Synchronous Removal of Small-Sized Antibiotics by a Bifunctional Photocatalytic Nanofiltration Membrane in a Continuous Flow-Through Process under Multiple Influent Matrices

Bifunctional photocatalytic nanofiltration (PNF) membranes are of increasing significance in removing micropollutants in the actual water environment, but there are still critical bottlenecks that greatly limit their practicality. In this work, a metal-free and visible light-responsive surface-anchored PNF membrane was fabricated for simultaneously and efficiently removing target antibiotics from real river water in a continuous flow-through process. The results exhibited that the optimal PNF-3 membrane was expectedly consisted of an inside tight sub-nanopore structured separation layer and an outside thinner, super hydrophilic mesoporous degradation layer. Consequently, the PNF-3 membrane irradiated via visible light exhibited outstanding removal rates of sulfamethoxazole, trimethoprim, and chloramphenicol (between 99.0 and 99.9%), accompanied with almost constant high water permeability. In addition, after repeating the fouling–physical rinsing process three times that lasted for 60 h, only sporadic adherent contaminants remained on the top surface, together with minimal total and irreversible fouling ratios (only 7.9 and 1.2%), strongly proving that the PNF-3 membrane displayed good self-cleaning performance. In addition, the acute and chronic biotoxicities of its permeate to Virbrio qinghaiensis sp. -67 were also reduced significantly to 11.4 and 10.1%, respectively. This study might provide valuable insights into the continuous enhancement of the practicality and effectiveness of PNF membranes in micro-polluted water purification scenarios

Selective amplification with primer-pair of E09/HM39 for five digestion sets of both varieties.

<p>Selective amplification with primer-pair of E09/HM39 for five digestion sets of both varieties.</p

Transgenerational Variations in DNA Methylation Induced by Drought Stress in Two Rice Varieties with Distinguished Difference to Drought Resistance

<div><p>Adverse environmental conditions have large impacts on plant growth and crop production. One of the crucial mechanisms that plants use in variable and stressful natural environments is gene expression modulation through epigenetic modification. In this study, two rice varieties with different drought resistance levels were cultivated under drought stress from tilling stage to seed filling stage for six successive generations. The variations in DNA methylation of the original generation (G0) and the sixth generation (G6) of these two varieties in normal condition (CK) and under drought stress (DT) at seedling stage were assessed by using Methylation Sensitive Amplification Polymorphism (MSAP) method. The results revealed that drought stress had a cumulative effect on the DNA methylation pattern of both varieties, but these two varieties had different responses to drought stress in DNA methylation. The DNA methylation levels of II-32B (sensitive) and Huhan-3 (resistant) were around 39% and 32%, respectively. Genome-wide DNA methylation variations among generations or treatments accounted for around 13.1% of total MSAP loci in II-32B, but was only approximately 1.3% in Huhan-3. In II-32B, 27.6% of total differentially methylated loci (DML) were directly induced by drought stress and 3.2% of total DML stably transmitted their changed DNA methylation status to the next generation. In Huhan-3, the numbers were 48.8% and 29.8%, respectively. Therefore, entrainment had greater effect on Huhan-3 than on II-32B. Sequence analysis revealed that the DML were widely distributed on all 12 rice chromosomes and that it mainly occurred on the gene’s promoter and exon region. Some genes with DML respond to environmental stresses. The inheritance of epigenetic variations induced by drought stress may provide a new way to develop drought resistant rice varieties.</p> </div

Distribution of the DML at chromosome level (A) and gene level (B)c.

<p>Distribution of the DML at chromosome level (A) and gene level (B)c.</p

Expression of genes with DML.

<div><p>(A) Expression of genes which re-methylated in CK vs. DT in G0 of II-32B;</p> <p>(B) Expression of genes which re-methylated in CK vs. DT in G0 of Huhan-3;</p> <p>(C) Expression of genes which de-methylated in CK vs. DT in G0 of II-32B;</p> <p>(D) Expression of genes which de-methylated in CK vs. DT in G0 of Huhan-3.</p></div

Further analysis of DNA methylation variations between generations and between treatments.

