ProsperousPlus: a one-stop and comprehensive platform for accurate protease-specific substrate cleavage prediction and machine-learning model construction.

Proteases contribute to a broad spectrum of cellular functions. Given a relatively limited amount of experimental data, developing accurate sequence-based predictors of substrate cleavage sites facilitates a better understanding of protease functions and substrate specificity. While many protease-specific predictors of substrate cleavage sites were developed, these efforts are outpaced by the growth of the protease substrate cleavage data. In particular, since data for 100+ protease types are available and this number continues to grow, it becomes impractical to publish predictors for new protease types, and instead it might be better to provide a computational platform that helps users to quickly and efficiently build predictors that address their specific needs. To this end, we conceptualized, developed, tested and released a versatile bioinformatics platform, ProsperousPlus, that empowers users, even those with no programming or little bioinformatics background, to build fast and accurate predictors of substrate cleavage sites. ProsperousPlus facilitates the use of the rapidly accumulating substrate cleavage data to train, empirically assess and deploy predictive models for user-selected substrate types. Benchmarking tests on test datasets show that our platform produces predictors that on average exceed the predictive performance of current state-of-the-art approaches. ProsperousPlus is available as a webserver and a stand-alone software package at http://prosperousplus.unimelb-biotools.cloud.edu.au/.

ATTIC is an integrated approach for predicting A-to-I RNA editing sites in three species.

A-to-I editing is the most prevalent RNA editing event, which refers to the change of adenosine (A) bases to inosine (I) bases in double-stranded RNAs. Several studies have revealed that A-to-I editing can regulate cellular processes and is associated with various human diseases. Therefore, accurate identification of A-to-I editing sites is crucial for understanding RNA-level (i.e. transcriptional) modifications and their potential roles in molecular functions. To date, various computational approaches for A-to-I editing site identification have been developed; however, their performance is still unsatisfactory and needs further improvement. In this study, we developed a novel stacked-ensemble learning model, ATTIC (A-To-I ediTing predICtor), to accurately identify A-to-I editing sites across three species, including Homo sapiens, Mus musculus and Drosophila melanogaster. We first comprehensively evaluated 37 RNA sequence-derived features combined with 14 popular machine learning algorithms. Then, we selected the optimal base models to build a series of stacked ensemble models. The final ATTIC framework was developed based on the optimal models improved by the feature selection strategy for specific species. Extensive cross-validation and independent tests illustrate that ATTIC outperforms state-of-the-art tools for predicting A-to-I editing sites. We also developed a web server for ATTIC, which is publicly available at http://web.unimelb-bioinfortools.cloud.edu.au/ATTIC/. We anticipate that ATTIC can be utilized as a useful tool to accelerate the identification of A-to-I RNA editing events and help characterize their roles in post-transcriptional regulation.

TIMER is a Siamese neural network-based framework for identifying both general and species-specific bacterial promoters.

BACKGROUND: Promoters are DNA regions that initiate the transcription of specific genes near the transcription start sites. In bacteria, promoters are recognized by RNA polymerases and associated sigma factors. Effective promoter recognition is essential for synthesizing the gene-encoded products by bacteria to grow and adapt to different environmental conditions. A variety of machine learning-based predictors for bacterial promoters have been developed; however, most of them were designed specifically for a particular species. To date, only a few predictors are available for identifying general bacterial promoters with limited predictive performance. RESULTS: In this study, we developed TIMER, a Siamese neural network-based approach for identifying both general and species-specific bacterial promoters. Specifically, TIMER uses DNA sequences as the input and employs three Siamese neural networks with the attention layers to train and optimize the models for a total of 13 species-specific and general bacterial promoters. Extensive 10-fold cross-validation and independent tests demonstrated that TIMER achieves a competitive performance and outperforms several existing methods on both general and species-specific promoter prediction. As an implementation of the proposed method, the web server of TIMER is publicly accessible at http://web.unimelb-bioinfortools.cloud.edu.au/TIMER/.

iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities.

