Embryonic Genome Activation (EGA) Occurred at 1-Cell Stage of Embryonic Development in the Mud Crab, Scylla paramamosain, Revealed by RNA-Seq.

As a prerequisite for the success of embryo development, embryonic genome activation (EGA) is an important biological event in which zygotic gene products in the embryo are activated to replace maternal-derived transcripts. Although EGA has been extensively studied in a large number of vertebrates and invertebrates, there is a lack of information regarding this event in crustacean crab. In this study, the timing of EGA was confirmed by examining a transcriptomic dataset of early embryonic development, including mature oocytes and embryos through six early developmental stages, and signaling pathways associated with EGA were identified in the mud crab, S. paramamosain. The comprehensive transcriptomic data identified a total of 53,915 transcripts from these sequencing samples. Notable transcriptomic change was evident at the 1-cell stage, indicated by a 36% transcript number shift and a reduction in transcript fragment length, compared to those present in the mature oocytes. Concurrently, a substantial increase in the expression of newly transcribed transcripts was observed, with gene counts reaching 3485 at the 1-cell stage, indicative of the onset of EGA. GO functional enrichment revealed key biological processes initiated at the 1-cell stage, such as protein complex formation, protein metabolism, and various biosynthetic processes. KEGG analysis identified several critical signaling pathways activated during EGA, including the "cell cycle," "spliceosome," "RNA degradation", and "RNA polymerase", pathways. Furthermore, transcription factor families, including zinc finger, T-box, Nrf1, and Tub were predominantly enriched at the 1-cell stage, suggesting their pivotal roles in regulating embryonic development through the targeting of specific DNA sequences during the EGA process. This groundbreaking study not only addresses a significant knowledge gap regarding the developmental biology of S. paramamosain, especially for the understanding of the mechanism underlying EGA, but also provides scientific data crucial for the research on the individual synchronization of seed breeding within S. paramamosain aquaculture. Additionally, it serves as a reference basis for the study of early embryonic development in other crustacean species.

[Temporal and spatial variations of vegetation coverage in Heilongjiang Basin and its responses to climate change]. / é»‘é¾™æ±ŸæµåŸŸæ¤è¢«è¦†ç›–åº¦æ—¶ç©ºåŠ¨æ€åŠå ¶å¯¹æ°”å€™å˜åŒ–çš„å“åº”.

Exploring the temporal and spatial dynamics of vegetation coverage in the Heilongjiang Basin and its response to climate change can provide a theoretical basis and data support for integrated basin management for three countries (Mongolia, China and Russia) in the region. We used MOD13Q1 remote sensing data from Google Earth Engine (GEE) platform between 2000 and 2020 to process the normalized vegetation index (NDVI) through the maximum value composites method, and calculated the vegetation coverage (FVC) using the dimidiate pixel model. The Sen+MK trend analysis method was employed to monitor the dynamics of FVC, while the Pearson correlation coefficient was utilized to quantify the responses of FVC to climate change. The results showed that the overall FVC in the Heilongjiang Basin exhibited a slight decreasing trend during 2000-2020, with an annual rate of 0.1%. The FVC in Mongolia showed a fluctuating increase trend (0.13%), while slight decrease trends were observed for Russia (0.15%) and China (0.08%). The FVC predominantly slightly degraded and severely degraded, accounting for 34% and 17% of the area, respectively, while the significantly improved area only accounted for 9%. The impact of precipitation on FVC in the study area was significantly greater than that of temperature. The proportion of areas where precipitation and temperature had a significant impact on FVC was 8.2% and 2.2%, respectively. The correlation coefficient between precipitation and FVC was the highest in Mongolia (r=0.446, P<0.05), and the lowest in Russian region (r=-0.442, P< 0.05).

