Reliable assessment and prediction of moderate preoxidation of sodium hypochlorite for algae-laden water treatment.

Chemical moderate preoxidation for algae-laden water is an economical and prospective strategy for controlling algae and exogenous pollutants, whereas it is constrained by a lack of effective on-line evaluation and quick-response feedback method. Herein, excitation-emission matrix parallel factor analysis (EEM-PARAFAC) was used to identify cyanobacteria fluorophores after preoxidation of sodium hypochlorite (NaClO) at Excitation/Emission wavelength of 260(360)/450 nm, based on which the algal cell integrity and intracellular organic matter (IOM) release were quantitatively assessed. Machine learning modeling of fluorescence spectral data for prediction of moderate preoxidation using NaClO was established. The optimal NaClO dosage for moderate preoxidation depended on algal density, growth phases, and organic matter concentrations in source water matrices. Low doses of NaClO (<0.5 mg/L) led to short-term desorption of surface-adsorbed organic matter (S-AOM) without compromising algal cell integrity, whereas high doses of NaClO (≥0.5 mg/L) quickly caused cell damage. The optimal NaClO dosage increased from 0.2-0.3 mg/L to 0.9-1.2 mg/L, corresponding to the source water with algal densities from 0.1 × 106 to 2.0 × 106 cells/mL. Different growth stages required varying NaClO doses: stationary phase cells needed 0.3-0.5 mg/L, log phase cells 0.6-0.8 mg/L, and decaying cells 2.0-2.5 mg/L. The presence of natural organic matter and S-AOM increased the NaClO dosage limit with higher dissolved organic carbon (DOC) concentrations (1.00 mg/L DOC required 0.8-1.0 mg/L NaClO, while 2.20 mg/L DOC required 1.5-2.0 mg/L). Compared to other predictive models, the machine learning model (Gaussian process regression-Matern (0.5)) performed best, achieving R2 values of 1.000 and 0.976 in training and testing sets. Optimal preoxidation followed by coagulation effectively removed algal contaminants, achieving 91%, 92%, and 92% removal for algal cells, turbidity, and chlorophyll-a, respectively, thereby demonstrating the effectiveness of moderate preoxidation. This study introduces a novel approach to dynamically adjust NaClO dosage by monitoring source water qualities and tracking post-preoxidation fluorophores, enhancing moderate preoxidation technology application in algae-laden water treatment.

Exploring the prognostic value of BRMS1 + microglia based on single-cell anoikis regulator patterns in the immunologic microenvironment of GBM.

BACKGROUND: Anoikis is a specialized form of programmed cell death induced by the loss of cell adhesion to the extracellular matrix (ECM). Acquisition of anoikis resistance is a significant marker for cancer cell invasion, metastasis, therapy resistance, and recurrence. Although current research has identified multiple factors that regulate anoikis resistance, the pathological mechanisms of anoikis-mediated tumor microenvironment (TME) in glioblastoma (GBM) remain largely unexplored. METHODS: Utilizing single-cell RNA sequencing (scRNA-seq) data and employing non-negative matrix factorization (NMF), we identified and characterized TME cell clusters with distinct anoikis-associated gene signatures. Prognostic and therapeutic response analyses were conducted using TCGA and CGGA datasets to assess the clinical significance of different TME cell clusters. The spatial relationship between BRMS1 + microglia and tumor cells was inferred from spatial transcriptome RNA sequencing (stRNA-seq) data. To simulate the tumor immune microenvironment, co-culture experiments were performed with microglia (HMC3) and GBM cells (U118/U251), and microglia were transfected with a BRMS1 overexpression lentivirus. Western blot or ELISA were used to detect BRMS1, M2 macrophage-specific markers, PI3K/AKT signaling proteins, and apoptosis-related proteins. The proliferation and apoptosis capabilities of tumor cells were evaluated using CCK-8, colony formation, and apoptosis assays, while the invasive and migratory abilities of tumor cells were assessed using Transwell assays. RESULTS: NMF-based analysis successfully identified CD8 + T cell and microglia cell clusters with distinct gene signature characteristics. Trajectory analysis, cell communication, and gene regulatory network analyses collectively indicated that anoikis-mediated TME cell clusters can influence tumor cell development through various mechanisms. Notably, BRMS1 + AP-Mic exhibited an M2 macrophage phenotype and had significant cell communication with malignant cells. Moreover, high expression of BRMS1 + AP-Mic in TCGA and CGGA datasets was associated with poorer survival outcomes, indicating its detrimental impact on immunotherapy. Upregulation of BRMS1 in microglia may lead to M2 macrophage polarization, activate the PI3K/AKT signaling pathway through SPP1/CD44-mediated cell interactions, inhibit tumor cell apoptosis, and promote tumor proliferation and invasion. CONCLUSION: This pioneering study used NMF-based analysis to reveal the important predictive value of anoikis-regulated TME in GBM for prognosis and immunotherapeutic response. BRMS1 + microglial cells provide a new perspective for a deeper understanding of the immunosuppressive microenvironment of GBM and could serve as a potential therapeutic target in the future.