Antimicrobial peptides (AMPs) are short peptides that play crucial roles in diverse biological processes and have various functional activities against target organisms. Due to the abuse of chemical antibiotics and microbial pathogens' increasing resistance to antibiotics, AMPs have the potential to be alternatives to antibiotics. As such, the identification of AMPs has become a widely discussed topic. A variety of computational approaches have been developed to identify AMPs based on machine learning algorithms. However, most of them are not capable of predicting the functional activities of AMPs, and those predictors that can specify activities only focus on a few of them. In this study, we first surveyed 10 predictors that can identify AMPs and their functional activities in terms of the features they employed and the algorithms they utilized. Then, we constructed comprehensive AMP datasets and proposed a new deep learning-based framework, iAMPCN (identification of AMPs based on CNNs), to identify AMPs and their related 22 functional activities. Our experiments demonstrate that iAMPCN significantly improved the prediction performance of AMPs and their corresponding functional activities based on four types of sequence features. Benchmarking experiments on the independent test datasets showed that iAMPCN outperformed a number of state-of-the-art approaches for predicting AMPs and their functional activities. Furthermore, we analyzed the amino acid preferences of different AMP activities and evaluated the model on datasets of varying sequence redundancy thresholds. To facilitate the community-wide identification of AMPs and their corresponding functional types, we have made the source codes of iAMPCN publicly available at https://github.com/joy50706/iAMPCN/tree/master. We anticipate that iAMPCN can be explored as a valuable tool for identifying potential AMPs with specific functional activities for further experimental validation.

Critical Role of miR-130b-5p in Cardiomyocyte Proliferation and Cardiac Repair in Mice After Myocardial Infarction.

Poor proliferative capacity of adult cardiomyocytes is the primary cause of heart failure after myocardial infarction (MI), thus exploring the molecules and mechanisms that promote the proliferation of adult cardiomyocytes is crucially useful for cardiac repair after MI. Here, we found that miR-130b-5p was highly expressed in mouse embryonic and neonatal hearts and able to promote cardiomyocyte proliferation both in vitro and in vivo. Mechanistic studies revealed that miR-130b-5p mainly promoted the cardiomyocyte proliferation through the MAPK-ERK signaling pathway, and the dual-specific phosphatase 6 (Dusp6), a negative regulator of the MAPK-ERK signaling, was the direct target of miR-130b-5p. Moreover, we found that overexpression of miR-130b-5p could promote the proliferation of cardiomyocytes and improve cardiac function in mice after MI. These studies thus revealed the critical role of miR-130b-5p and its targeted MAPK-ERK signaling in the cardiomyocyte proliferation of adult hearts and proved that miR-130b-5p could be a potential target for cardiac repair after MI.

Clarion is a multi-label problem transformation method for identifying mRNA subcellular localizations.

Subcellular localization of messenger RNAs (mRNAs) plays a key role in the spatial regulation of gene activity. The functions of mRNAs have been shown to be closely linked with their localizations. As such, understanding of the subcellular localizations of mRNAs can help elucidate gene regulatory networks. Despite several computational methods that have been developed to predict mRNA localizations within cells, there is still much room for improvement in predictive performance, especially for the multiple-location prediction. In this study, we proposed a novel multi-label multi-class predictor, termed Clarion, for mRNA subcellular localization prediction. Clarion was developed based on a manually curated benchmark dataset and leveraged the weighted series method for multi-label transformation. Extensive benchmarking tests demonstrated Clarion achieved competitive predictive performance and the weighted series method plays a crucial role in securing superior performance of Clarion. In addition, the independent test results indicate that Clarion outperformed the state-of-the-art methods and can secure accuracy of 81.47, 91.29, 79.77, 92.10, 89.15, 83.74, 80.74, 79.23 and 84.74% for chromatin, cytoplasm, cytosol, exosome, membrane, nucleolus, nucleoplasm, nucleus and ribosome, respectively. The webserver and local stand-alone tool of Clarion is freely available at http://monash.bioweb.cloud.edu.au/Clarion/.

