Irradiated and CCl4 -treated bone marrow-derived liver macrophages exhibit different gene expression patterns and phenotypes.

Myeloid cells infiltrate into the liver and differentiate into macrophages in different liver injury mouse models. However, the heterogeneity of bone marrow (BM)-derived LMs populations remains to be understood. To investigate this and understand the impact of the macrophage niche on the properties of recruited BM-derived macrophages, we used a non-myeloablation BM transplantation model to label and trace BM-derived LMs. Subsequently, we quantified the number of embryonic-derived liver-resident macrophages, BM-derived LMs and total LMs in CCl4 and irradiated acute liver injury mouse models, respectively. Finally, we compared the cell fate, gene expression patterns, chemokine signals, and surface markers of irradiated and CCl4 -treated BM-derived LMs. We observed that, as compared to CCl4, radiation generated a macrophage niche by depleting embryonic-derived liver-resident macrophages and induced the recruitment of BM-derived LMs that further settled in the liver. Irradiated and CCl4 -treated BM-derived LMs are different with respect to their cell fates, gene expression patterns, and chemokine expression and recruitment. They also have different surface markers shortly after differentiating from their progenitors. Our findings suggest that irradiated and CCl4 -treated LM populations derived from the bone marrow display different patterns of gene expression and phenotypes; these differences may be due to the availability of macrophage niche.

Targeting Endothelial Erk1/2-Akt Axis as a Regeneration Strategy to Bypass Fibrosis during Chronic Liver Injury in Mice.

Liver sinusoidal endothelial cells (LSECs) have great capacity for liver regeneration, and this capacity can easily switch to profibrotic phenotype, which is still poorly understood. In this study, we elucidated a potential target in LSECs for regenerative treatment that can bypass fibrosis during chronic liver injury. Proregenerative LSECs can be transformed to profibrotic phenotype after 4 weeks of carbon tetrachloride administration or 10 days of bile duct ligation. This phenotypic alternation of LSECs was mediated by extracellular regulated protein kinases 1 and 2 (Erk1/2)-Akt axis switch in LSECs during chronic liver injury; Erk1/2 was normally associated with maintenance of the LSEC proregenerative phenotype, inhibiting hepatic stellate cell (HSC) activation and promoting tissue repair by enhancing nitric oxide (NO)/reactive oxygen species (ROS) ratio and increasing expression of hepatic growth factor (HGF) and Wingless-type MMTV integration site family member 2 (Wnt2). Alternatively, Akt induced LSEC profibrotic phenotype, which mainly stimulated HSC activation and concomitant senescence by reducing NO/ROS ratio and decreasing HGF/Wnt2 expression. LSEC-targeted adenovirus or drug particle to promote Erk1/2 activity can alleviate liver fibrosis, accelerate fibrosis resolution, and enhance liver regeneration. This study demonstrated that the Erk1/2-Akt axis acted as a switch to regulate the proregenerative and profibrotic phenotypes of LSECs, and targeted therapy promoted liver regeneration while bypassing fibrosis, providing clues for a more effective treatment of liver diseases.

Predicting drug-disease associations by using similarity constrained matrix factorization.

BACKGROUND: Drug-disease associations provide important information for the drug discovery. Wet experiments that identify drug-disease associations are time-consuming and expensive. However, many drug-disease associations are still unobserved or unknown. The development of computational methods for predicting unobserved drug-disease associations is an important and urgent task. RESULTS: In this paper, we proposed a similarity constrained matrix factorization method for the drug-disease association prediction (SCMFDD), which makes use of known drug-disease associations, drug features and disease semantic information. SCMFDD projects the drug-disease association relationship into two low-rank spaces, which uncover latent features for drugs and diseases, and then introduces drug feature-based similarities and disease semantic similarity as constraints for drugs and diseases in low-rank spaces. Different from the classic matrix factorization technique, SCMFDD takes the biological context of the problem into account. In computational experiments, the proposed method can produce high-accuracy performances on benchmark datasets, and outperform existing state-of-the-art prediction methods when evaluated by five-fold cross validation and independent testing. CONCLUSION: We developed a user-friendly web server by using known associations collected from the CTD database, available at http://www.bioinfotech.cn/SCMFDD/ . The case studies show that the server can find out novel associations, which are not included in the CTD database.