[Effect of competition on the prediction accuracy of individual tree biomass model for natural Larix gmelinii forests]. / ç«žäº‰å¯¹å ´å®‰è½å¶æ¾å¤©ç„¶æž—å•æœ¨ç”Ÿç‰©é‡æ¨¡åž‹é¢„ä¼°ç²¾åº¦çš„å½±å“.

Quantifying the impact of competition on individual tree biomass and its distribution pattern can provide a basis for improving the prediction accuracy of forest biomass models. To accurately quantify the effects of competition factors on individual biomass and its distribution, we constructed three different individual biomass models by using nonlinear coupling equations based on the biomass survey data of 50 Larix gmelinii from 18 plots of Pangu Forest Farm in Daxing'an Mountains. M-1 was a traditional singly additive biomass model. M-2 and M-3 were models taking the distance dependent simple competition index (CI) and distance independent relative diameter (Rd) into account, respectively. Those models were used to reveal the influence of competition factors on the prediction accuracy and distribution pattern of single tree biomass model of L. gmelinii. The results showed that the adjusted R2 of three additive models ranged from 0.694 to 0.974, mean prediction errors ranged from -0.017 to 0.021, and mean absolute errors ranged from 0.152 to 0.357. The introduction of Rd could improve the fitting degree and prediction accuracy of most biomass models, but CI did not affect the model fitting effect and prediction ability. Among the three models, M-3 model had the best performance, with good fitting degree and prediction accuracy of the biomass of each part, which could accurately estimate the single tree biomass of L. gmelinii. Further simulation results showed that the variation of biomass with DBH was mainly affected by CI and Rd grade, and the influence of Rd was stronger than CI. CI had greater influence on root and dry biomass, but less influence on branch and leaf biomass. Rd had a more significant effect on biomass of branch and leaf than on that of root and trunk.

Facile synthesis of N-doped graphene quantum dots as a fluorescent sensor for Cr(vi) and folic acid detection.

The development of stable fluorescent sensors for toxic pollutants and drugs is meaningful to the environment and public health. In this work, nitrogen-doped graphene quantum dots (N-GQDs) were facially synthesized by a one-step hydrothermal method using soluble starch and l-arginine as carbon and nitrogen sources in pure water at 190 °C for 4 h. The as-synthesized N-GQDs were well characterized and displayed blue fluorescence emission at 445 nm with excellent pH stability, salt tolerance, thermostability, photobleaching resistance and reproducibility. Moreover, N-GQDs could serve as an "on-off" sensor for selective detection of Cr(vi) and folic acid with low detection limit (0.80 and 2.1 µM), good linear correlation over wide linear range (0-50 µM and 0-200 µM) as well as short response time (<10 s). The practical applications of N-GQDs for Cr(vi) and folic acid detection in actual samples were further investigated and showed acceptable recoveries (92-105%) with relative standard deviations less than 5%. These results indicated that this N-GQDs-based sensor could be a potential alternative for Cr(vi) and folic acid detection in the fields of environmental monitoring and drug analysis.

Diels-Alder Reaction Mechanisms of La@C60 and Gd@C60 Studied Using Density Functional Theory.

Encapsulation of transition metals represents a crucial method for modifying the electronic structure and regulating the reactivity of fullerene, thereby expanding its applications. Herein, we present calculations with density functional theory methods to investigate the mechanisms of the Diels-Alder (DA) reactions of cyclopentadiene and La@C60 or Gd@C60 as well as their tricationic derivatives. Our findings indicate that the encapsulation of La and Gd into the C60 cage is thermodynamically favorable. The DA reactions are favored by the presence of La and Gd, with lower barriers, though the regioselectivity, favoring 6-6 bonds in the fullerene, is not affected. The effect of external electric fields has been also considered.

Prion protein E219K polymorphism: from the discovery of the KANNO blood group to interventions for human prion disease.