Positive-unlabeled learning in bioinformatics and computational biology: a brief review.

Conventional supervised binary classification algorithms have been widely applied to address significant research questions using biological and biomedical data. This classification scheme requires two fully labeled classes of data (e.g. positive and negative samples) to train a classification model. However, in many bioinformatics applications, labeling data is laborious, and the negative samples might be potentially mislabeled due to the limited sensitivity of the experimental equipment. The positive unlabeled (PU) learning scheme was therefore proposed to enable the classifier to learn directly from limited positive samples and a large number of unlabeled samples (i.e. a mixture of positive or negative samples). To date, several PU learning algorithms have been developed to address various biological questions, such as sequence identification, functional site characterization and interaction prediction. In this paper, we revisit a collection of 29 state-of-the-art PU learning bioinformatic applications to address various biological questions. Various important aspects are extensively discussed, including PU learning methodology, biological application, classifier design and evaluation strategy. We also comment on the existing issues of PU learning and offer our perspectives for the future development of PU learning applications. We anticipate that our work serves as an instrumental guideline for a better understanding of the PU learning framework in bioinformatics and further developing next-generation PU learning frameworks for critical biological applications.

LncCMRR Plays an Important Role in Cardiac Differentiation by Regulating the Purb/Flk1 Axis.

As crucial epigenetic regulators, long noncoding RNAs (lncRNAs) play critical functions in development processes and various diseases. However, the regulatory mechanism of lncRNAs in early heart development is still limited. In this study, we identified cardiac mesoderm-related lncRNA (LncCMRR). Knockout (KO) of LncCMRR decreased the formation potential of cardiac mesoderm and cardiomyocytes during embryoid body differentiation of mouse embryonic stem (ES) cells. Mechanistic analyses showed that LncCMRR functionally interacted with the transcription suppressor PURB and inhibited its binding potential at the promoter region of Flk1, which safeguarded the transcription of Flk1 during cardiac mesoderm formation. We also carried out gene ontology term and signaling pathway enrichment analyses for the differentially expressed genes after KO of LncCMRR, and found significant correlation of LncCMRR with cardiac muscle contraction, dilated cardiomyopathy, and hypertrophic cardiomyopathy. Consistently, the expression level of Flk1 at E7.75 and the thickness of myocardium at E17.5 were significantly decreased after KO of LncCMRR, and the survival rate and heart function index of LncCMRR-KO mice were also significantly decreased as compared with the wild-type group. These findings indicated that the defects in early heart development led to functional abnormalities in adulthood heart of LncCMRR-KO mice. Conclusively, our findings elucidate the main function and regulatory mechanism of LncCMRR in cardiac mesoderm formation, and provide new insights into lncRNA-mediated regulatory network of mouse ES cell differentiation.

The improvement of postoperative blood pressure and associated factors in patients with hormone-negative adrenal adenoma and hypertension.

OBJECTIVE: To investigate the effect of adrenal surgery on blood pressure (BP) improvements in patients with hormone-negative adrenal adenoma (HNA) concomitant with hypertension and analyze associated prognostic factors. METHODS: We retrospectively reviewed the clinical data of patients with HNA and hypertension and patients with aldosterone-producing adenoma (APA) and hypertension who underwent adrenal surgery at our center between 2019 and 2022. Hypertension outcomes were evaluated in all patients and subjects were divided into three groups according to follow-up BP and the administration of anti-hypertensive agents: a clinical curation group, an improvement group, and a no-improvement group. Logistic regression analysis was performed to predict factors associated with clinical curation in patients with HNA post-surgery. RESULTS: Of the 182 patients with HNA, clinical curation was achieved in 58 patients (31.9%), improvement in 72 (39.5%), and no improvement in 52 (28.6%). The clinical curation, improvement and no improvement rates in patients with APA were 64.8% (n = 118), 15.9% (n = 29), and 19.2% (n = 35). Multivariate logistic regression analysis indicated that a duration of hypertension ≤6 years and a plasma aldosterone level >160 pg/ml were both independent factors for the clinical curation of hypertension in patients with HNA after adrenal surgery. CONCLUSION: Adrenal surgery can cure or improve hypertension in most patients with HNA, especially in a short duration of hypertension and high plasma levels of aldosterone.

