ALKBH5-mediated m6A modification of IL-11 drives macrophage-to-myofibroblast transition and pathological cardiac fibrosis in mice.

Cardiac macrophage contributes to the development of cardiac fibrosis, but factors that regulate cardiac macrophages transition and activation during this process remains elusive. Here we show, by single-cell transcriptomics, lineage tracing and parabiosis, that cardiac macrophages from circulating monocytes preferentially commit to macrophage-to-myofibroblast transition (MMT) under angiotensin II (Ang II)-induced hypertension, with accompanying increased expression of the RNA N6-methyladenosine demethylases, ALKBH5. Meanwhile, macrophage-specific knockout of ALKBH5 inhibits Ang II-induced MMT, and subsequently ameliorates cardiac fibrosis and dysfunction. Mechanistically, RNA immunoprecipitation sequencing identifies interlukin-11 (IL-11) mRNA as a target for ALKBH5-mediated m6A demethylation, leading to increased IL-11 mRNA stability and protein levels. By contrast, overexpression of IL11 in circulating macrophages reverses the phenotype in ALKBH5-deficient mice and macrophage. Lastly, targeted delivery of ALKBH5 or IL-11 receptor α (IL11RA1) siRNA to monocytes/macrophages attenuates MMT and cardiac fibrosis under hypertensive stress. Our results thus suggest that the ALKBH5/IL-11/IL11RA1/MMT axis alters cardiac macrophage and contributes to hypertensive cardiac fibrosis and dysfunction in mice, and thereby identify potential targets for cardiac fibrosis therapy in patients.

Characterization, structure and inhibition of the human succinyl-CoA:glutarate-CoA transferase, a genetic modifier of glutaric aciduria type 1.

Glutaric Aciduria Type 1 (GA1) is a serious inborn error of metabolism with no pharmacological treatments. A novel strategy to treat this disease is to divert the toxic biochemical intermediates to less toxic or non-toxic metabolites. Here, we report a novel target, SUGCT, which we hypothesize suppresses the GA1 metabolic phenotype through decreasing glutaryl-CoA. We report the structure of SUGCT, the first eukaryotic structure of a type III CoA transferase, develop a high-throughput enzyme assay and a cell-based assay, and identify valsartan and losartan carboxylic acid as inhibitors of the enzyme validating the screening approach. These results may form the basis for future development of new pharmacological intervention to treat GA1.

Treatment of diabetic foot with moxibustion: Clinical evidence from meta-analysis.

To assess the efficacy of moxibustion for diabetic foot, and compile the findings of randomised clinical trials. China National Knowledge Infrastructure Database, Medicine, WanFang Database, Embase, Chinese Scientific Journal Database and Web of Science were from the establishment to January, 2024 were searched. Randomised controlled trials, which evaluated the effects of moxibustion were included. A total of 12 randomised controlled trials involving 1196 patients were included. According to the pooled results of this meta-analysis, effective rate (relative risk 1.16, 95% confidence intervals, CI [1.11, 1.22]), healing time (mean difference [MD] -6.27, 95% CI [-8.68, -3.86]), wound area (MD 3.46, 95% CI [0.84, 6.09]), and ankle brachial index (MD 0.14, 95% CI [0.03, 0.24]) were statistically significant compared to the control group. This study suggests that moxibustion treatment has the potential for improving symptoms of diabetic foot. However, future in-depth research on the benefits and harms of moxibustion for the diabetic foot is needed before it can be accepted as an evidence-based treatment.

A dual-signal aptasensor based on cascade amplification for ultrasensitive detection of aflatoxin B1.

Aflatoxin B1 (AFB1) is considered as a serious carcinogenic mycotoxin that was widely detected in grains and foods, and its sensitive analysis is of key importance to avoid the health threats for consumers. In this study, a dual-signal aptasensor based on cascade of entropy-driven strand displacement reaction (ESDR) and linear rolling circle amplification (LRCA) was fabricated for ultrasensitive determination of AFB1. At the sensing system, the complementary strand would be released after the aptamer combined with AFB1, which will bring about the functional domains exposed, triggering the subsequent ESDR. Meanwhile, the two strands that were outputted by ESDR would incur the downstream LRCA reaction to produce a pair of long strands to assist in the generation of fluorescence and absorbance signals. Under the optimized conditions, the proposed aptasensor could achieve excellent sensitivity (limit of detection, 0.427 pg/mL) with satisfactory accuracy (recoveries, 92.8-107.9 %; RSD, 2.4-5.0 %), mainly ascribed to the cascade amplification. Importantly, owing to the flexibility design of nucleic acid primer, this analytical method can be applied in monitoring various hazardous substances according to the specific requirements. Our strategy provides some novel insights at signal amplification for rapid detection of AFB1 and other targets.