KANNO is a new human blood group that was recently discovered. The KANNO antigen shares the PRNP gene with the prion protein and the prion protein E219K polymorphism determines the presence or absence of the KANNO antigen and the development of anti-KANNO alloantibodies. These alloantibodies specifically react with prion proteins, which serve as substrates for conversion into pathological isoforms in some prion diseases and may serve as effective targets for resisting prion infection. These findings establish a potential link between the KANNO blood group and human prion disease via the prion protein E219K polymorphism. We reviewed the interesting correlation between the human PRNP gene's E219K polymorphism and the prion proteins it expresses, as well as human red blood cell antigens. Based on the immune serological principles of human blood cells, the prion protein E219K polymorphism may serve as a foundation for earlier molecular diagnosis and future drug development for prion diseases.

Metabolic disorders and hepatitis: Insights from a Mendelian randomization study.

BACKGROUND: Hepatitis is a systemic disease that often results in various comorbidities. Meta-bolic disorders, the most common comorbidities in clinical practice, were selected for this study. AIM: To investigate the causal relationship between comorbidities and hepatitis trea-tment outcomes. METHODS: A total of 23583378 single nucleotide polymorphisms from 1248743 cases and related summaries of genome-wide association studies were obtained from online public databases. A two-sample Mendelian randomization (MR) was performed to investigate causality between exposure [type 2 diabetes mellitus (T2D), hyperlipidemia, and hypertension] and outcome (chronic hepatitis B or C in-fections). RESULTS: The data supported the causal relationship between comorbidities and hepatitis infections, which will affect the severity of hepatitis progression and will also provide a reference for clinical researchers. All three exposures showed a link with progression of both hepatitis B (T2D, P = 0.851; hyperlipidemia, P = 0.596; and hypertension, P = 0.346) and hepatitis C (T2D, P = 0.298; hyperlipidemia, P = 0.141; and hypertension, P = 0.035). CONCLUSION: The results of MR support a possible causal relationship between different ex-posures (T2D, hyperlipidemia, and hypertension) and chronic hepatitis progression; however, the potential mechanisms still need to be elucidated.

Visible-Light-Driven Reduction of CO2 to CO with Highly Active and Selective Earth-Abundant Metal Porphyrin-Conjugated Organic Polymers.

The field of artificial photosynthesis, which focuses on harnessing solar light for the conversion of CO2 to economically valuable chemical products, remains a captivating area of research. In this study, we developed a series of photocatalysts based on Earth abundant elements (Fe, Co, Ni, Cu, and Zn) incorporated into 2D metalloporphyrin-conjugated organic polymers known as MTBPP-BEPA-COPs. These photocatalysts were utilized for the photoreduction of CO2 employing only H2O as the electron donor, without the need for any sacrificial agents or precious-metal cocatalysts. Remarkably, all of the synthesized MTBPP-BEPA-COPs exhibited an exceptional CO2 photoreduction performance only irradiated by visible light. Particularly, upon optimizing the metal ion coordinated with porphyrin units, ZnTBPP-BEPA-COP outperformed the other MTBPP-BEPA-COPs in terms of photocatalytic activity, achieving an impressive CO reduction yield of 152.18 µmol g-1 after just 4 h of irradiation. The electrostatic potential surfaces calculated by density functional theory suggest the potential involvement of metal centers as binding and catalytic sites for the binding of CO2. The calculated adsorption energy of CO2 with ZnTBPP-BEPA-COP exhibited one of the two smallest values. This may be the reason for the excellent catalytic effect of ZnTBPP-BEPA-COP. Thus, the present study not only demonstrates the potential of porphyrin-based conjugated polymers as highly efficient photocatalysts for CO2 reduction but also offers valuable insights into the rational design of such materials in the future.

Establishment of a corneal ulcer prognostic model based on machine learning.