TiO2 with Tandem Fractionation (TAFT): An Approach for Rapid, Deep, Reproducible, and High-Throughput Phosphoproteome Analysis.

Mass-spectrometry-based phosphoproteomic workflows traditionally require efficient prefractionation and enrichment of phosphopeptides to gain an in-depth, global, and unbiased systematic investigation of phosphoproteome. Here we present TiO2 with tandem fractionation (TAFT) approach, which combines titanium dioxide (TiO2) enrichment and tandem high-pH reverse-phase (HpRP) for phosphoproteome analysis in a high-throughput manner; the entire workflow takes only 3 h to complete without laborious phosphopeptide preparation. We applied this approach to HeLa and HepG2.2.15 cells to characterize the capability of TAFT approach, which enables deep identification and quantification of more than 14 000 unique phosphopeptides in a single sample from 1 mg of protein as starting materials in <4 h of MS measurement. In total, we identified and quantified 21 281 phosphosites in two cell lines with >91% selectivity and high quantitative reproducibility (average Pearson correlation is 0.90 between biological replicates). More generally, the presented approach enables rapid, deep, and reproducible phosphoproteome analysis in a high-throughput manner with low cost, which should facilitate our understanding of signaling networks in a wide range of biological systems or the process of clinical applications.

Regulation of Tak1 alternative splicing by splice-switching oligonucleotides.

Alternative splicing (AS) generates multiple isoforms from a single precursor mRNA, and these isoforms usually exhibit different tissue distributions and functions. Aberrant protein isoforms can lead to abnormalities in protein function and may even result in genetic disorders or cancer. In recent years, splice-switching oligonucleotides (SSOs) have emerged as a promising therapeutic strategy for several neurological diseases, but the efficacy of this strategy in other organs is less reported. In this study, we designed and synthesized SSOs targeting the splicing regulators of exon 12 of the Tak1 gene, inducing variant switching between Tak1-A and Tak1-B. We also designed SSOs capable of knockdown both Tak1 variants by inducing the aberrant splicing of exon 4. The Vivo-morpholino SSOs showed significant splice-switching of Tak1 in mouse liver, with a persistence of at least 10 days after initial SSOs delivery. Bioinformatics analysis indicated a lipid metabolism-related function for Tak1-B but not Tak1-A. The conversion of Tak1-B to Tak1-A consistently led to significant accumulation of lipids in cultured AML12 cells, as well as the dysregulation of several lipid metabolism-related genes in mouse liver. Different functional properties of the two isoforms may explain the conflicting functions previously reported for Tak1. In conclusion, our research clarified the different functions of Tak1 isoforms, and provided an efficient strategy for the functional research of the AS isoforms.

Mobile Platform for Multiplexed Detection and Differentiation of Disease-Specific Nucleic Acid Sequences, Using Microfluidic Loop-Mediated Isothermal Amplification and Smartphone Detection.

New tools are needed to enable rapid detection, identification, and reporting of infectious viral and microbial pathogens in a wide variety of point-of-care applications that impact human and animal health. We report the design, construction, and characterization of a platform for multiplexed analysis of disease-specific DNA sequences that utilizes a smartphone camera as the sensor in conjunction with a hand-held "cradle" that interfaces the phone with a silicon-based microfluidic chip embedded within a credit-card-sized cartridge. Utilizing specific nucleic acid sequences for four equine respiratory pathogens as representative examples, we demonstrated the ability of the system to utilize a single 15 µL droplet of test sample to perform selective positive/negative determination of target sequences, including integrated experimental controls, in approximately 30 min. Our approach utilizes loop-mediated isothermal amplification (LAMP) reagents predeposited into distinct lanes of the microfluidic chip, which when exposed to target nucleic acid sequences from the test sample, generates fluorescent products that when excited by appropriately selected light emitting diodes (LEDs), are visualized and automatically analyzed by a software application running on the smartphone microprocessor. The system achieves detection limits comparable to those obtained by laboratory-based methods and instruments. Assay information is combined with the information from the cartridge and the patient to populate a cloud-based database for epidemiological reporting of test results.

