Topography of histone H3-H4 interaction with the Hat1-Hat2 acetyltransferase complex.

Chaperones influence histone conformation and intermolecular interaction in multiprotein complexes, and the structures obtained with full-length histones often provide more accurate and comprehensive views. Here, our structure of the Hat1-Hat2 acetyltransferase complex bound to Asf1-H3-H4 shows that the core domains of H3 and H4 are involved in binding Hat1 and Hat2, and the N-terminal tail of H3 makes extensive interaction with Hat2. These findings expand the knowledge about histone-protein interaction and implicate a function of Hat2/RbAp46/48, which is a versatile histone chaperone found in many chromatin-associated complexes, in the passing of histones between chaperones.

A new approach to testing mediation of the microbiome at both the community and individual taxon levels.

MOTIVATION: Understanding whether and which microbes played a mediating role between an exposure and a disease outcome are essential for researchers to develop clinical interventions to treat the disease by modulating the microbes. Existing methods for mediation analysis of the microbiome are often limited to a global test of community-level mediation or selection of mediating microbes without control of the false discovery rate (FDR). Further, while the null hypothesis of no mediation at each microbe is a composite null that consists of three types of null, most existing methods treat the microbes as if they were all under the same type of null, leading to excessive false positive results. RESULTS: We propose a new approach based on inverse regression that regresses the microbiome data at each taxon on the exposure and the exposure-adjusted outcome. Then, the P-values for testing the coefficients are used to test mediation at both the community and individual taxon levels. This approach fits nicely into our Linear Decomposition Model (LDM) framework, so our new method LDM-med, implemented in the LDM framework, enjoys all the features of the LDM, e.g. allowing an arbitrary number of taxa to be tested simultaneously, supporting continuous, discrete, or multivariate exposures and outcomes (including survival outcomes), and so on. Using extensive simulations, we showed that LDM-med always preserved the FDR of testing individual taxa and had adequate sensitivity; LDM-med always controlled the type I error of the global test and had compelling power over existing methods. The flexibility of LDM-med for a variety of mediation analyses is illustrated by an application to a murine microbiome dataset, which identified several plausible mediating taxa. AVAILABILITY AND IMPLEMENTATION: Our new method has been added to our R package LDM, which is available on GitHub at https://github.com/yijuanhu/LDM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Decomposition of Al13 promoted by salicylic acid under acidic condition: Mechanism study by differential mass spectrometry method and DFT calculation.

Decomposition of the polycation Al13O4(OH)24(H2O)127+ (Al13) promoted by ligand is a vital subject to advance our understanding of natural and artificial occurrence and evolution of aluminum ions, especially in the case of acidic condition that dissolved Al3+ species can be released from the Al-bearing substances. However, the microscopic pathway of synchronous proton-promoted and ligand-promoted decomposition process for Al13 is still in the status of ambiguity. Herein, we applied differential mass spectrometry method and DFT calculation to study the initial detailed process of Al13 decomposition under the presence of proton and salicylic acid (H2Sal). Mass results showed that the mononuclear Al3+-H2Sal complexes dominated the resulting Al species, whereas the monodentate complex Al13HSal6+ was not observed in the spectra. The difference of decomposition levels between the ligand/Al ratio 0.2 and 0.5 cases revealed that proton and ligand performed synergistic effect in initial Al13 decomposition process, and the proton transfer determined the ring closure efficiency. The ring closure reaction is the prerequisite for the collapse of Al13 structure and detachment of the mononuclear complex. DFT calculations reveal that hydrogen bond plays an important role in inducing the formation of chelated complex accompanying proton transfer. Attachment of protons at the bridging OH- can elongate and weaken the critical bond between targeted Al3+ and µ4-O2- resulting from delocalization of electron pairs in the oxygen atom. These results demonstrate the detailed mechanism of Al13 composition promoted by ligand and proton, and provide significant understanding for further application and control of Al13.

Irisin: a new molecular marker and target in metabolic disorder.

Irisin is a newly discovered exercise-mediated myokine which regulates energy metabolism and has been the subject of much recent research. Irisin plays an important role in metabolic diseases making it a potential new target to combat obesity and its associated disorders, such as T2DM. However, the results of several recent studies investigating the effects of irisin have been controversial. The present review will introduce the discovery of irisin, the role of irisin in metabolic disorders, possible mechanisms, and unanswered questions for future research.

