initiation of genes is closely bound to the functions of cis-regulatory elements, including promoters, typical enhancers (TEs), and recently-identified super-enhancers (SEs). In this study, we identified these cis-regulatory elements in the livers of two Chinese (Meishan and Enshi Black) and two Western (Duroc and Large White) pig breeds using ChIP-seq data, then explored their similarities and differences. In addition, we analyzed the conservation of SEs among different tissues and species (pig, human, and mouse). We observed that SEs were more significantly enriched by transcriptional initiation regions, TF binding sites, and SNPs than other cis-elements. Western breeds included fewer SEs in number, while more growth-related QTLs were associated with these SEs. Additionally, the SEs were highly tissue-specific, and were conserved in the liver among humans, pigs, and mice. We concluded that intense selection could concentrate functional SEs; thus, SEs could be applied as effective detection regions in genomic selection breeding.

Application of machine learning techniques in real-world research to predict the risk of liver metastasis in rectal cancer.

Background: The liver is the most common site of distant metastasis in rectal cancer, and liver metastasis dramatically affects the treatment strategy of patients. This study aimed to develop and validate a clinical prediction model based on machine learning algorithms to predict the risk of liver metastasis in patients with rectal cancer. Methods: We integrated two rectal cancer cohorts from Surveillance, Epidemiology, and End Results (SEER) and Chinese multicenter hospitals from 2010-2017. We also built and validated liver metastasis prediction models for rectal cancer using six machine learning algorithms, including random forest (RF), light gradient boosting (LGBM), extreme gradient boosting (XGB), multilayer perceptron (MLP), logistic regression (LR), and K-nearest neighbor (KNN). The models were evaluated by combining several metrics, such as the area under the curve (AUC), accuracy score, sensitivity, specificity and F1 score. Finally, we created a network calculator using the best model. Results: The study cohort consisted of 19,958 patients from the SEER database and 924 patients from two hospitals in China. The AUC values of the six prediction models ranged from 0.70 to 0.95. The XGB model showed the best predictive power, with the following metrics assessed in the internal test set: AUC (0.918), accuracy (0.884), sensitivity (0.721), and specificity (0.787). The XGB model was assessed in the outer test set with the following metrics: AUC (0.926), accuracy (0.919), sensitivity (0.740), and specificity (0.765). The XGB algorithm also shows a good fit on the calibration decision curves for both the internal test set and the external validation set. Finally, we constructed an online web calculator using the XGB model to help generalize the model and to assist physicians in their decision-making better. Conclusion: We successfully developed an XGB-based machine learning model to predict liver metastasis from rectal cancer, which was also validated with a real-world dataset. Finally, we developed a web-based predictor to guide clinical diagnosis and treatment strategies better.

Computational fluid dynamics modelling of quasi-collimated beam apparatus - a typical bench scale UV apparatus for water treatment.

Quasi-collimated beam apparatus (QCBA), a typical bench scale UV apparatus, is crucial for the biodosimetry determination of UV dose in target reactors. However, the key parameters for the QCBA construction are usually estimated via rule-of-thumb calculations. Computational fluid dynamics models are applied in this study to simulate the UV fluence rate (FR) distributions in QCBAs. QCBAs with either a cylindrical tube or successive apertures irradiate quasi parallel light into selected dishes. The simulated Petri factors (PF) in the target QCBAs with a single aperture were all >0.84, and increased with the extended distance (L1) from the UV lamp to the upper aperture. QCBAs with two successive apertures are recommended compared with those with three apertures or cylindrical tube. A trend of FR distribution from dispersed to concentrated is observed when L1 or the interval distance between each aperture increases in a dual-aperture QCBA. QCBAs with multiple lamps were favorable to increase the UV output power, while having a nearly negligible loss of parallelism. An actual QCBA was constructed, and the maximal and average FR and PF values in a 60-mm dish were 0.159 and 0.164 W/m2, and 0.967, respectively, in accordance with the simulated results.

Effect of low-intensity ultrasound on partial nitrification: Performance, sludge characteristics, and properties of extracellular polymeric substances.

Ultrasound technology, which is environment-friendly and economical, has emerged as a novel strategy that can be used to enhance the partial nitrification process. However, its effect on this process remains unclear. Therefore, in this study, partial nitrification sludge was subjected to low-intensity (0.15 W/mL) ultrasound treatment for 10 min, and the effect of ultrasonic treatment on the partial nitrification process was evaluated based on changes in reactor performance, sludge characteristics, and the properties of extracellular polymeric substances (EPS). The results obtained showed that the ultrasonic treatment enhanced nitrite accumulation performance as well as the activity of ammonia-oxidizing bacteria from 3.3 to 16.6 mg O2/g VSS,⋅while inhibiting the activity of nitrite-oxidizing bacteria. Further analysis showed that owing to the ultrasonic treatment, there was an increase in EPS contents. Particularly, there was a significant increase in loosely bound polysaccharide (PS) contents, indicating the occurrence of intracellular PS anabolics as well as PS secretion. Additionally, ultrasonic treatment induced a significant increase in carbonyl, hydroxyl, and amine functional group contents, and EPS analysis results revealed that it had a positive effect on mass transfer efficiency; thus, it enhanced the partial nitrification process. Overall, this study describes the effect of intermittent low-intensity ultrasound on the partial nitrification process as well as the associated enhancement mechanism.

Enhanced fluorescence and heat dissipation of calcium titanate red phosphor based on silver coating.

Phosphor plays an important role in LEDs-the next generation of lighting source. However, many families of phosphor like titanate still face two severe problems: Low photoluminescence (PL) efficiency and poor thermal stability. Herein, the silver coating is applied to alleviate the above challenges. Ag nanoparticles with different morphology like disks or triangular plates are synthesised by a simple sol-reduction method, and then coated on the shape-regular CaTiO3:Eu (CTOE) phosphor. When the localized surface plasmon resonance (LSPR) extinction spectrum of Ag nanoparticles matches well with excitation or emission wavelength, the PL intensity of CTOE phosphor would be efficiently enhanced. There is an optimum point of LSPR coating amount due to the balance of LSPR-enhancement and scattering/reflection-reduction of Ag nanoparticles. The coating of Ag also leads to an improvement in heat dissipation of CTOE phosphors; meanwhile an overmuch of Ag would also reduce the luminous efficiency. Thus the most suitable coating amount based on the overall consideration successfully enables the enhancement of both PL intensity and heat dissipation, and the pc-LED lamp packaged with Ag coated CTOE phosphor also shows a higher efficiency and more stable working status than the uncoated ones.