Discovery of novel genes and gene isoforms by integrating transcriptomic and proteomic profiling from mouse liver.

Comprehensively identifying gene expression in both transcriptomic and proteomic levels of one tissue is a prerequisite for a deeper understanding of its biological functions. Alternative splicing and RNA editing, two main forms of transcriptional processing, play important roles in transcriptome and proteome diversity and result in multiple isoforms for one gene, which are hard to identify by mass spectrometry (MS)-based proteomics approach due to the relative lack of isoform information in standard protein databases. In our study, we employed MS and RNA-Seq in parallel into mouse liver tissue and captured a considerable catalogue of both transcripts and proteins that, respectively, covered 60 and 34% of protein-coding genes in Ensembl. We then developed a bioinformatics workflow for building a customized protein database that for the first time included new splicing-derived peptides and RNA-editing-caused peptide variants, allowing us to more completely identify protein isoforms. Using this experimentally determined database, we totally identified 150 peptides not present in standard biological databases at false discovery rate of <1%, corresponding to 72 novel splicing isoforms, 43 new genetic regions, and 15 RNA-editing sites. Of these, 11 randomly selected novel events passed experimental verification by PCR and Sanger sequencing. New discoveries of gene products with high confidence in two omics levels demonstrated the robustness and effectiveness of our approach and its potential application into improve genome annotation. All the MS data have been deposited to the iProx ( http://ww.iprox.org ) with the identifier IPX00003601.

Investigation of the causal association between Parkinson's disease and autoimmune disorders: a bidirectional Mendelian randomization study.

Background: To date, an increasing number of epidemiological evidence has pointed to potential relationships between Parkinson's disease (PD) and various autoimmune diseases (AIDs), however, no definitive conclusions has been drawn about whether PD is causally related to AIDs risk. Methods: By employing summary statistics from the latest and most extensive genome-wide association studies (GWAS), we performed a bidirectional two-sample Mendelian randomization (MR) analysis to investigate the causal associations between PD and a variety of 17 AIDs, encompassing multiple sclerosis, neuromyelitis optica spectrum disorder, myasthenia gravis, asthma, inflammatory bowel disease, Crohn's disease, ulcerative colitis, irritable bowel syndrome, celiac disease, primary biliary cirrhosis, primary sclerosing cholangitis, type 1 diabetes, ankylosing spondylitis, rheumatoid arthritis, systemic lupus erythematosus, psoriasis and vitiligo. Inverse-variance weighted (IVW) was adopted as the main statistical approach to obtain the causal estimates of PD on different AIDs, supplemented by a series of complementary analyses (weighted median, MR Egger regression, and MR-PRESSO) for further strengthening the robustness of results. Results: Our MR findings suggested that genetically predicted higher liability to PD was causally associated with a decreased risk of irritable bowel syndrome (OR = 0.98; 95% CI: 0.96-0.99; P = 0.032). On the contrary, IVW analysis showed a potential positive correlation between genetically determined PD and the incidence of type 1 diabetes (OR = 1.10; 95%CI: 1.02-1.19; P = 0.010). Subsequent MR tests ended up in similar results, confirming our findings were reliable. Additionally, in the reverse MR analyses, we did not identify any evidence to support the causal relationship of genetic predisposition to AIDs with PD susceptibility. Conclusion: In general, a bifunctional role that PD exerted on the risk of developing AIDs was detected in our studies, both protecting against irritable bowel syndrome occurrence and raising the incidence of type 1 diabetes. Future studies, including population-based observational studies and molecular experiments in vitro and in vivo, are warranted to validate the results of our MR analyses and refine the underlying pathological mechanisms involved in PD-AIDs associations.