The nociceptive inputs of the paraventricular hypothalamic nucleus in formalin stimulated mice.

The paraventricular hypothalamic nucleus (PVH) is an important neuroendocrine center involved in pain regulation, but the nociceptive afferent routes for the nucleus are still unclear. We examined the profile of PVH receiving injurious information by a combination of retrograde tracing with Fluoro-Gold (FG) and FOS expression induced by formalin stimuli. The result showed that formalin injection induced significantly increased expression of FOS in the PVH, among which oxytocin containing neurons are one neuronal phenotype. Immunofluorescent staining of FG and FOS revealed that double labeled neurons were strikingly distributed in the area 2 of the cingulate cortex (Cg2), the lateral septal nucleus (LS), the periaqueductal gray (PAG), the posterior hypothalamic area (PH), and the lateral parabrachial nucleus (LPB). In the five regions, LPB had the biggest number and the highest ratio of FOS expression in FG labeled neurons, with main subnuclei distribution in the external, superior, dorsal, and central parts. Further immunofluorescent triple staining disclosed that about one third of FG and FOS double labeled neurons in the LPB were immunoreactive for calcitonin gene related peptide (CGRP). In conclusion, the present study demonstrates the nociceptive input profile of the PVH area under inflammatory pain and suggests that neurons in the LPB may play essential roles in transmitting noxious information to the PVH.

A novel ARHGAP family gene signature for survival prediction in glioma patients.

ARHGAP family genes are often used as glioma oncogenic factors, and their mechanism of action remains unexplained. Our research entailed a thorough examination of the immune microenvironment and enrichment pathways across various glioma subtypes. A distinctive 6-gene signature was developed employing the CGGA cohort, leading to insights into the disparities in clinical characteristics, mutation patterns, and immune cell infiltration among distinct risk categories. Additionally, a unique nomogram was established, grounded on ARHGAPs, with DCA curves illustrating the model's prospective clinical utility in guiding therapeutic strategies. Emphasizing the role of ARHGAP30, integral to our model, its impact on glioma severity and the credibility of our risk assessment model were substantiated through RT-qPCR, Western blot analysis, and cellular functional assays. We identified 6 ARHGAP family genes associated with glioma prognosis. Analysis using the Kaplan-Meier method indicated a correlation between elevated risk levels and adverse outcomes in glioma patients. The risk score, linked with tumour staging and IDH mutation status, emerged as an independent factor predicting prognosis. Patients in the high-risk category exhibited increased immune cell infiltration, enhanced tumour mutational burden, more pronounced expression of immune checkpoint genes, and a better response to ICB therapy. A nomogram, integrating the risk score with the pathological features of glioma patients, was developed. DCA analysis and cellular studies confirmed the model's potential to improve clinical treatment outcomes for patients. A novel ARHGAP family gene signature reveals the prognosis of glioma.

Microecology of aerobic denitrification system construction driven by cyclic stress of sulfamethoxazole.

The construction of aerobic denitrification (AD) systems in an antibiotic-stressed environment is a serious challenge. This study investigated strategy of cyclic stress with concentration gradient (5-30 mg/L) of sulfamethoxazole (SMX) in a sequencing batch reactor (SBR), to achieve operation of AD. Total nitrogen removal efficiency of system increased from about 10 % to 95 %. Original response of abundant-rare genera to antibiotics was changed by SMX stress, particularly conditionally rare or abundant taxa (CRAT). AD process depends on synergistic effect of heterotrophic nitrifying aerobic denitrification bacteria (Paracoccus, Thauera, Hypomicrobium, etc). AmoABC, napA, and nirK were functionally co-expressed with multiple antibiotic resistance genes (ARGs) (acrR, ereAB, and mdtO), facilitating AD process. ARGs and TCA cycling synergistically enhance the antioxidant and electron transport capacities of AD process. Antibiotic efflux pump mechanism played an important role in operation of AD. The study provides strong support for regulating activated sludge to achieve in situ AD function.