Corneal infection is a major public health concern worldwide and the most common cause of unilateral corneal blindness. Toxic effects of different microorganisms, such as bacteria and fungi, worsen keratitis leading to corneal perforation even with optimal drug treatment. The cornea forms the main refractive surface of the eye. Diseases affecting the cornea can cause severe visual impairment. Therefore, it is crucial to analyze the risk of corneal perforation and visual impairment in corneal ulcer patients for making early treatment strategies. The modeling of a fully automated prognostic model system was performed in two parts. In the first part, the dataset contained 4973 slit lamp images of corneal ulcer patients in three centers. A deep learning model was developed and tested for segmenting and classifying five lesions (corneal ulcer, corneal scar, hypopyon, corneal descementocele, and corneal neovascularization) in the eyes of corneal ulcer patients. Further, hierarchical quantification was carried out based on policy rules. In the second part, the dataset included clinical data (name, gender, age, best corrected visual acuity, and type of corneal ulcer) of 240 patients with corneal ulcers and respective 1010 slit lamp images under two light sources (natural light and cobalt blue light). The slit lamp images were then quantified hierarchically according to the policy rules developed in the first part of the modeling. Combining the above clinical data, the features were used to build the final prognostic model system for corneal ulcer perforation outcome and visual impairment using machine learning algorithms such as XGBoost, LightGBM. The ROC curve area (AUC value) evaluated the model's performance. For segmentation of the five lesions, the accuracy rates of hypopyon, descemetocele, corneal ulcer under blue light, and corneal neovascularization were 96.86, 91.64, 90.51, and 93.97, respectively. For the corneal scar lesion classification, the accuracy rate of the final model was 69.76. The XGBoost model performed the best in predicting the 1-month prognosis of patients, with an AUC of 0.81 (95% CI 0.63-1.00) for ulcer perforation and an AUC of 0.77 (95% CI 0.63-0.91) for visual impairment. In predicting the 3-month prognosis of patients, the XGBoost model received the best AUC of 0.97 (95% CI 0.92-1.00) for ulcer perforation, while the LightGBM model achieved the best performance with an AUC of 0.98 (95% CI 0.94-1.00) for visual impairment.

[Age estimation model for individual tree in natural Larix gmelinii forest based on random forest model]. / åŸºäºŽéšæœºæ£®æž—çš„å ´å®‰è½å¶æ¾å¤©ç„¶æž—å•æœ¨å¹´é¾„é¢„ä¼°æ¨¡åž‹.

To accurately estimate the age of individual tree and to achieve full-cycle sustainable management of natural Larix gmelinii forest in Great Xing'an Mountains of northeastern China, we constructed individual tree age prediction model using stepwise regression and random forest algorithms based on 44 fixed plots data and 280 stan-dard tree cores obtained from the Pangu Forest Farm. We analyzed the influence of stand structure, site conditions, and competition index on the accuracy of model prediction. The model was evaluated by the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The results showed that the random forest model had the highest prediction accuracy when number of decision trees was 1500 and number of node con-tention variables was 8. The random forest model had better accuracy and prediction ability than the stepwise regression model, with R2, RMSE and MAE of 0.5882, 9.9259 a, 8.1155 a. Diameter at breast height was the most important factor affecting age prediction (83.8%), followed by tree height (34.4%), elevation (17.9%), and basal area per hectare (17.5%). The random forest algorithm exhibited better adaptability and modeling effect on constructing a predictive model for individual tree age. This research contributed to improving the accuracy of growth and harvest estimation for L. gmelinii, and could provide a reference for other scientific studies related to tree age estimation in forests.

Nickel-Catalyzed Highly Selective Radical C-C Coupling from Carboxylic Acids with Photoredox Catalysis.