Head fat is a novel method of measuring metabolic disorder in Chinese obese patients.

BACKGROUND: Body adiposity, especially ectopic fat accumulation, has a range of metabolic and cardiovascular effects. The aim of this study was to investigate the association between head fat and metabolic values in Chinese obese patients. METHODS: Data of this cross-sectional study from 66 obese patients were collected. Fat distribution was measured by dual-energy X-ray absorptiometry, and data of body weight, body mass index (BMI), neck circumference (NC), waist circumference (WC), hip circumference (HC), visceral index, basal metabolism (BM), glucose metabolism, lipid levels, uric acid (UA) had been collected. RESULTS: 1) Head fat was significantly associated with BMI, WC, HC, visceral index, BM, total fat and total fat excluding head fat in both males and females (p<0.05). Head fat was positively correlated with upper limb fat, trunk fat, weight, fasting plasma C peptide, fasting plasma insulin and UA in women(p<0.05), and the association was not statistically significant in male (p>0.05). Head fat was positively corrected with NC in males (p<0.05) but not females (p>0.05). There was no significant correlation between head fat and fasting plasma glucose, total choleslerolemia, triglyceridemia, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol and free fat acid in either gender (p>0.05). 2) Receiver operating characteristic analysis showed that a head fat of 1925.6 g and a head fat of 1567.85 g were the best cut-off values to determine subjects with low high-density lipoprotein cholesterol and hyperuricemia respectively. CONCLUSIONS: Head fat accumulation was closely associated with increased body fat, hyperinsulinemia, hyperuricemia, and impared lipid profile, suggesting it might be used as an indicator for dyslipidemia and hyperuricemia.

Differential patterns of insulin secretion and sensitivity in patients with type 2 diabetes mellitus and nonalcoholic fatty liver disease versus patients with type 2 diabetes mellitus alone.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM) often coexist and have adverse outcomes. The aim of our study was to elucidate metabolic abnormalities in patients with DM-NAFLD versus those with T2DM alone. METHODS: Patients were divided into two groups: 26 T2DM patients with NAFLD and 26 gender-, age-, and body mass index-matched patients with T2DM alone. Patients took a 75-g oral glucose tolerance test (OGTT), which measured serum insulin and C-peptide (C-p) levels at baseline (0 min), 30 min, 60 min, and 120 min after glucose challenge. RESULTS: Patients with DM-NAFLD or T2DM alone had similar blood glucose levels. ß-cell hypersecretion was more obvious in patients with DM-NAFLD. In addition, fasting, early-phase, and late-phase C-peptide levels were significantly increased in patients with DM-NAFLD (ΔC-p 0-30 min, P < 0.05; Area Under the Curve (AUC) C-p/PG 30-120 min ratio, P < 0.01; and AUC C-p 30-120 min, P < 0.01). Hepatic and extrahepatic insulin resistance during the OGTT did not differ significantly between groups. Hepatic insulin sensitivity independently contributed to the early phase (0-30 min) of the OGTT in patients with T2DM and NAFLD, whereas a significant deficit in late insulin secretion independently contributed to the 30-120 min glucose status in patients with T2DM only. CONCLUSIONS: In patients with similar levels of insulin resistance and hyperglycemia, DM-NAFLD was associated with higher serum insulin levels than T2DM alone. Hyperinsulinemia is caused mainly by ß-cell hypersecretion. The present study demonstrates pathophysiological differences in mechanisms of insulin resistance in patients with DM-NAFLD versus T2DM alone.

Assessing intra- and inter-method agreement of functional data.

Modern medical devices are increasingly producing complex data that could offer deeper insights into physiological mechanisms of underlying diseases. One type of complex data that arises frequently in medical imaging studies is functional data, whose sampling unit is a smooth continuous function. In this work, with the goal of establishing the scientific validity of experiments involving modern medical imaging devices, we focus on the problem of evaluating reliability and reproducibility of multiple functional data that are measured on the same subjects by different methods (i.e. different technologies or raters). Specifically, we develop a series of intraclass correlation coefficient and concordance correlation coefficient indices that can assess intra-method, inter-method, and total (intra + inter) agreement based on multivariate multilevel functional data consisting of replicated functional data measurements produced by each of the different methods. For efficient estimation, the proposed indices are expressed using variance components of a multivariate multilevel functional mixed effect model, which can be smoothly estimated by functional principal component analysis. Extensive simulation studies are performed to assess the finite-sample properties of the estimators. The proposed method is applied to evaluate the reliability and reproducibility of renogram curves produced by a high-tech radionuclide image scan used to non-invasively detect kidney obstruction.