Targeting nucleotide metabolic pathways in colorectal cancer by integrating scRNA-seq, spatial transcriptome, and bulk RNA-seq data.

BACKGROUND: Colorectal cancer is a malignant tumor of the digestive system originating from abnormal cell proliferation in the colon or rectum, often leading to gastrointestinal symptoms and severe health issues. Nucleotide metabolism, which encompasses the synthesis of DNA and RNA, is a pivotal cellular biochemical process that significantly impacts both the progression and therapeutic strategies of colorectal cancer METHODS: For single-cell RNA sequencing (scRNA-seq), five functions were employed to calculate scores related to nucleotide metabolism. Cell developmental trajectory analysis and intercellular interaction analysis were utilized to explore the metabolic characteristics and communication patterns of different epithelial cells. These findings were further validated using spatial transcriptome RNA sequencing (stRNA-seq). A risk model was constructed using expression profile data from TCGA and GEO cohorts to optimize clinical decision-making. Key nucleotide metabolism-related genes (NMRGs) were functionally validated by further in vitro experiments. RESULTS: In both scRNA-seq and stRNA-seq, colorectal cancer (CRC) exhibited unique cellular heterogeneity, with myeloid cells and epithelial cells in tumor samples displaying higher nucleotide metabolism scores. Analysis of intercellular communication revealed enhanced signaling pathways and ligand-receptor interactions between epithelial cells with high nucleotide metabolism and fibroblasts. Spatial transcriptome sequencing confirmed elevated nucleotide metabolism states in the core region of tumor tissue. After identifying differentially expressed NMRGs in epithelial cells, a risk prognostic model based on four genes effectively predicted overall survival and immunotherapy outcomes in patients. High-risk group patients exhibited an immunosuppressive microenvironment and relatively poorer prognosis and responses to chemotherapy and immunotherapy. Finally, based on data analysis and a series of cellular functional experiments, ACOX1 and CPT2 were identified as novel therapeutic targets for CRC. CONCLUSION: In this study, a comprehensive analysis of NMRGs in CRC was conducted using a combination of single-cell sequencing, spatial transcriptome sequencing, and high-throughput data. The prognostic model constructed with NMRGs shows potential as a standalone prognostic marker for colorectal cancer patients and may significantly influence the development of personalized treatment approaches for CRC.

Genome-Wide Association Study Uncovers Genomic Regions Associated with Coleoptile Length in a Worldwide Collection of Oat.

The length of coleoptile is crucial for determining the sowing depth of oats in low-precipitation regions, which is significant for oat breeding programs. In this study, a diverse panel of 243 oat accessions was used to explore coleoptile length in two independent experiments. The panel exhibited significant variation in coleoptile length, ranging from 4.66 to 8.76 cm. Accessions from Africa, America, and the Mediterranean region displayed longer coleoptile lengths than those from Asia and Europe. Genome-wide association studies (GWASs) using 26,196 SNPs identified 34 SNPs, representing 32 quantitative trait loci (QTLs) significantly associated with coleoptile length. Among these QTLs, six were consistently detected in both experiments, explaining 6.43% to 10.07% of the phenotypic variation. The favorable alleles at these stable loci additively increased coleoptile length, offering insights for pyramid breeding. Gene Ontology (GO) analysis of the 350 candidate genes underlying the six stable QTLs revealed significant enrichment in cell development-related processes. Several phytochrome-related genes, including auxin transporter-like protein 1 and cytochrome P450 proteins, were found within these QTLs. Further validation of these loci will enhance our understanding of coleoptile length regulation. This study provides new insights into the genetic architecture of coleoptile length in oats.

Application value of intraoperative electrophysiological monitoring in cerebral eloquent area glioma surgery: a retrospective cohort study.