Proteomic analysis of DEN and CCl4-induced hepatocellular carcinoma mouse model.

Hepatocellular carcinoma (HCC) seriously threatens human health, mostly developed from liver fibrosis or cirrhosis. Since diethylnitrosamine (DEN) and carbon tetrachloride (CCl4)-induced HCC mouse model almost recapitulates the characteristic of HCC with fibrosis and inflammation, it is taken as an essential tool to investigate the pathogenesis of HCC. However, a comprehensive understanding of the protein expression profile of this model is little. In this study, we performed proteomic analysis of this model to elucidate its proteomic characteristics. Compared with normal liver tissues, 432 differentially expressed proteins (DEPs) were identified in tumor tissues, among which 365 were up-regulated and 67 were down-regulated. Through Gene Ontology (GO) analysis, Ingenuity Pathway Analysis (IPA), protein-protein interaction networks (PPI) analysis and Gene-set enrichment analysis (GSEA) analysis of DEPs, we identified two distinguishing features of DEN and CCl4-induced HCC mouse model in protein expression, the upregulation of actin cytoskeleton and branched-chain amino acids metabolic reprogramming. In addition, matching DEPs from the mouse model to homologous proteins in the human HCC cohort revealed that the DEN and CCl4-induced HCC mouse model was relatively similar to the subtype of HCC with poor prognosis. Finally, combining clinical information from the HCC cohort, we screened seven proteins with prognostic significance, SMAD2, PTPN1, PCNA, MTHFD1L, MBOAT7, FABP5, and AGRN. Overall, we provided proteomic data of the DEN and CCl4-induced HCC mouse model and highlighted the important proteins and pathways in it, contributing to the rational application of this model in HCC research.

Repopulating Kupffer cells originate directly from hematopoietic stem cells.

BACKGROUND: Kupffer cells (KCs) originate from yolk-sac progenitors before birth. Throughout adulthood, they self-maintain independently from the input of circulating monocytes (MOs) at a steady state and are replenished within 2 weeks after having been depleted, but the origin of repopulating KCs in adults remains unclear. The current paradigm dictates that repopulating KCs originate from preexisting KCs or monocytes, but there remains a lack of fate-mapping evidence. METHODS: We first traced the fate of preexisting KCs and that of monocytic cells with tissue-resident macrophage-specific and monocytic cell-specific fate-mapping mouse models, respectively. Secondly, we performed genetic lineage tracing to determine the type of progenitor cells involved in response to KC-depletion in mice. Finally, we traced the fate of hematopoietic stem cells (HSCs) in an HSC-specific fate-mapping mouse model, in the context of chronic liver inflammation induced by repeated carbon tetrachloride treatment. RESULTS: By using fate-mapping mouse models, we found no evidence that repopulating KCs originate from preexisting KCs or MOs and found that in response to KC-depletion, HSCs proliferated in the bone marrow, mobilized into the blood, adoptively transferred into the liver and differentiated into KCs. Then, in the chronic liver inflammation context, we confirmed that repopulating KCs originated directly from HSCs. CONCLUSION: Taken together, these findings provided in vivo fate-mapping evidence that repopulating KCs originate directly from HSCs, which presents a completely novel understanding of the cellular origin of repopulating KCs and shedding light on the divergent roles of KCs in liver homeostasis and diseases.

Sample preparation method for isolation of single-cell types from mouse liver for proteomic studies.