<p>(A) Comparison based on generations (G0 and G6). Only G0 means that DNA methylation variations occurred between CK and DT in G0, but not in G6; Both G0 and G6 means that DNA methylation variations occurred between CK and DT in both G0 and G6; Only G6 means that DNA methylation variations occurred between CK and DT in G6, but not at G0; Non means that no DNA methylation variations occurred between CK and DT in both G0 and G6, but G0 and G6 had different methylation pattern. (B) Comparison based on treatments (CK and DT). Only CK means that DNA methylation variations occurred between G0 and G6 under CK, but not under DT; Both CK and DT means that DNA methylation variations occurred between G0 and G6 under both CK and DT; Only DT means DNA methylation variations occurred between G0 and G6 under DT, but not under CK; Non means no DNA methylation variations occurred between G0 and G6 under both CK and DT, but CK and DT had different methylation pattern.</p

FOXP3+ macrophage represses acute ischemic stroke-induced neural inflammation

Proper termination of cell-death-induced neural inflammation is the premise of tissue repair in acute ischemic stroke (AIS). Macrophages scavenge cell corpses/debris and produce inflammatory mediators that orchestrate immune responses. Here, we report that FOXP3, the key immune-repressive transcription factor of Tregs, is conditionally expressed in macrophages in stroke lesion. FOXP3 ablation in macrophages results in detrimental stroke outcomes, emphasizing the beneficial role of FOXP3+ macrophages. FOXP3+ macrophages are distinct from the M1 or M2 subsets and display superactive efferocytic capacity. With scRNAseq and analysis of FOXP3-bound-DNA isolated with CUT & RUN, we show that FOXP3 facilitates macrophage phagocytosis through enhancing cargo metabolism. FOXP3 expression is controlled by macroautophagic/autophagic protein degradation in resting macrophages, while initiation of LC3-associated phagocytosis (LAP) competitively occupies the autophagic machineries, and thus permits FOXP3 activation. Our data demonstrate a distinct set of FOXP3+ macrophages with enhanced scavenging capability, which could be a target in immunomodulatory therapy against AIS. Abbreviations: ADGRE1/F4/80: adhesion G protein-coupled receptor E1; AIF1/Iba1: allograft inflammatory factor 1; AIS: acute ischemic stroke; ARG1: arginase 1; ATP: adenosine triphosphate; BECN1/Beclin1: Beclin 1, autophagy related; BMDM: bone marrow-derived macrophages; CKO: conditional knockout; CSF1/M-CSF: colony stimulating factor 1 (macrophage); CSF2/GM-CSF: colony stimulating factor 2; CSF3/G-CSF: colony stimulating factor 3; CUT & RUN: cleavage under targets and release using nuclease; CyD: cytochalasin D; DAMP: danger/damage-associated molecular pattern; DIL: dioctadecyl-3,3,3,3-tetramethylin docarbocyanine; ELISA: enzyme linked immunosorbent assay; GO: Gene Ontology; FCGR3/CD16: Fc receptor, IgG, low affinity III; HMGB1: high mobility group box 1; IFNG/IFNγ: interferon gamma; IP: immunoprecipitation; KEGG: Kyoto Encyclopedia of Genes and Genomes; ITGAM/CD11b: integrin subunit alpha M; ITGAX/CD11c: integrin subunit alpha X; LAP: LC3-associated phagocytosis; LC-MS: liquid chromatography-mass spectrometry; LPS: lipopolysaccharide; MRC1/CD206: mannose receptor, C type 1; O4: oligodendrocyte marker O4; PBMC: peripheral blood mononuclear cells; RBC: red blood cells; PTPRC/CD45: protein tyrosine phosphatase, receptor type, C; RBFOX3/NeuN: RNA binding protein, fox 1 homolog (C. elegans) 3; RUBCN/Rubicon: RUN domain and cysteine-rich domain containing, Beclin 1-interacting protein; scRNAseq: single cell RNA sequencing; SQSTM1/p62 (sequestosome 1); TGFB/TGFβ: transforming growth factor, beta; tMCAO: transient middle cerebral artery occlusion; TNF/TNFα: tumor necrosis factor; Treg: regulatory T cell.</p