INTRODUCTION: Surgery for gliomas involving eloquent areas is a very challenging microsurgical procedure. Maximizing both the extent of resection (EOR) and preservation of neurological function have always been the focus of attention. Intraoperative neurophysiological monitoring (IONM) is widely used in this kind of surgery. The purpose of this study was to evaluate the efficacy of IONM in eloquent area glioma surgery. METHODS: Sixty-eight glioma patients who underwent surgical treatment from 2014 to 2019 were included in this retrospective cohort study, which focused on eloquent areas. Clinical indicators and IONM data were analysed preoperatively, two weeks after surgery, and at the final follow-up. Logistic regression, Cox regression, and Kaplan‒Meier analyses were performed, and nomograms were then established for predicting prognosis. The diagnostic value of the IONM indicator was evaluated by the receiver operating characteristic (ROC) curve. RESULTS: IONM had no effect on the postoperative outcomes, including EOR, intraoperative bleeding volume, duration of surgery, length of hospital stay, and neurological function status. However, at the three-month follow-up, the percentage of patients who had deteriorated function in the monitored group was significantly lower than that in the unmonitored group (23.3% vs. 52.6%; P < 0.05). Logistic regression analysis showed that IONM was a significant factor in long-term neurological function (OR = 0.23, 95% CI (0.07-0.70). In the survival analysis, long-term neurological deterioration indicated worsened overall survival (OS) and progression-free survival (PFS). A prognostic nomogram was established through Cox regression model analysis, which could predict the probability 3-year survival rate. The concordance index was 0.761 (95% CI 0.734-0.788). The sensitivity and specificity of IONM evoked potential (SSEP and TCeMEP) were 0.875 and 0.909, respectively. In the ROC curve analysis, the area under the curve (AUC) for the SSEP and TCeMEP curves was 0.892 (P < 0.05). CONCLUSIONS: The application of IONM could improve long-term neurological function, which is closely related to prognosis and can be used as an independent prognostic factor. IONM is practical and widely available for predicting postoperative functional deficits in patients with eloquent area glioma.

Exploring the causal relationship between antihypertensive drugs and glioblastoma by combining drug target Mendelian randomization study, eQTL colocalization, and single-cell RNA sequencing.

Recent reports indicate a potential oncogenic role of antihypertensive drugs in common cancers. However, it remains uncertain whether this phenomenon influences the risk of glioblastoma multiforme (GBM). This study aimed to assess the potential causal effects of blood pressure (BP) and antihypertensive drugs on GBM. Genome-wide association study (GWAS) summary statistics for systolic blood pressure (SBP), diastolic blood pressure (DBP), and GBM in Europeans were downloaded. To represent the effects of antihypertensive drugs, we utilized single nucleotide polymorphisms (SNPs) associated with SBP/DBP adjacent to the coding regions of different antihypertensive drugs as instrumental variables to model five antihypertensive drugs, including angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, calcium channel blockers, ß-receptor blockers (BBs), and thiazide diuretics. Positive control studies were performed using GWAS data in chronic heart failure. The primary method for causality estimation was the inverse-variance-weighted method. Mendelian randomization analysis showed that BBs with the ß1-adrenergic receptor (ADRB1) as a therapeutic target could significantly reduce the risk of GBM by mediating DBP (OR = 0.431, 95% CI: 0.267-0.697, p < .001) and that they could also significantly reduce the risk of GBM by mediating SBP (OR = 0.595, 95% CI: 0.422-0.837, p = .003). Sensitivity analysis and colocalization analysis reinforced the robustness of these findings. Finally, the low expression of the ADRB1 gene in malignant gliomas was found by GBM data from TCGA and single-cell RNA sequencing, which most likely contributed to the poor prognosis of GBM patients. In summary, our study provides preliminary evidence of some causal relationship between ADRB1-targeted BBs and glioblastoma development. However, more studies are needed to validate these findings and further reveal the complex relationship between BP and GBM.

Parasitic Reflection Eliminating for Planar Elements Based on Multi-Frequency Phase-Shifting in Phase Measuring Deflectometry.

Phase measuring deflectometry (PMD) stands as an extremely important technique for specular surface measurement. However, the parasitic reflection from the rear surface poses a challenge for PMD. To solve this problem, this paper proposes an effective method based on multi-frequency and phase-shifting to search for the correct phase. Firstly, the relationship between the phase error and fringe frequency is adequately investigated. Subsequently, an auxiliary function is established to find the special frequency at which the phase error is zero theoretically and the unwrapped phase is the phase of the top surface exactly. Then, the shape of the top surface can be reconstructed correctly. A standard plane element with a thickness of 40 mm and a flat glass with 19 mm were measured. The experimental results verify the feasibility of the proposed method. Considering the result of the interferometer as a reference, the RMSE of the error map is up to 20 nm for the standard plane element. The experimental results demonstrate that the proposed method can successfully untangle the superposed reflections and reliably reconstruct the top surface of the object under test.