Controlling the cross-coupling reaction between two different radicals is a long-standing challenge due to the process occurring statistically, which would lead to three products, including two homocoupling products and one cross-coupling product. Generally, the cross-coupling selectivity is achieved by the persistent radical effect (PRE) that requires the presence of a persistent radical and a transient radical, thus resulting in limited radical precursors. In this paper, a highly selective cross-coupling of alkyl radicals with acyl radicals to construct C(sp2)-C(sp3) bonds, or with alkyl radicals to construct C(sp3)-C(sp3) bonds have been achieved with the readily available carboxylic acids and their derivatives (NHPI ester) as coupling partners. The success originates from the use of tridentate ligand (2,2' : 6',2''-terpyridine) to enable radical cross-coupling process to Ni-mediated organometallic mechanism. This protocol offers a facile and flexible access to structurally diverse ketones (up to 90 % yield), and also a new solution for the challenging double decarboxylative C(sp3)-C(sp3) coupling. The broad utility and functional group tolerance are further illustrated by the late-stage functionalization of natural-occurring carboxylic acids and drugs.

Research Progress on Active Ingredients and Product Development of Lycium ruthenicum Murray.

Lycium ruthenicum Murray possesses significant applications in both food and medicine, including antioxidative, anti-tumor, anti-fatigue, anti-inflammatory, and various other effects. Consequently, there has been a surge in research endeavors dedicated to exploring its potential benefits, necessitating the organization and synthesis of these findings. This article systematically reviews the extraction and content determination methods of active substances such as polysaccharides, anthocyanins, flavonoids, and polyphenols in LRM in the past five years, as well as some active ingredient composition determination methods, biological activities, and product development. This review is divided into three main parts: extraction and determination methods, their bioactivity, and product development. Building upon prior research, we also delve into the economic and medicinal value of Lycium ruthenicum Murray, thereby contributing significantly to its further exploration and development. It is anticipated that this comprehensive review will serve as a valuable resource for advancing research on Lycium ruthenicum Murray.

Comprehensive analysis of immune-related lncRNAs in AML patients uncovers potential therapeutic targets and prognostic biomarkers.

Purpose: The objective of this study was to provide theoretically feasible strategies by understanding the relationship between the immune microenvironment and the diagnosis and prognosis of AML patients. To this end, we built a ceRNA network with lncRNAs as the core and analyzed the related lncRNAs in the immune microenvironment by bioinformatics analysis. Methods: AML transcriptome expression data and immune-related gene sets were obtained from TCGA and ImmPort. Utilizing Pearson correlation analysis, differentially expressed immune-related lncRNAs were identified. Then, the LASSO-Cox regression analysis was performed to generate a risk signature consisting immune-related lncRNAs. Accuracy of signature in predicting patient survival was evaluated using univariate and multivariate analysis. Next, GO and KEGG gene enrichment and ssGSEA were carried out for pathway enrichment analysis of 183 differentially expressed genes, followed by drug sensitivity and immune infiltration analysis with pRRophetic and CIBERSORT, respectively. Cytoscape was used to construct the ceRNA network for these lncRNAs. Results: 816 common lncRNAs were selected to acquire the components related to prognosis. The final risk signature established by multivariate Cox and stepwise regression analysis contained 12 lncRNAs engaged in tumor apoptotic and metastatic processes: LINC02595, HCP5, AC020934.2, AC008770.3, LINC01770, AC092718.4, AL589863.1, AC131097.4, AC012368.1, C1RL-AS1, STARD4-AS1, and AC243960.1. Based on this predictive model, high-risk patients exhibited lower overall survival rates than low-risk patients. Signature lncRNAs showed significant correlation with tumor-infiltrating immune cells. In addition, significant differences in PD-1/PD-L1 expression and bleomycin/paclitaxel sensitivity were observed between risk groups. Conclusion: LncRNAs related to immune microenvironment were prospective prognostic and therapeutic options for AML.

IGSF10 inhibits the metastasis of lung adenocarcinoma via the Spi-B/Integrin-ß1 signaling pathway.