Profiling regulatory T lymphocytes within the tumor microenvironment of breast cancer via radiomics.

OBJECTIVE: To generate an image-driven biomarker (Rad_score) to predict tumor-infiltrating regulatory T lymphocytes (Treg) in breast cancer (BC). METHODS: Overall, 928 BC patients were enrolled from the Cancer Genome Atlas (TCGA) for survival analysis; MRI (n = 71 and n = 30 in the training and validation sets, respectively) from the Cancer Imaging Archive (TCIA) were retrieved and subjected to repeat least absolute shrinkage and selection operator for feature reduction. The radiomic scores (rad_score) for Treg infiltration estimation were calculated via support vector machine (SVM) and logistic regression (LR) algorithms, and validated on the remaining patients. RESULTS: Landmark analysis indicated Treg infiltration was a risk factor for BC patients in the first 5 years and after 10 years of diagnosis (p = 0.007 and 0.018, respectively). Altogether, 108 radiomic features were extracted from MRI images, 4 of which remained for model construction. Areas under curves (AUCs) of the SVM model were 0.744 (95% CI 0.622-0.867) and 0.733 (95% CI 0.535-0.931) for training and validation sets, respectively, while for the LR model, AUCs were 0.771 (95% CI 0.657-0.885) and 0.724 (95% CI 0.522-0.926). The calibration curves indicated good agreement between prediction and true value (p > 0.05), and DCA shows the high clinical utility of the radiomic model. Rad_score was significantly correlated with immune inhibitory genes like CTLA4 and PDCD1. CONCLUSIONS: High Treg infiltration is a risk factor for patients with BC. The Rad_score formulated on radiomic features is a novel tool to predict Treg abundance in the tumor microenvironment.

Contrast-Enhanced Mammography Radiomics Analysis for Preoperative Prediction of Breast Cancer Molecular Subtypes.

BACKGROUND: Predicting breast cancer molecular subtypes can help guide individualised clinical treatment of patients who need the rational preoperative treatment. This study aimed to investigate the efficacy of preoperative prediction of breast cancer molecular subtypes by contrast-enhanced mammography (CEM) radiomic features. METHODS: This retrospective two-centre study included women with breast cancer who underwent CEM preoperatively between August 2016 and May 2022. We included 356 patients with 386 lesions, which were grouped into training (n = 162), internal test (n = 160) and external test sets (n = 64). Radiomics features were extracted from low-energy (LE) images and recombined (RC) images and selected. Three dichotomous tasks were established according to postoperative immunohistochemical results: Luminal vs. non-Luminal, human epidermal growth factor receptor (HER2)-enriched vs. non-HER2-enriched, and triple-negative breast cancer (TNBC) vs. non-TNBC. For each dichotomous task, the LE, RC, and LE+RC radiomics models were built by the support vector machine classifier. The prediction performance of the models was assessed by the area under the receiver operating characteristic curve (AUC). Then, the accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were calculated for the models. DeLong's test was utilised to compare the AUCs. RESULTS: Radiomics models based on CEM are valuable for predicting breast cancer molecular subtypes. The LE+RC model achieved the best performance in the test set. The LE+RC model predicted Luminal, HER2-enriched, and TNBC subtypes with AUCs of 0.93, 0.89, and 0.87 in the internal test set and 0.82, 0.83, and 0.69 in the external test set, respectively. In addition, the LE model performed more satisfactorily than the RC model. CONCLUSION: CEM radiomics features can effectively predict breast cancer molecular subtypes preoperatively, and the LE+RC model has the best predictive performance.

Facile synthesis of Ag/ZIF-8@ZIF-67 as an electrochemical sensing platform for sensitive detection of halonitrophenols in drinking water.