A chalcone-based ESIPT and AIE fluorophore for ß-gal imaging in living cells.

ß-Galactosidase (ß-gal), which is responsible for the hydrolysis of the glycosidic bond of lactose to galactose, has been recognized as an important biomarker of cell or organism status, especially cell senescence and primary ovarian cancer. Extensive efforts have been devoted to develop probes for detecting and visualizing ß-gal in cells. Herein, a fluorescent probe gal-HCA which possesses both excited-state intramolecular proton transfer (ESIPT) and aggregation-induced emission (AIE) properties was prepared to monitor ß-gal in living cells. The probe consists of 2-hydroxy-4'-dimethylamino-chalcone (HCA) capped with a D-galactose group. The cleavage of the glycosidic bond in gal-HCA triggered by ß-gal releases HCA, which results in a significant bathochromic shift in fluorescence from 532 to 615 nm. The probe exhibited high selectivity and sensitivity toward ß-gal with a detection limit as low as 0.0122 U mL-1. The confocal imaging investigation demonstrated the potential of gal-HCA in monitoring the endocellular overexpressed ß-gal in senescent cells and ovarian cancer cells. This study provides a straightforward approach for the development of fluorescent probes to monitor ß-gal and detection of ß-gal-associated diseases.

A novel non-chemically amplified resist based on polystyrene-iodonium derivatives for electron beam lithography.

To break the resolution limitation of traditional resists, more work is needed on non-chemically amplified resists (non-CARs). Non-CARs based on iodonium salt modified polystyrene (PS-I) were prepared with controllable molecular weight and structure. The properties of the resist can be adjusted by the uploading of iodonium salts on the polymer chain, the materials with a higher proportion of iodonium salts show better lithography performance. By comparing contrast curves and quality of the lithographic patterns, the optimum developing condition of 4-methyl-2-pentanone and ethyl alcohol (v:v = 1:7) was selected. The high-resolution stripes of 15 nm half-pitch (HP) can be achieved by PS-I0.58in e-beam lithography (EBL). PS-I0.58shows the advanced lithography performance in the patterns of 16 nm HP and 18 nm HP stripes with low line edge roughness (3.0 nm and 2.4 nm). The resist shows excellent potential for further pattern transfer, the etch selectivity of resist PS-I0.58to the silicon was close to 12:1. The lithographic mechanism of PS-I was investigated by experimental and theoretical calculation, which indicates the polarity of materials changes results in the solubility switch. This work provides a new option and useful guidelines for the development of high-resolution resist.

Porpoise: a new approach for accurate prediction of RNA pseudouridine sites.

Pseudouridine is a ubiquitous RNA modification type present in eukaryotes and prokaryotes, which plays a vital role in various biological processes. Almost all kinds of RNAs are subject to this modification. However, it remains a great challenge to identify pseudouridine sites via experimental approaches, requiring expensive and time-consuming experimental research. Therefore, computational approaches that can be used to perform accurate in silico identification of pseudouridine sites from the large amount of RNA sequence data are highly desirable and can aid in the functional elucidation of this critical modification. Here, we propose a new computational approach, termed Porpoise, to accurately identify pseudouridine sites from RNA sequence data. Porpoise builds upon a comprehensive evaluation of 18 frequently used feature encoding schemes based on the selection of four types of features, including binary features, pseudo k-tuple composition, nucleotide chemical property and position-specific trinucleotide propensity based on single-strand (PSTNPss). The selected features are fed into the stacked ensemble learning framework to enable the construction of an effective stacked model. Both cross-validation tests on the benchmark dataset and independent tests show that Porpoise achieves superior predictive performance than several state-of-the-art approaches. The application of model interpretation tools demonstrates the importance of PSTNPs for the performance of the trained models. This new method is anticipated to facilitate community-wide efforts to identify putative pseudouridine sites and formulate novel testable biological hypothesis.