Removal of typical pollutant ciprofloxacin using iron-nitrogen co-doped modified corncob in the presence of hydrogen peroxide.

Iron-nitrogen co-doped modified corncob (Fe-N-BC) was synthesized using a hydrothermal and calcination method. The material shows excellent oxidation performance and environmental friendliness. When the dosage of Fe-N-BC was 0.6 g L-1, the concentration of H2O2 was 12 mM and pH was 4, ciprofloxacin (CIP) was virtually totally eliminated in 240 min under Fe-N-BC/H2O2 conditions. The TOC removal efficiency was 54.6%, and the effects of various reaction parameters on the catalytic activity of Fe-N-BC were thoroughly assessed. Through electron paramagnetic resonance (EPR) analyses and free radical quenching experiments, it was established that the reactive oxygen species (˙OH, ˙O2-, 1O2) were crucial in the elimination of CIP. Furthermore, the degradation of CIP was accelerated by the synergistic interaction between the transition metal and PFRs. A thorough evaluation was conducted to assess the respective contributions of adsorption and catalytic oxidation in the system. The degradation mechanism of CIP was proposed under Fe-N-BC/H2O2 conditions. Meanwhile, the possible degradation intermediates and pathways were proposed, and the toxicity of the degradation products of CIP was also meticulously investigated in the study. These findings offered the elimination of CIP in water a theoretical foundation and technical support.

Interaction, immune infiltration characteristics and prognostic modeling of efferocytosis-related subtypes in glioblastoma.

BACKGROUND: Efferocytosis is a biological process in which phagocytes remove apoptotic cells and vesicles from tissues. This process is initiated by the release of inflammatory mediators from apoptotic cells and plays a crucial role in resolving inflammation. The signals associated with efferocytosis have been found to regulate the inflammatory response and the tumor microenvironment (TME), which promotes the immune escape of tumor cells. However, the role of efferocytosis in glioblastoma multiforme (GBM) is not well understood and requires further investigation. METHODS: In this study, we conducted a comprehensive analysis of 22 efferocytosis-related genes (ERGs) by searching for studies related to efferocytosis. Using bulk RNA-Seq and single-cell sequencing data, we analyzed the expression and mutational characteristics of these ERGs. By using an unsupervised clustering algorithm, we obtained ERG clusters from 549 GBM patients and evaluated the immune infiltration characteristics of each cluster. We then identified differential genes (DEGs) in the two ERG clusters and classified GBM patients into different gene clusters using univariate cox analysis and unsupervised clustering algorithms. Finally, we utilized the Boruta algorithm to screen for prognostic genes and reduce dimensionality, and the PCA algorithm was applied to create a novel efferocytosis-related scoring system. RESULTS: Differential expression of ERGs in glioma cell lines and normal cells was analyzed by rt-PCR. Cell function experiments, on the other hand, validated TIMD4 as a tumor risk factor in GBM. We found that different ERG clusters and gene clusters have distinct prognostic and immune infiltration profiles. The ERG signature we developed provides insight into the tumor microenvironment of GBM. Patients with lower ERG scores have a better survival rate and a higher likelihood of benefiting from immunotherapy. CONCLUSIONS: Our novel efferocytosis-related signature has the potential to be used in clinical practice for risk stratification of GBM patients and for selecting individuals who are likely to respond to immunotherapy. This can help clinicians design appropriate targeted therapies before initiating clinical treatment.

Model-independent nonlinearity rectification algorithm using a phase-probability-equalization-based look-up table.

In the fringe projection system, nonlinearities often result in severe artifacts, such as the gamma effect and the phase-shifting error. Most previous methods can only eliminate the nonlinearity of a particular model. Additionally, the problems of coupling nonlinearities are difficult to solve. Therefore, this paper proposes a model-independent nonlinear rectification algorithm. By applying phase probability equalization (PPE) on several complete periods of a flat area, we built a look-up table (LUT) between the phase error and the wrapped phase, and retrieved an accurate phase with the subtraction of a searched phase error. The simulation and experimental results show that, compared with the traditional full-field PPE algorithm, the proposed algorithm is more robust to the object height distributions and has better rectification on incomplete fringe periods. Besides, the proposed algorithm also has higher efficiency because of the characteristics of local processing and noniterative characteristics.