Halonitrophenols (HNPs) are an emerging type of aromatic disinfection byproduct, with detected concentrations of ∼nmol L-1 in source water and drinking water. Currently, there are no standard methods for identifying HNPs, and most of the reported methods are time-consuming and equipment-dependent. A core-shell metal-organic framework (MOF) based electrochemical sensor (Ag/ZIF-8@ZIF-67) capable of detecting 2,6-dichloro-4-nitrophenol (2,6-DCNP) is reported in this study. The electrochemical sensor obtains the concentration of 2,6-DCNP by detecting the peak current passing through the sensor. In this sensor, Ag nanoparticles (AgNPs) play a key role in electrochemical sensing by reducing nitro groups via electron transfer, and porous structure with a large surface area is offered by ZIF-8@ZIF-67. The cyclic voltammetry (CV) response of Ag/ZIF-8@ZIF-67 was found to be approximately 1.75 times and 2.23 times greater than that of Ag/ZIF-8 and Ag/ZIF-67, respectively, suggesting an ideal synergistic effect of the core-shell structures. The Ag/ZIF-8@ZIF-67 sensor exhibited exceptional sensitivity to 2,6-DCNP, exhibiting a broad linear response range (R2 = 0.992) from 240 nmol L-1 to 288 µmol L-1 and a low detection limit of 20 nmol L-1. Furthermore, the sensor exhibited good anti-interference for isomers and common distractors in water, excellent stability and reproducibility, and high recovery in actual water samples. Our reported sensor gives a novel strategy for sensitive, selective, and in situ detection of 2,6-DCNP in practical analysis.

Pre-oxidation coupled with charged covalent organic framework membranes for highly efficient removal of organic chloramines precursors in algae-containing water treatment.

Organic chloramines in water would pose both chemical and microbiological risks. It is essential to remove the precursors of organic chloramine (amino acids and decomposed peptides/proteins) to limit its formation in disinfection. In our work, nanofiltration was chosen to remove organic chloramines precursors. To solve the "trade-off" effect and low rejection of small molecules in algae organic matter, we synthesized a thin film composite (TFC) nanofiltration (NF) membrane with a crumpled polyamide (PA) layer via interfacial polymerization on polyacrylonitrile (PAN) composite support loaded with covalent organic framework (COF) nanoparticles (TpPa-SO3H). The obtained NF membrane (PA-TpPa-SO3H/PAN) increased the permeance from 10.2 to 28.2 L m-2 h-1 bar-1 and the amino acid rejection from 24% to 69% compared to the control NF membrane. The addition of TpPa-SO3H nanoparticles decreased the thickness of PA layers, increased the hydrophilicity of the membrane, and increased the transition energy barrier for amino acids transferring through the membrane, which was identified by scanning electron microscope, contact angle test, and density functional theory computations, respectively. Finally, pre-oxidation coupled with PA-TpPa-SO3H/PAN membrane nanofiltration on the limitation of organic chloramines formation was evaluated. We found that the combined application of KMnO4 pre-oxidation and PA-TpPa-SO3H/PAN membranes nanofiltration in algae-containing water treatment could minimize the formation of organic chloramines in subsequent chlorination and maintain a high flux during filtration. Our work provides an effective way for algae-containing water treatment and organic chloramines control.

Identification of multi-component metal ion mixtures in complex systems using fluorescence sensor arrays.

The growing co-contamination of multiple metal ions seriously influences human health due to their synergistic and additive toxicological effects, whereas the rapid discrimination of multiple heavy metal ions in complex aquatic systems remains a major challenge. Herein, a high- throughput fluorescence sensor array was fabricated based on three gold nanoclusters (GSH-Au NCs, OVA-Au NCs, and BSA-Au NCs) for the direct identification and quantification of seven heavy metal ions (Pb2+, Fe3+, Cu2+, Co2+, Ag+, Hg2+ and As3+) from environmental waters without sample pretreatment other than filtration. At the detection system, three gold nanoclusters with various ligands possessed distinct binding capacities against metal ions and induced aggregation-induced fluorescence enhancement and quenching, resulting in a unique pattern of fluorescence variations. Meanwhile, integrated the collected fluorescence fingerprints with linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA), a discrete database was obtained for the accurate recognition and sensitive detection of metal ions. Under the optimized conditions, the limit of detection (LOD) of the proposed fluorescence sensor array for metal ions detection at nM concentration level along with a satisfactory accuracy. Importantly, our study indicated that the fluorescence sensor array could be widely used as a general platform in environmental monitoring against multiple targets at low concentrations.