Nonalcoholic fatty liver disease: molecular pathways and therapeutic strategies.

Along with rising numbers of patients with metabolic syndrome, the prevalence of nonalcoholic fatty liver disease (NAFLD) has increased in proportion with the obesity epidemic. While there are no established treatments for NAFLD, current research is targeting new molecular mechanisms that underlie NAFLD and associated metabolic disorders. This review discusses some of these emerging molecular mechanisms and their therapeutic implications for the treatment of NAFLD. The basic research that has identified potential molecular targets for pharmacotherapy will be outlined.

Integrative analysis of microbial 16S gene and shotgun metagenomic sequencing data improves statistical efficiency.

Background: The most widely used technologies for profiling microbial communities are 16S marker-gene sequencing and shotgun metagenomic sequencing. Interestingly, many microbiome studies have performed both sequencing experiments on the same cohort of samples. The two sequencing datasets often reveal consistent patterns of microbial signatures, highlighting the potential for an integrative analysis to improve power of testing these signatures. However, differential experimental biases, partially overlapping samples, and differential library sizes pose tremendous challenges when combining the two datasets. Currently, researchers either discard one dataset entirely or use different datasets for different objectives. Methods: In this article, we introduce the first method of this kind, named Com-2seq, that combines the two sequencing datasets for testing differential abundance at the genus and community levels while overcoming these difficulties. The new method is based on our LOCOM model (Hu et al., 2022), which employs logistic regression for testing taxon differential abundance while remaining robust to experimental bias. To benchmark the performance of Com-2seq, we introduce two ad hoc approaches: applying LOCOM to pooled taxa count data and combining LOCOM p-values from analyzing each dataset separately. Results: Our simulation studies indicate that Com-2seq substantially improves statistical efficiency over analysis of either dataset alone and works better than the two ad hoc approaches. An application of Com-2seq to two real microbiome studies uncovered scientifically plausible findings that would have been missed by analyzing individual datasets. Conclusions: Com-2seq performs integrative analysis of 16S and metagenomic sequencing data, which improves statistical efficiency and has the potential to accelerate the search of microbial communities and taxa that are involved in human health and diseases.

Integrative analysis of microbial 16S gene and shotgun metagenomic sequencing data improves statistical efficiency.

The most widely used technologies for profiling microbial communities are 16S marker-gene sequencing and shotgun metagenomic sequencing. Interestingly, many microbiome studies have performed both sequencing experiments on the same cohort of samples. The two sequencing datasets often reveal consistent patterns of microbial signatures, highlighting the potential for an integrative analysis to improve power of testing these signatures. However, differential experimental biases, partially overlapping samples, and differential library sizes pose tremendous challenges when combining the two datasets. Currently, researchers either discard one dataset entirely or use different datasets for different objectives. In this article, we introduce the first method of this kind, named Com-2seq, that combines the two sequencing datasets for the objective of testing differential abundance at the genus and community levels while overcoming these difficulties. We demonstrate that Com-2seq substantially improves statistical efficiency over analysis of either dataset alone and works better than two ad hoc approaches.

Spiking neural networks fine-tuning for brain image segmentation.

Introduction: The field of machine learning has undergone a significant transformation with the progress of deep artificial neural networks (ANNs) and the growing accessibility of annotated data. ANNs usually require substantial power and memory usage to achieve optimal performance. Spiking neural networks (SNNs) have recently emerged as a low-power alternative to ANNs due to their sparsity nature. Despite their energy efficiency, SNNs are generally more difficult to be trained than ANNs. Methods: In this study, we propose a novel three-stage SNN training scheme designed specifically for segmenting human hippocampi from magnetic resonance images. Our training pipeline starts with optimizing an ANN to its maximum capacity, then employs a quick ANN-SNN conversion to initialize the corresponding spiking network. This is followed by spike-based backpropagation to fine-tune the converted SNN. In order to understand the reason behind performance decline in the converted SNNs, we conduct a set of experiments to investigate the output scaling issue. Furthermore, we explore the impact of binary and ternary representations in SNN networks and conduct an empirical evaluation of their performance through image classification and segmentation tasks. Results and discussion: By employing our hybrid training scheme, we observe significant advantages over both ANN-SNN conversion and direct SNN training solutions in terms of segmentation accuracy and training efficiency. Experimental results demonstrate the effectiveness of our model in achieving our design goals.