Core Microbiota in the Rhizosphere of Heavy Metal Accumulators and Its Contribution to Plant Performance.

Persistent microbial symbioses can confer greater fitness to their host under unfavorable conditions, but manipulating such beneficial interactions necessitates a mechanistic understanding of the consistently important microbiomes for the plant. Here, we examined the phylogenetic profiles and plant-beneficial traits of the core microbiota that consistently inhabits the rhizosphere of four divergent Cd hyperaccumulators and an accumulator. We evidenced the existence of a conserved core rhizosphere microbiota in each plant distinct from that in the non-hyperaccumulating plant. Members of Burkholderiaceae and Sphingomonas were the shared cores across hyperaccumulators and accumulators. Several keystone taxa in the rhizosphere networks were part of the core microbiota, the abundance of which was an important predictor of plant Cd accumulation. Furthermore, an inoculation experiment with synthetic communities comprising isolates belonging to the shared cores indicated that core microorganisms could facilitate plant growth and metal tolerance. Using RNA-based stable isotope probing, we discovered that abundant core taxa overlapped with active rhizobacteria utilizing root exudates, implying that the core rhizosphere microbiota assimilating plant-derived carbon may provide benefits to plant growth and host phenotype such as Cd accumulation. Our study suggests common principles underpinning hyperaccumulator-microbiome interactions, where plants consistently interact with a core set of microbes contributing to host fitness and plant performance. These findings lay the foundation for harnessing the persistent root microbiomes to accelerate the restoration of metal-disturbed soils.

News Text Mining-Based Business Sentiment Analysis and Its Significance in Economy.

The purpose of business sentiment analysis is to determine the emotions or attitudes expressed toward the company, products, services, personnel, or events. Text analysis are the simplest and most developed types of sentiment analysis so far. The text-based business sentiment analysis still has some unresolved challenges. For example, the machine learning algorithms are unable to recognize double meanings, jokes and allusions. The regional differences between language and non-native speech structures cannot be explained. To solve this problem, an undirected weighted graph is constructed for news topics. The sentences in an article are modeled as nodes, and the normalized sentence similarity is used as the link of the nodes, which can help avoid the influence of sentence length on the summary results. In the topic extraction process, the keywords are not limited to a single word, to achieve the purpose of improving the readability of the abstract. To improve the accuracy of sentiment classification, this work proposes a robust news mining-based business sentiment analysis framework, called BuSeD. It contains two main stages: (1) news collection and preprocessing, and (2) feature extraction and sentiment classification. In the first stage, the news is collected by using crawler tools. The news dataset is then preprocessed by reducing noises. In the second stage, topics in each article is extracted by using traditional topic extraction tools. And then a convolutional neural network (CNN)-based text analyzing model is designed to analyze news from sentence level. We conduct comprehensive experiments to evaluate the performance of BuSeD for sentiment classification. Compared with four classical classification algorithms, the proposed CNN-based classification model of BuSeD achieves the highest F1 scores. We also present a quantitative trading application based on sentiment analysis to validate BuSeD, which indicates that the news-based business sentiment analysis has high economic application value.

The involvement of nitric oxide and ethylene on the formation of endodermal barriers in response to Cd in hyperaccumulator Sedum alfredii.

Nitric oxide (NO) and ethylene are both important signaling molecules which participate in numerous plant development processes and environmental stress resistance. Here, we investigate whether and how NO interacts with ethylene during the development of endodermal barriers that have major consequences for the apoplastic uptake of cadmium (Cd) in the hyperaccumulator Sedum alfredii. In response to Cd, an increased NO accumulation, while a decrease in ethylene production was observed in the roots of S. alfredii. Exogenous supplementation of NO donor SNP (sodium nitroprusside) decreased the ethylene production in roots, while NO scavenger cPTIO (2-(4-carboxyphenyl)-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide) had the opposite effect. The exogenous addition of NO affected the ethylene production through regulating the expression of genes related to ethylene synthesis. However, upon exogenous ethylene addition, roots retained their NO accumulation. The abovementioned results suggest that ethylene is downstream of the NO signaling pathway in S. alfredii. Regardless of Cd, addition of SNP promoted the deposition of endodermal barriers via regulating the genes related to Casparian strips deposition and suberization. Correlation analyses indicate that NO positively modifies the formation of endodermal barriers via the NO-ethylene signaling pathway, Cd-induced NO accumulation interferes with the synthesis of ethylene, leading to a deposition of endodermal barriers in S. alfredii.