Large-scale fabrication of an ultrathin broadband absorber using quasi-random dielectric Mie resonators.

Ultrathin broadband absorber maintaining a near-uniform low reflectivity over a broadband wavelength is essential for many optical applications, such as light harvesting and nanoscale imaging. Recently, there has been considerable interest in employing arrays of high-index dielectric Mie resonators on surfaces to trap light and reduce the reflectivity. For such Mie-resonant metasurfaces, however, antireflection properties featuring both a flat low reflectance curve and a wide bandwidth are hard to be satisfied simultaneously, and an efficient large-scale nanofabrication technique rarely exists. Here, we present a high-throughput laser interference induced quasi-random patterning (LIIQP) technique to fabricate quasi-random Mie resonators in large scale. Mie resonators with feature sizes down to sub-100 nm have been fabricated using a 1064 nm laser source. Each Mie resonator concentrates light at its shape-dependent resonant frequency, and all such resonators are arranged quasi-randomly to provide both rich (with broadband Fourier components) and strong (with large intensities) Fourier spectra. Specifically, a near-uniform broadband reflectivity over 400-1100 nm spectrum region has been confined below 3% by fabricating a large-scale ultrathin (around 400 nm) absorber. Our concept and high-throughput fabrication technique allows the rapid production of quasi-random dielectric Mie-resonant metasurfaces in a controllable way, which can be used in various promising applications including thin-film solar cells, display, and imaging.

Linc1548 Promotes the Transition of Epiblast Stem Cells Into Neural Progenitors by Engaging OCT6 and SOX2.

The transition of embryonic stem cells from the epiblast stem cells (EpiSCs) to neural progenitor cells (NPCs), called the neural induction process, is crucial for cell fate determination of neural differentiation. However, the mechanism of this transition is unclear. Here, we identified a long non-coding RNA (linc1548) as a critical regulator of neural differentiation of mouse embryonic stem cells (mESCs). Knockout of linc1548 did not affect the conversion of mESCs to EpiSCs, but delayed the transition from EpiSCs to NPCs. Moreover, linc1548 interacts with the transcription factors OCT6 and SOX2 forming an RNA-protein complex to regulate the transition from EpiSCs to NPCs. Finally, we showed that Zfp521 is an important target gene of this RNA-protein complex regulating neural differentiation. Our findings prove how the intrinsic transcription complex is mediated by a lncRNA linc1548 and can better understand the intrinsic mechanism of neural fate determination.

Periostin promotes nucleus pulposus cells apoptosis by activating the Wnt/ß-catenin signaling pathway.

Intervertebral disc (IVD) degeneration (IVDD) is closely linked to degenerative spinal disease, resulting in disability, poor quality of life, and financial burden. Apoptosis of nucleus pulposus (NP) cells (NPCs) is a key pathological basis of IVDD. Periostin (POSTN), an extracellular matrix protein, is expressed in many tissues, whereas its abnormal expression is associated with IVDD. The conventional Wnt/ß-catenin pathway is also involved in IVDD and contributes to NPCs apoptosis. However, research on the mechanisms of POSTN in IVDD is lacking. This study investigated the relationship between POSTN and ß-catenin expression in degenerated IVDs. We detected the expression of POSTN, ß-catenin, and cleaved-caspase-3 (C-caspase3) in degenerated and non-degenerated IVD tissues of different grades (n = 8) using RT-qPCR, immunohistochemical staining, and western blotting analysis. Next, we explored the effects of recombinant periostin (rPOSTN) and isoquercitrin (Iso), an inhibitor of the Wnt/ß-catenin pathway, on NPCs apoptosis. Finally, we inhibited the expression of POSTN in degenerated NPCs in vivo and investigated the anti-apoptotic effect. The expression of ß-catenin, POSTN, and C-caspase3 in severe degenerative IVDs was significantly higher than that in mild degenerative IVDs. These findings were confirmed in rat and cell-based degenerative models. When treated with rPOSTN, the Wnt/ß-catenin pathway activity and cell apoptosis were time- and dose-dependent. However, rPOSTN-induced NPCs apoptosis decreased after iso-induced inhibition of the Wnt/ß-catenin pathway. POSTN inhibition reduced apoptosis but was restored by rPOSTN re-addition. Lastly, POSTN inhibition ameliorated puncture-induced IVDD in vivo. Overall, our study demonstrated that POSTN promotes NPCs apoptosis and aggravates degeneration by activating the Wnt/ß-catenin pathway.