It becomes increasingly clear that separation of pure cell populations provides a uniquely sensitive and accurate approach to protein profiling in biological systems and opens up a new area for proteomic analysis. The method we described could simultaneously isolate population of hepatocytes (HCs), hepatic stellate cells (HSCs), Kupffer cells (KCs) and liver sinusoidal endothelial cells (LSECs) by a combination of collagenase-based density gradient centrifugation and magnetic activated cell sorting with high purity and yield for the first time. More than 98% of the isolated HCs were positive for cytokeratin 18, with a viability of 91%. Approximately 97% of the isolated HSCs expressed glial fibrillary acidic protein with a viability of 95%. Nearly 98% of isolated KCs expressed F4/80 with a viability of 94%. And the purity of LSECs reached up to 91% with a viability of 94%. And yield for HCs, HSCs, LSECs and KCs were 6.3, 1.3, 2.6 and 5.0 million per mouse. This systematic isolation method enables us to study the proteome profiling of different types of liver cells with high purity and yield, which is especially useful for sample preparation of Human Liver Proteome Project.

Efficacy and safety of retention enema with traditional Chinese medicine for ulcerative colitis: A meta-analysis of randomized controlled trials.

OBJECTIVE: To assess the efficacy and safety of retention enema with traditional Chinese medicine (TCM) for ulcerative colitis (UC) through a meta-analysis of published studies. METHODS: Literatures were retrieved from five electronic databases. Quality evaluation and meta-analysis were respectively conducted using the Cochrane collaboration and RevMan5.3. Overall quality of evidence was evaluated using GRADE system. Effect sizes were pooled using random effect models. RESULTS: Seventeen RCTs were included. Compared with routine pharmacotherapies (RPs), TCM enema exhibited a statistically significant difference in clinical efficacy and reduction of the recurrence rate. The results of qualitative description for other endpoints, such as improvements in anabrosis, ulcer, diarrhea, and hematochezia, suggested that TCM enema had better efficacy than RPs. Furthermore, the incidence of side effects in TCM was lower than that in RPs. CONCLUSION: This meta-analysis confirmed the efficacy and safety of TCM enema for improving UC symptoms. However, further well-designed researches are needed.

Platinum nanoparticles on defect-rich nitrogen-doped hollow carbon as an efficient electrocatalyst for hydrogen evolution reactions.

Design and synthesis of efficient electrocatalysts with low usage of precious metal and of high stability are essential for their practical applications in hydrogen evolution reactions. In this work, we synthesize an electrocatalyst through the deposition of platinum nanoparticles on defect-rich nitrogen-doped hollow carbon derived from surface-attached poly(4-vinylpyridine) monolayers. The platinum nanoparticles with an average diameter of about 1.8 nm are well dispersed on the outer surface of the pre-synthesized carbon material and the platinum loading is about 8.6 wt%. The mass activity of the as-synthesized catalyst under an overpotential of 55 mV is about 5.0 A mgPt -1, about 4.93 times higher than that of commercial Pt/C catalysts. Moreover, the synthesized catalyst is also more electrochemically stable than commercial Pt/C catalysts as evidenced by continuous cyclic voltammetry and chronoamperometric response measurements.

PY13FSI-Infiltrated SBA-15 as Nonflammable and High Ion-Conductive Ionogel Electrolytes for Quasi-Solid-State Sodium-Ion Batteries.

Exploring electrolytes of high safety is essential to pave the practical route for sodium-ion batteries (SIBs) toward their important applications in large-scale energy storage and power supplies. In this regard, ionogel electrolytes (IEs) have been highlighted owing to their high ionic conductivity, prominent electrochemical and thermal stability, and, more crucially, high interfacial wettability. However, present studies lack an understanding of the interaction of IEs, which determines the ion desolvation and migration. In this article, IEs comprising an SBA-15 host, an ionic liquid, sodium salt, and poly(vinylidene fluoride)-hexafluoro propylene (PVDF-HFP) have been proposed by mechanical ball milling and roller pressing. The component ratio has been optimized based on the balance between ionic conductivity and self-supporting capability of IEs. The optimal IEs showed sufficiently high ionic conductivity (2.48 × 10-3 S cm-1 at 30 °C), wide electrochemical window (up to 4.8 V vs Na+/Na), and high Na+ transference number (0.37). Due to the presence of SBA-15 and an ionic liquid, the IEs exhibited much improved thermal resistance than that of the conventional organic liquid electrolytes (OLEs). Furthermore, Fourier transform infrared (FT-IR) spectroscopy revealed the hydrogen bonding interaction between silanols and the dissolved salts, not only anchoring anions for immobilization but also promoting the dissociation of sodium salts. After being matched with the Na3V2(PO4)3 (NVP) cathode and metallic Na anode, the SIBs presented a specific discharge capacity of up to 110.7 mA h g-1 initially at room temperature with 92% capacity retention after 300 cycles. The improved safety and electrochemical performance provided insights into rationally regulating IEs and their interactions with the prospect of strengthening their practical applications in SIBs.