Structural insights into RNA cleavage by a novel family of bacterial RNases.

Processing of RNA is a key regulatory mechanism for all living systems. We recently discovered a novel family of endoribonucleases that is conserved across all bacteria. Here, using crystallography, cryo-EM microscopy, biochemical, biophysical, and mass spectrometry techniques, we are able to shed light on a novel RNA cleavage mechanism in bacteria. We show that YicC, the prototypical member of this family, forms a hexameric channel that closes down on a 26-mer RNA substrate, and find that it cleaves across an RNA hairpin to generate several short fragments.

Specific gut microbiome and metabolome changes in patients with continuous ambulatory peritoneal dialysis and comparison between patients with different dialysis vintages.

Background: In recent years, the role of gut microbiota and derived metabolites in renal disease has attracted more attention. It has been established that the gut microbiota is a potential target for medical interventions in renal disease including chronic kidney disease (CKD), acute kidney injury (AKI) and renal calculus. Emerging evidence has related dialysis treatment to the microbial composition and function of the intestines, and there are many reports related to HD, but few studies have been related to PD. Previous studies have found that PD patients have intestinal flora disturbances, so we speculate that intestinal flora and its metabolites may be the regulatory factors in long-term therapy of PD. And as far as we know, there have been no studies characterized the gut microbiota in PD patients of different dialysis vintages. Methods: It is a cross-sectional study based on clinical data and biological samples of 72 patients with CAPD, 13 patients with ESRD and 13 healthy volunteers. The intestinal microecological characteristics of CAPD patients were comprehensively evaluated by combining the intestinal microflora structure, enterotoxin and receptor (serum LPS and LBP), intestinal barrier function index (serum D-Lactate), intestinal uremic toxin (serum IS, PCS, TMAO), fecal SCFAs and other multi-dimensional and multi-omics studies. Furthermore, the changes of intestinal microecology in CAPD patients of different dialysis vintages (≥ 3 and < 12 months, ≥ 12 and < 24 months, ≥ 24 and < 60 months, ≥ 60 months) were further explored, and the correlations between intestinal microecology indicators and some clinical indicators were analyzed. Fecal and serum samples were collected from PD patients (PD group, n = 72), ESRD patients (ESRD group, n = 13) and healthy volunteers (Normal group, n = 13). Fecal samples were subjected to microbiome (16S rDNA) and SCFA (GC-MS) analyses. Serum samples were subjected to LPS, LBP, D-lactate, IS, PCS, and TMAO (ELISA) analyses. Results: The diversity and richness of intestinal flora in CAPD patients were lower than those in healthy people and ESRD patients, and the microflora structure was different. Anaerobes of Blautia and facultative anaerobes and aerobic bacteria with Bacilli and Lactobacillales those in Firmicutes are the main intestinal flora in CAPD patients. The abundance of Bacteroidaceae, Bacteroides, Faecalibacterium and other dominant bacteria in the intestinal tract of CAPD patients decreased. Proteobacteria, Enterobacteriaceae and Escherichia-Shigella increased their colonization (LDA > 4). In CAPD patients of different dialysis vintages, there was no significant change in the diversity and richness of microflora, and the microflora structure of PDC group was significantly different from that of PDD, which the abnormal expansion of enterobacter group was more prominent in PDC and the abundance of Bacteroides group was relatively higher in PDD. Intestinal barrier damage, intestinal uremic toxin accumulation and short-chain fatty acid reduction were observed in CAPD patients, such as the serum level of D-Lactate, PCS and TMAO were significantly higher than that in the Normal group (P < 0.05),and the fecal levels of BA and CA were significantly lower (P < 0.05). The intestinal microecological disorder of PDC group, while that of PDD group showed a better trend. Such as the PDC group had a significantly higher serum level of LPS, D-Lactate and TMAO (P < 0.01), and significantly lower serum level of LBP (P < 0.01), and lower fecal levels of AA and BA (P > 0.05) than the PDD group. Conclusion: The intestinal microecology and metabolic system of CAPD patients had changes compared with healthy people and ESRD non-dialysis patients, and there were differences in CAPD patients with different dialysis vintages. PD patients on dialysis for more than 60 months showed a better trend in the intestinal microecology than patients with 24∼36 months, which suggested that the intestinal microecology of PD patients had a certain ability of self-regulation and remodeling under the management of standardized system and it is necessary to strengthen the monitoring of the intestinal status and the occurrence of related complications in PD patients on dialysis of 24∼36 months of dialysis vintage. It is initially considered that the mechanism of intestinal microecology is a potential target for intervention in the diagnosis and treatment of CAPD and incorporating intestinal microecosystem monitoring into the long-term management of CAPD patients is a new strategy.