IGSF10, a protein that belongs to the immunoglobulin superfamily, is involved in regulating the early migration of neurons that produce gonadotropin-releasing hormone and performs a fundamental function in development. Our previous study confirmed that the mRNA expression level of IGSF10 may be a protective prognosis factor for lung adenocarcinoma (LUAD) patients. However, the specific mechanisms of IGSF10 are still unclear. In this research, it was shown that the protein level of IGSF10 was down-modulated in LUAD tissues and had a link to the clinical and pathological characteristics as well as the patient's prognosis in LUAD. Importantly, IGSF10 regulates the metastatic ability of LUAD cells in vitro and in vivo. It was proven in a mechanistic sense that IGSF10 inhibits the capacity of LUAD cells to metastasize through the Spi-B/Integrin-ß1 signaling pathway. These findings gave credence to the premise that IGSF10 performed a crucial function in LUAD.

Bezafibrate alleviates diabetes-induced spermatogenesis dysfunction by inhibiting inflammation and oxidative stress.

The metabolic disorders caused by diabetes can lead to various complications, including male spermatogenesis dysfunction. Exploring effective therapeutics that attenuate diabetes mellitus (DM)-induced male subfertility is of great importance. Pharmaceuticals targeting PPARα activation such as bezafibrate have been regarded as an important strategy for patients with diabetes. In this study, we use streptozocin (STZ) injection to establish a type 1 DM mice model and use bezafibrate to treat DM mice and evaluate the effects of bezafibrate on the spermatogenic function of the DM male mice. Bezafibrate treatment exhibited protective effects on DM-induced spermatogenesis deficiency, as reflected by increased testis weight, improved histological morphology of testis, elevated sperm parameters, increased serum testosterone concentration as well as increased mRNA levels of steroidogenesis enzymes. Meanwhile, testicular cell apoptosis, inflammation accumulation and oxidative stress status were also shown to be alleviated by bezafibrate compared with the DM group. In vivo and in vitro studies, PPARα specific inhibitor and PPARα knockout mice were further used to investigate the role of PPARα in the protective effects of bezafibrate on DM-induced spermatogenesis dysfunction. Our results indicated that the protection of bezafibrate on DM-induced spermatogenesis deficiency was abrogated by PPARα inhibition or deletion. Our study suggested that bezafibrate administration could ameliorate DM-induced spermatogenesis dysfunction and may represent a novel practical strategy for male infertility.

Correlation analysis of bone marrow microvessel density and miRNA expression on drug resistance in patients with chronic myelogenous leukemia after tyrosine kinase inhibitor treatment.

OBJECTIVE: This study analyzed the relationship between bone marrow microvessel density (MVD) and the expression of four miRNAs with chronic myelogenous leukemia (CML) resistance after tyrosine kinase inhibitor (TKI) treatment. METHODS: 234 CML patients were divided into resistance and non-resistance groups in terms of the results of the 5-year follow-up. Patients were divided into the Optimum response group and the Warning/Failure group based on TKI response. MVD was determined by immunohistochemistry, and the expression levels of four miRNAs (miR-106a, miR-155, miR-146a, and miR-340) in bone marrow biopsy specimens were examined by qPCR. We evaluated the association of MVD with four miRNAs and them predictive value for CML resistance after TKI treatment. RESULTS: The MVD and the levels of miR-106a, miR-155, and miR-146a were significantly higher while the miR-340 level was lower in the resistance group than the non-resistance group. Besides, MVD had a significant correlation with the levels of miR-340 and miR-155. According to the results of survival analysis, MVD as well as miR-340 and miR-155 levels were observably correlated with 5-year survival of patients without TKI resistance. The results of the ROC curve indicated that the MVD, miR-106a, miR-340, and miR-155 had good predictive accuracy for CML resistance after TKI treatment. As for the results of multivariate analysis, disease stage, risk level (high risk), high MVD, low miR-340 expression, and high miR-155 expression were all independent risk factors for CML resistance. CONCLUSION: MVD and the expression of miR-340 and miR-155 are closely associated with CML resistance after TKI treatment.