Polymer network-derived nitrogen/sulphur co-doped three-dimensionally interconnected hierarchically porous carbon for oxygen reduction, lithium-ion battery, and supercapacitor.

Rational design and simple synthesis of carbon-based materials with high electrocatalytic activity are essential for their practical applications in electrochemical energy conversion and storage devices. Herein, we report the synthesis of nitrogen, sulfur co-doped three-dimensional interconnected hierarchically porous carbon (NSHPC) by zinc acetate assisted pyrolysis of polymer networks. The thus-synthesized NSHPC has a specific surface area of 1057 cm2 g-1 with the coexistence of micro- and meso-pores. As metal-free electrocatalyst, the NSHPC exhibits a promising activity towards oxygen reduction reactions as evidenced by the slightly negative shift of half-wave potential compared with commercial Pt/C catalyst. The assembled lithium ion battery using NSHPC as anode delivers the reversible capacity of 740 and 470 mA h g-1 at current densities of 2 and 5 A g-1 without performance decay after 1000 charge-discharge cycles. Moreover, the assembled supercapacitor using NSHPC as electrode has the capacitance of 203 F g-1 at 1 A g-1.

The Counterion Effect of Imidazolium-Type Poly(ionic liquid) Brushes on Carbon Dioxide Adsorption.

Imidazolium-based poly(ionic liquid) brushes were attached to spherical silica nanoparticles bearing various functionalities by using a surface-initiated atom transfer radical polymerization ("grafting from" technique). A temperature-programmed desorption process was applied to evaluate and analyze the carbon dioxide adsorption performance of the synthesized polymer brushes. The confined structure of the surface-attached polymer chains facilitates gas transport and adsorption, leading to an enhanced adsorption capacity of carbon dioxide molecules compared with pure polymer powders. Temperature-programmed desorption profiles of the synthesized polymer brushes after carbon dioxide adsorption reveal that the substituent groups on the nitrogen atom at the 3-position of the imidazole ring, as well as the associated anions significantly affect the adsorption capacity of functionalized poly(ionic liquid) brushes. Of the tested samples, amine-functionalized poly(ionic liquid) brushes associated with hexafluorophosphate ions exhibit the highest carbon dioxide adsorption capacity of 2.56 mmol g-1 (112.64 mg g-1 ) at 25 °C under a carbon dioxide partial pressure of 0.2 bar.

Recent Advances in the Machine Learning-Based Drug-Target Interaction Prediction.

BACKGROUND: The identification of drug-target interactions is a crucial issue in drug discovery. In recent years, researchers have made great efforts on the drug-target interaction predictions, and developed databases, software and computational methods. RESULTS: In the paper, we review the recent advances in machine learning-based drug-target interaction prediction. First, we briefly introduce the datasets and data, and summarize features for drugs and targets which can be extracted from different data. Since drug-drug similarity and target-target similarity are important for many machine learning prediction models, we introduce how to calculate similarities based on data or features. Different machine learningbased drug-target interaction prediction methods can be proposed by using different features or information. Thus, we summarize, analyze and compare different machine learning-based prediction methods. CONCLUSION: This study provides the guide to the development of computational methods for the drug-target interaction prediction.