Predicting diagnostic gene expression profiles associated with immune infiltration in patients with lupus nephritis.

Objective: To identify potential diagnostic markers of lupus nephritis (LN) based on bioinformatics and machine learning and to explore the significance of immune cell infiltration in this pathology. Methods: Seven LN gene expression datasets were downloaded from the GEO database, and the larger sample size was used as the training group to obtain differential genes (DEGs) between LN and healthy controls, and to perform gene function, disease ontology (DO), and gene set enrichment analyses (GSEA). Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE), were applied to identify candidate biomarkers. The diagnostic value of LN diagnostic gene biomarkers was further evaluated in the area under the ROC curve observed in the validation dataset. CIBERSORT was used to analyze 22 immune cell fractions from LN patients and to analyze their correlation with diagnostic markers. Results: Thirty and twenty-one DEGs were screened in kidney tissue and peripheral blood, respectively. Both of which covered macrophages and interferons. The disease enrichment analysis of DEGs in kidney tissues showed that they were mainly involved in immune and renal diseases, and in peripheral blood it was mainly enriched in cardiovascular system, bone marrow, and oral cavity. The machine learning algorithm combined with external dataset validation revealed that C1QA(AUC = 0.741), C1QB(AUC = 0.758), MX1(AUC = 0.865), RORC(AUC = 0.911), CD177(AUC = 0.855), DEFA4(AUC= 0.843)and HERC5(AUC = 0.880) had high diagnostic value and could be used as diagnostic biomarkers of LN. Compared to controls, pathways such as cell adhesion molecule cam, and systemic lupus erythematosus were activated in kidney tissues; cell cycle, cytoplasmic DNA sensing pathways, NOD-like receptor signaling pathways, proteasome, and RIG-1-like receptors were activated in peripheral blood. Immune cell infiltration analysis showed that diagnostic markers in kidney tissue were associated with T cells CD8 and Dendritic cells resting, and in blood were associated with T cells CD4 memory resting, suggesting that CD4 T cells, CD8 T cells and dendritic cells are closely related to the development and progression of LN. Conclusion: C1QA, C1QB, MX1, RORC, CD177, DEFA4 and HERC5 could be used as new candidate molecular markers for LN. It may provide new insights into the diagnosis and molecular treatment of LN in the future.

Exploring consumers' intention toward domestic energy-saving vehicles: Some insights from China.

Policies to promote the usage of energy-saving vehicles (EVs), such as electric vehicles and hybrids, were introduced and implemented in many countries due to increasing awareness of the potential benefits of such vehicles on environmental and energy conservation. However, despite consumers' claims of their concerns and positive attitudes toward environmental issues, those claims have not been translated into energy-saving vehicles' purchasing behavior. Prior studies neglected the interrelationship between consumer ethnocentrism (CE), perceived value (PV), and consumer knowledge (CK) in influencing consumer behavior, including pro-environmental behavior. This study examines the relationship between CE, PV, CK, perceived usefulness (PU), perceived ease of use (PEU), attitude and intention to purchase domestic energy-saving vehicles. A total of 396 completed questionnaires were collected through convenience sampling in Xuzhou, China. The survey data were subjected to descriptive analysis and analysis of variance using SPSS. In addition, confirmatory factor analysis and structural equation modeling (SEM) were utilized for the hypotheses testing. The results revealed that CE positively influenced PV and CK; PV and CK positively influenced PU and PEU. CK positively influenced PV, while PU and PEU positively influenced attitude and intention, and PEU was shown to influence PU. Furthermore, attitude was shown to significantly influence intention to purchase domestic energy-saving vehicles. Lastly, the theoretical and practical implications of the outcomes were discussed, including the limitations of the research.