Lipid concentration and composition in xylem sap of woody angiosperms from a tropical savanna and a seasonal rainforest.

Lipids may play an important role in preventing gas embolisms by coating nanobubbles in xylem sap. Few studies on xylem sap lipids have been reported for temperate plants, and it remain unclear whether sap lipids have adaptational significance in tropical plants. In this study, we quantify the lipid composition of xylem sap for angiosperm species from a tropical savanna (seven species) and a seasonal rainforest (five species) using mass spectrometry. We found that all twelve species studied contained lipids in their xylem sap, including galactolipids, phospholipids and triacylglycerol, with a total lipid concentration ranging from 0.09 to 0.26 nmol/L. There was no difference in lipid concentration or composition between plants from the two sites, and the lipid concentration was negatively related to species' open vessel volume. Furthermore, savanna species showed little variation in lipid composition between the dry and the rainy season. These results support the hypothesis that xylem sap lipids are derived from the cytoplasm of individual conduit cells, remain trapped inside individual conduits, and undergo few changes in composition over consecutive seasons. A xylem sap lipidomic data set, which includes 12 tropical tree species from this study and 11 temperate tree species from literature, revealed no phylogenetic signals in lipid composition for these species. This study fills a knowledge gap in the lipid content of xylem sap in tropical trees and provides additional support for their common distribution in xylem sap of woody angiosperms. It appears that xylem sap lipids have no adaptive significance.

Hydrogen bond unlocking-driven pore structure control for shifting multi-component gas separation function.

Purification of ethylene (C2H4) as the most extensive and output chemical, from complex multi-components is of great significance but highly challenging. Herein we demonstrate that precise pore structure tuning by controlling the network hydrogen bonds in two highly-related porous coordination networks can shift the efficient C2H4 separation function from C2H2/C2H4/C2H6 ternary mixture to CO2/C2H2/C2H4/C2H6 quaternary mixture system. Single-crystal X-ray diffraction revealed that the different amino groups on the triazolate ligands resulted in the change of the hydrogen bonding in the host network, which led to changes in the pore shape and pore chemistry. Gas adsorption isotherms, adsorption kinetics and gas-loaded crystal structure analysis indicated that the coordination network Zn-fa-atz (2) weakened the affinity for three C2 hydrocarbons synchronously including C2H4 but enhanced the CO2 adsorption due to the optimized CO2-host interaction and the faster CO2 diffusion, leading to effective C2H4 production from the CO2/C2H2/C2H4/C2H6 mixture in one step based on the experimental and simulated breakthrough data. Moreover, it can be shaped into spherical pellets with maintained porosity and separation performance.

Versatile Application of TiO2@PDA Modified Filter Paper for Oily Wastewater Treatment.

Although membrane separation technology has been widely used in the treatment of oily wastewater, the complexity and high cost of the membrane preparation, as well as its poor stability, limit its further development. In this study, via the vacuum-assisted suction filtration method, polydopamine (PDA)-coated TiO2 nanoparticles were tightly attached and embedded on both sides of laboratory filter paper (FP). The resultant FP possessed the typical wettability of high hydrophilicity in the air with the water contact angle (WCA) of 28°, superoleophilicity with the oil contact angle (OCA) close to 0°, underwater superoleophobicity with the underwater OCA greater than 150°, and superhydrophobicity under the water with the underoil WCA over 150° for five kinds of organic solvents (carbon tetrachloride, toluene, n-hexane, n-octane, and iso-octane). The separation efficiency of immiscible oil/water, oil-in-water, and water-in-oil emulsions using the modified FP is higher than 99%. After 17 cycles of emulsion separation, a high separation efficiency of 99% was still maintained for the FP, along with good chemical and mechanical stability. In addition, successful separation and purification were also realized for the oil-in-water emulsion that contained the methylene blue (MB) dye, along with the complete degradation of MB in an aqueous solution under UV irradiation.