Identification and validation of alternative splicing isoforms as novel biomarker candidates in hepatocellular carcinoma.

Alternative splicing (AS) is a transcriptional regulation mechanism that participates in multiple aspects of cancer. The present study aimed to identify differential AS events from tumor and non­tumor samples and investigate the potential of AS as a source of candidate cancer diagnostic biomarkers. Deep RNA sequencing of three paired hepatocellular carcinoma (HCC) tumors and adjacent non­tumors was applied to identify AS events. RT­qPCR was performed on 45 HCC clinical samples to validate the splicing differences. The maximal information coefficient was first used to build an association between clinical features and AS changes. We identified 197 significantly differential skipped exon events, of which only 29% overlapped with the differentially expressed genes. The differentially spliced genes were mainly enriched in HCC­characterized biological processes and pathways, clearly separating tumors from non­tumors. We also validated the statistically significant splicing differences of three AS candidates (CEACAM1 exon 7, VPS29 exon 2 and ISOC2 exon 3). Furthermore, a clinicopathological analysis revealed that carcinoembryonic antigen­related cell adhesion molecule 1 (CEACAM1) exon 7 was significantly correlated with the survival time, and VPS29 exon 2 was associated with cell differentiation stages. In conclusion, the findings of the three AS candidates in the present study could be beneficial in HCC prognosis and new treatment strategies.

Ammonium Polyphosphate Intercalated Layered Double Hydroxide and Zinc Borate as Highly Efficient Flame Retardant Nanofillers for Polypropylene.

We found in our previous study that layered double hydroxides (LDHs) which undergo aqueous miscible organic solvent treatment (AMOST) can tune the hydrophobicity surface of LDHs to be hydrophobic, and then the solvent mixing method can be used to prepare polymer/LDH nanocomposites. However, flame retardant property is not very high if LDHs are only used. In this present work, ammonium polyphosphate (APP) intercalated LDHs and zinc borate (ZB) was incorporated into a polypropylene (PP) matrix using the solvent mixing method. The structures, morphologies, and performance of the composites were characterized carefully. The peak heat release rate (PHRR) reduction of PP containing 10 and 20 wt % APP-LDH reached 27% and 55%, respectively, which increased up to 63% compared with PP/CO3-LDH. After incorporating 2 wt % ZB in the PP/APP-LDH system, the flame retardant property was further improved. Polypropylene composites with 20 wt % APP-LDH and 2 wt % ZB showed a 58% PHRR reduction. In addition, thermogravimetric analyzer (TGA) results indicated that the addition of APP-LDH and ZB improved the temperature at 50% weight loss (T50%) and the char formation of the materials significantly.

The synergistic effect of layered double hydroxides with other flame retardant additives for polymer nanocomposites: a critical review.

Layered double hydroxides (LDHs) are a new type of inorganic flame retardant additive for polymer nanocomposites. Although their unique structural properties and tunable chemical compositions make them highly promising, it has been noticed that on their own, LDHs can hardly fulfill all the requirements for commercial applications. In recent years, the application of LDHs together with other synergistic additives has been proposed as a new route for obtaining highly efficient flame retardant polymer nanocomposites. It is believed that the synergistic additives can overcome the shortcomings of LDHs. As great progress has been made in this field so far, we believe that a timely review is warranted. Thus, in this contribution, the synergistic effect of LDHs with other flame retardant additives including (1) phosphorus-containing compounds, (2) graphene and carbon compounds, (3) intumescent flame retardants, (4) magnesium hydroxide, (5) borate-containing compounds, and (6) some other flame retardant compounds will be critically reviewed. For each type of additive, the synergistic mechanism with LDHs, and their performance on both flame retardancy and thermal stability will be discussed. We believe that this work will inspire and guide researchers from a wide range of backgrounds and help to pave the way for major breakthroughs in both fundamental studies and industrial applications in this field.