Facile synthesis of a novel BaSnO3/MXene nanocomposite by electrostatic self-assembly for efficient photodegradation of 4-nitrophenol.

Photocatalysis is regarded as one of the most effective strategies for the removal of the toxic organic pollutants from aqueous solutions. However, a lack of the efficient photocatalysts prevents the widespread practical application. Herein, the electrostatic self-assembly method has been designed for facile synthesis of a novel BaSnO3/PDDA/MXene (BSO/P/MX) nanocomposite as high efficient photocatalyst. In this nanocomposite, the BaSnO3 (BSO), poly (dimethyl-diallylammonium chloride) (PDDA) and MXene (Ti3C2Tx) act as the active species, structure stabilizer and efficient electron transfer medium, respectively. Due to the strong synergy of the nanocomposite, the electron-transferring ability as well as the charge separation efficiency is boosted and thus high catalytic activity achieves towards the photodegradation of 4-nitrophenol. The superior degradation rate of 98.8% and a rate constant K of 0.09113 min-1 have been realized within 75 min of ultraviolet (UV) light irradiation over the BSO/P/MX-8% catalyst. This as-prepared nanocomposite with the excellent catalytic activity can be employed as a promising photocatalyst for treating the organic pollutants from aqueous solutions.

The new CORSIA baseline has limited motivation to promote the green recovery of global aviation.

The Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) is the first programme to tackle carbon dioxide (CO2) emissions from a single industry at the global level, to realize the carbon-neutral growth of international flights from 2020 onwards. However, the COVID-19 pandemic has caused a drastic decline in the global aviation industry. The International Civil Aviation Organization (ICAO) has adjusted the CORSIA by removing 2020 emissions from the baseline, which now will only be based on 2019 emissions. We estimate that the total carbon dioxide (CO2) emissions from global international flights decreased by 70 % from February to July 2020 compared to those in 2019. Our analysis suggests that the annual CO2 emissions from international flights during the pilot stage of CORSIA (2021-2023) will be far below the revised baseline even if the global aviation industry could embrace an optimistic recovery. The major airline companies will have very limited motivations due to the CORSIA scheme to implement mitigation actions proactively. Therefore, more progressive actions are needed to align the industry recovery of global aviation and climate change mitigation during the post-COVID-19 period.

Prediction and Validation of Mouse Meiosis-Essential Genes Based on Spermatogenesis Proteome Dynamics.

The molecular mechanism associated with mammalian meiosis has yet to be fully explored, and one of the main reasons for this lack of exploration is that some meiosis-essential genes are still unknown. The profiling of gene expression during spermatogenesis has been performed in previous studies, yet few studies have aimed to find new functional genes. Since there is a huge gap between the number of genes that are able to be quantified and the number of genes that can be characterized by phenotype screening in one assay, an efficient method to rank quantified genes according to phenotypic relevance is of great importance. We proposed to rank genes by the probability of their function in mammalian meiosis based on global protein abundance using machine learning. Here, nine types of germ cells focusing on continual substages of meiosis prophase I were isolated, and the corresponding proteomes were quantified by high-resolution MS. By combining meiotic labels annotated from the mouse genomics informatics mouse knockout database and the spermatogenesis proteomics dataset, a supervised machine learning package, FuncProFinder (https://github.com/sjq111/FuncProFinder), was developed to rank meiosis-essential candidates. Of the candidates whose functions were unannotated, four of 10 genes with the top prediction scores, Zcwpw1, Tesmin, 1700102P08Rik, and Kctd19, were validated as meiosis-essential genes by knockout mouse models. Therefore, mammalian meiosis-essential genes could be efficiently predicted based on the protein abundance dataset, which provides a paradigm for other functional gene mining from a related abundance dataset.

Ultrafiltration pre-oxidation by boron-doped diamond anode for algae-laden water treatment: membrane fouling mitigation, interface characteristics and cake layer organic release.