ARID3A plays a key regulatory role in palmitic acid-stimulated milk fat synthesis in mouse mammary epithelial cells.

Palmitic acid (PA) can stimulate milk fat synthesis in mammary gland, but the specific mechanism is still unclear. In our research, we aim to explore the role and corresponding mechanism of AT-rich interaction domain 3A (ARID3A) in milk fat synthesis stimulated by PA. We found that ARID3A protein level in mouse mammary gland tissues during lactation was much higher than that during puberty and involution. ARID3A knockdown and gene activation showed that ARID3A stimulated the synthesis of triglycerides and cholesterol in HC11 cells, secretion of free fatty acids from cells and lipid droplet formation in cells. ARID3A also promoted the expression and maturation of SREBP1 in HC11 cells. PA stimulated ARID3A protein expression and SREBP1 expression and maturation in a dose-dependent manner, and the PI3K specific inhibitor LY294002 blocked the stimulation of PA on ARID3A expression. ARID3A knockdown blocked the stimulation of PA on SREBP1 protein expression and maturation. We further showed that ARID3A was localized in the nucleus and PA stimulated this localization, and ARID3A knockdown blocked the stimulation of PA on the mRNA expression of SREBP1. To sum up, our data reveal that ARID3A is a key mediator for PA to promote SREBP1 mRNA expression and stimulate milk fat synthesis in mammary epithelial cells.

PAUPAR and PAX6 sequentially regulate human embryonic stem cell cortical differentiation.

Long noncoding RNAs (lncRNAs) play a wide range of roles in the epigenetic regulation of crucial biological processes, but the functions of lncRNAs in cortical development are poorly understood. Using human embryonic stem cell (hESC)-based 2D neural differentiation approach and 3D cerebral organoid system, we identified that the lncRNA PAUPAR, which is adjacent to PAX6, plays essential roles in cortical differentiation by interacting with PAX6 to regulate the expression of a large number of neural genes. Mechanistic studies showed that PAUPAR confers PAX6 proper binding sites on the target neural genes by directly binding the genomic regions of these genes. Moreover, PAX6 recruits the histone methyltransferase NSD1 through its C-terminal PST enrichment domain, then regulate H3K36 methylation and the expression of target genes. Collectively, our data reveal that the PAUPAR/PAX6/NSD1 complex plays a critical role in the epigenetic regulation of hESC cortical differentiation and highlight the importance of PAUPAR as an intrinsic regulator of cortical differentiation.

Met stimulates ARID1A degradation and activation of the PI3K-SREBP1 signaling to promote milk fat synthesis in bovine mammary epithelial cells.