RSM, ANN-GA and ANN-PSO modeling of SDBS removal from greywater in rural areas via Fe2O3-coated volcanic rocks.

Decontamination and reuse of greywater in rural areas has attracted increasing attention. Typical contaminants in grey water are SDBS, which has a stubborn molecular structure. In this study, Fe2O3-coated volcanic rocks (Fe2O3-VR) prepared from FeCl3 solution by a heating evaporation method can reach 95% removal of SDBS, which is 80% higher than before. The effect of contact time, pH, initial concentration, FeCl3 solution concentration, adsorbent dosage and calcination temperature on the removal rate was researched and modeled by response methodology (RSM) and artificial neural network (ANN). Based on the univariate test, the Box-Behnken design method was used to establish the data sample, which represented a quadratic polynomial model with p-value <0.001, R 2 = 0.9872, while the ANN model has the better performance with R 2 = 0.9961. The weights of the BP-ANN model were further analyzed using the Garson equation, and the results showed that the validity ranking of the variables was as follows: contact time (37.31%) > calcination temperature (29.43%) > dosage (24.44%) > initial concentration (17.18%) > FeCl3 solution concentration (17.18%) > pH (11.56%). Genetic algorithm (GA) and particle swarm optimization (PSO) were selected to optimize the process parameters. The results showed that ANN-PSO methodology presented a satisfactory alternative and the predicted removal efficiency was 99.9982% with relative error = 0.2230. The optimum level of contact time, pH, initial SDBS concentration, FeCl3 solution concentration, adsorbent dosage and calcination temperature is 136.45 min, 5.64, 22.4 mg L-1, 0.3 mol L-1, 83.21 g L-1, 274.02 °C, respectively. Moreover, Fe2O3-VR was characterized via instrumental analyses (SEM-EDS, FTIR, XRD, BET).

Adsorption and Fenton-like Degradation of Ciprofloxacin Using Corncob Biochar-Based Magnetic Iron-Copper Bimetallic Nanomaterial in Aqueous Solutions.

An economical corncob biochar-based magnetic iron-copper bimetallic nanomaterial (marked as MBC) was successfully synthesized and optimized through a co-precipitation and pyrolysis method. It was successfully used to activate H2O2 to remove ciprofloxacin (CIP) from aqueous solutions. This material had high catalytic activity and structural stability. Additionally, it had good magnetic properties, which can be easily separated from solutions. In MBC/H2O2, the removal efficiency of CIP was 93.6% within 360 min at optimal reaction conditions. The conversion of total organic carbon (TOC) reached 51.0% under the same situation. The desorption experiments concluded that adsorption and catalytic oxidation accounted for 34% and 66% on the removal efficiency of CIP, respectively. The influences of several reaction parameters were systematically evaluated on the catalytic activity of MBC. OH was proved to play a significant role in the removal of CIP through electron paramagnetic resonance (EPR) analysis and a free radical quenching experiment. Additionally, such outstanding removal efficiency can be attributed to the excellent electronic conductivity of MBC, as well as the redox cycle reaction between iron and copper ions, which achieved the continuous generation of hydroxyl radicals. Integrating HPLC-MS, ion chromatography and density functional theory (DFT) calculation results, and possible degradation of the pathways of the removal of CIP were also thoroughly discussed. These results provided a theoretical basis and technical support for the removal of CIP in water.

End-to-end computational optics with a singlet lens for large depth-of-field imaging.

Large depth-of-field (DOF) imaging with a high resolution is useful for applications ranging from robot vision to bio-imaging. However, it is challenging to construct an optical system with both a high resolution and large DOF. The common solution is to design relatively complex optical systems, but the setup of such systems is often bulky and expensive. In this paper, we propose a novel, compact, and low-cost method for large-DOF imaging. The core concept is to (1) design an aspherical lens with a depth-invariant point spread function to enable uniform image blurring over the whole depth range and (2) construct a deep learning network to reconstruct images with high fidelity computationally. The raw images captured by the aspherical lens are deblurred by the trained network, which enables large-DOF imaging at a smaller F number. Experimental results demonstrate that our end-to-end computational imager can achieve enhanced imaging performance. It can reduce loss by up to 46.5% compared to inherited raw images. With the capabilities of high-resolution and large-DOF imaging, the proposed method is promising for applications such as microscopic pathological diagnosis, virtual/augmented reality displays, and smartphone photography.