In this study, ultrafiltration (UF) pre-oxidation with a boron-doped diamond (BDD) electrode was employed aiming to mitigate membrane fouling during algae-laden water treatment. It was found that BDD anodizing can efficiently alleviate membrane fouling regardless of the filtration membrane material when the oxidation time was over 30 min. This was because that the cake layer fouling resistance was highly mitigated by the pre-oxidation process. The generated small molecular organics after anodic oxidation might increase the potential of pore blockage. The anodizing preferentially oxidized hydrophobic organic and fluorescent substances, which is conducive to reducing membrane fouling and improving production efficiency. Besides, disinfection byproduct precursors and harmful algae derived substances of UF filtrated solution were contained. The algae bodies tend to agglomeration and the zeta potential obviously declined after the pretreatment, which is instrumental in forming a loose cake layer structure. In addition, the interaction force between membrane and foulants also converted to a repulsion force after pre-oxidation, which implies that BDD pre-oxidation was an effective way to mitigate cake layer fouling by reducing foulant-membrane interactions. At last, the secondary organic release of a dynamic formed cake layer was proved to be limited especially for living algae cells.

Hydrothermal formation of controllable hexagonal holes and Er2O3/Er2O3-RGO particles on silicon wafers toward superhydrophobic surfaces.

In this work, controllable hexagonal holes and distributed Er2O3/Er2O3- graphene particles are fabricated on silicon wafers using a straightforward, hydrofluoric, acid-free, and strong alkali-free hydrothermal method. As long as erbium nitrate hydrate and urea coexist in the reaction mixture, silicon wafers can be synthesized successfully using controllable hexagonal hole structures that are regulated by hydrothermal temperature and the addition of graphene oxide and hexadecyl trimethyl ammonium bromide to the reaction mixture. Correspondingly, the wettability of these silicon wafers also is controllable due to the structure that can be changed from hydrophilic (89.3°) to superhydrophobic (153.1°). In short, this work not only provides a simple and nontoxic approach for preparing hexagonal hole structured silicon wafers, but also produces superhydrophobic silicon wafers that potentially can be applied for corrosion-resistant coatings, oil-water separation, and other fields.

Genome-Wide Characterization of DNase I-Hypersensitive Sites and Cold Response Regulatory Landscapes in Grasses.

Deep sequencing of DNase-I treated chromatin (DNase-seq) can be used to identify DNase I-hypersensitive sites (DHSs) and facilitates genome-scale mining of de novo cis-regulatory DNA elements. Here, we adapted DNase-seq to generate genome-wide maps of DHSs using control and cold-treated leaf, stem, and root tissues of three widely studied grass species: Brachypodium distachyon, foxtail millet (Setaria italica), and sorghum (Sorghum bicolor). Functional validation demonstrated that 12 of 15 DHSs drove reporter gene expression in transiently transgenic B. distachyon protoplasts. DHSs under both normal and cold treatment substantially differed among tissues and species. Intriguingly, the putative DHS-derived transcription factors (TFs) are largely colocated among tissues and species and include 17 ubiquitous motifs covering all grass taxa and all tissues examined in this study. This feature allowed us to reconstruct a regulatory network that responds to cold stress. Ethylene-responsive TFs SHINE3, ERF2, and ERF9 occurred frequently in cold feedback loops in the tissues examined, pointing to their possible roles in the regulatory network. Overall, we provide experimental annotation of 322,713 DHSs and 93 derived cold-response TF binding motifs in multiple grasses, which could serve as a valuable resource for elucidating the transcriptional networks that function in the cold-stress response and other physiological processes.

Unzipping haplotypes in diploid and polyploid genomes.

Diploid genomes consist of two homologous copies of chromosomes with one from each parent while polyploid genomes contain more than two homologous sets of chromosomes. Most of the reference genome assemblies collapsed haplotypes that represent 'mosaic' sequences, ignoring allelic variants that may be involved in important cellular and biological functions. Unzipping haplotypes into distinct sets of sequences has been a growing trend in recent genome studies, as it is an essential tool towards resolving important clinical and biological questions, such as compound heterozygotes, heterosis, and evolution. Herein, we review existing methods for alignment-based and assembly-based haplotype phasing for heterozygous diploid and polyploid genomes, as well as recent advances of experimental approaches for improved genome phasing. We anticipate that full haplotype phasing could become a routine procedure in genome studies in the near future.