Methionine (Met) can promote milk fat synthesis in bovine mammary epithelial cells (BMECs), but the potential molecular mechanism is largely unknown. In this report, we aim to explore the role and molecular mechanism of AT-rich interaction domain 1A (ARID1A) in milk fat synthesis stimulated by Met. ARID1A knockdown and activation indicated that ARID1A negatively regulated the synthesis of triglycerides, cholesterol and free fatty acids and the formation of lipid droplets in BMECs. ARID1A also negatively regulated the phosphorylation of PI3K and AKT proteins, as well as the expression and maturation of SREBP1. Met stimulated the phosphorylation of PI3K and AKT proteins, as well as the expression and maturation of SREBP1, while ARID1A gene activation blocked the stimulatory effects of Met. We further found that ARID1A was located in the nucleus of BMECs, and Met reduced the nuclear localization and expression of ARID1A. ARID1A gene activation blocked the stimulation of PI3K and SREBP1 mRNA expression by Met. In summary, our data suggests that ARID1A negatively regulates milk fat synthesis stimulated by Met in BMECs through inhibiting the PI3K-SREBP1 signaling pathway, which may provide some new perspectives for improving milk fat synthesis.

Neonatal Plasma Exosomes Contribute to Endothelial Cell-Mediated Angiogenesis and Cardiac Repair after Acute Myocardial Infarction.

Acute myocardial infarction (AMI) accompanied by cardiac remodeling still lacks effective treatment to date. Accumulated evidences suggest that exosomes from various sources play a cardioprotective and regenerative role in heart repair, but their effects and mechanisms remain intricate. Here, we found that intramyocardial delivery of plasma exosomes from neonatal mice (npEXO) could help to repair the adult heart in structure and function after AMI. In-depth proteome and single-cell transcriptome analyses suggested that npEXO ligands were majorly received by cardiac endothelial cells (ECs), and npEXO-mediated angiogenesis might serve as a pivotal reason to ameliorate the infarcted adult heart. We then innovatively constructed systematical communication networks among exosomal ligands and cardiac ECs and the final 48 ligand-receptor pairs contained 28 npEXO ligands (including the angiogenic factors, Clu and Hspg2), which mainly mediated the pro-angiogenic effect of npEXO by recognizing five cardiac EC receptors (Kdr, Scarb1, Cd36, etc.). Together, the proposed ligand-receptor network in our study might provide inspiration for rebuilding the vascular network and cardiac regeneration post-MI.

Preparation and Application of Amino-Terminated Hyperbranched Magnetic Composites in High-Turbidity Water Treatment.

In order to separate the colloidal in high-turbidity water, a kind of magnetic composite (Fe3O4/HBPN) was prepared via the functional assembly of Fe3O4 and an amino-terminal hyperbranched polymer (HBPN). The physical and chemical characteristics of Fe3O4@HBPN were investigated by different means. The Fourier Transform infrared spectroscopy (FTIR) spectra showed that the characteristic absorption peaks positioned at 1110 cm-1, 1468 cm-1, 1570 cm-1 and 1641 cm-1 were ascribed to C-N, H-N-C, N-H and C=O bonds, respectively. The shape and size of Fe3O4/HBPN showed a different and uneven distribution; the particles clumped together and were coated with an oil-like film. Energy-dispersive spectroscopy (EDS) displayed that the main elements of Fe3O4/HBPN were C, N, O, and Fe. The superparamagnetic properties and good magnetic response were revealed by vibrating sample magnetometer (VSM) analysis. The characteristic diffraction peaks of Fe3O4/HBPN were observed at 2θ = 30.01 (220), 35.70 (311), 43.01 (400), 56.82 (511), and 62.32 (440), which indicated that the intrinsic phase of magnetite remained. The zeta potential measurement indicated that the surface charge of Fe3O4/HBPN was positive in the pH range 4-10. The mass loss of Fe3O4/HBPN in thermogravimetric analysis (TGA) proved thermal decomposition. The -C-NH2 or -C-NH perssad of HBPN were linked and loaded with Fe3O4 particles by the N-O bonds. When the Fe3O4/HBPN dosage was 2.5 mg/L, pH = 4-5, the kaolin concentration of 1.0 g/L and the magnetic field of 3800 G were the preferred reaction conditions. In addition, a removal efficiency of at least 86% was reached for the actual water treatment. Fe3O4/HBPN was recycled after the first application and reused five times. The recycling efficiency and removal efficiency both showed no significant difference five times (p > 0.05), and the values were between 84.8% and 86.9%.