FGF receptor-mediated gene delivery using ligands coupled to PEI-ß-CyD.

A novel vector with high gene delivery efficiency and special cell-targeting ability was developed using a good strategy that utilized low-molecular-weight polyethylenimine (PEI; molecular weight: 600 KDa [PEI600]) crosslinked to ß-cyclodextrin (ß-CyD) via a facile synthetic route. Fibroblast growth factor receptors (FGFRs) are highly expressed in a variety of human cancer cells and are potential targets for cancer therapy. In this paper, CY11 peptides, which have been proven to combine especially with FGFRs on cell membranes were coupled to PEI-ß-CyD using N-succinimidyl-3-(2-pyridyldithio) propionate as a linker. The ratios of PEI600, ß-CyD, and peptide were calculated based on proton integral values obtained from the (1)H-NMR spectra of the resulting products. Electron microscope observations showed that CY11-PEI-ß-CyD can efficiently condense plasmid DNA (pDNA) into nanoparticles of about 200 nm, and MTT assays suggested the decreased toxicity of the polymer. Experiments on gene delivery efficiency in vitro showed that CY11-PEI-ß-CyD/pDNA polyplexes had significantly greater transgene activities than PEI-ß-CyD/pDNA in the COS-7 and HepG2 cells, which positively expressed FGFR, whereas no such effect was observed in the PC-3 cells, which negatively expressed FGFR. Our current research indicated that the synthesized nonviral vector shows improved gene delivery efficiency and targeting specificity in FGFR-positive cells.

Effects of tetracyclines on bones: an ambiguous question needs to be clarified.

Tetracyclines have been widely used in bone histomorphometry to label new bone formation and apposition rate. However, most studies of tetracyclines have also shown their strong inhibitory action on osteoclasts and their effects on osteoblast activities as well. To even obtain the in-depth understanding on this issue, we have reviewed related studies in "Pubmed" by searching the keywords "tetracyclines and osteoclast", "tetracyclines and osteoblast", which retrieved 118 and 162 related documents, respectively. Among these papers, some described the application of tetracyclines as fluorescent marker in bone histomorphometry, while others discussed their role in protection of bone metabolism partly through inhibiting osteoclastogenesis or bone resorption and through enhancing osteogenesis. Based on the above mentioned, it seems that tetracyclines used as bone labeling markers may affect the results of bone histomorphometry to some extent. To even confirm the effect of tetracyclines on bones cells (osteoblast, osteoclast) and in vivo bone remodeling, related research work has been performed in our research team which indicated quite different results in vivo and in vitro. Therefore, the influence of tetracyclines on bones may differ in terms of different conditions which need to be further elucidated.

Extension of PERMANOVA to Testing the Mediation Effect of the Microbiome.

Recently, we have seen a growing volume of evidence linking the microbiome and human diseases or clinical outcomes, as well as evidence linking the microbiome and environmental exposures. Now comes the time to assess whether the microbiome mediates the effects of exposures on the outcomes, which will enable researchers to develop interventions to modulate outcomes by modifying microbiome compositions. Use of distance matrices is a popular approach to analyzing complex microbiome data that are high-dimensional, sparse, and compositional. However, the existing distance-based methods for mediation analysis of microbiome data, MedTest and MODIMA, only work well in limited scenarios. PERMANOVA is currently the most commonly used distance-based method for testing microbiome associations. Using the idea of inverse regression, here we extend PERMANOVA to test microbiome-mediation effects by including both the exposure and the outcome as covariates and basing the test on the product of their F statistics. This extension of PERMANOVA, which we call PERMANOVA-med, naturally inherits all the flexible features of PERMANOVA, e.g., allowing adjustment of confounders, accommodating continuous, binary, and multivariate exposure and outcome variables including survival outcomes, and providing an omnibus test that combines the results from analyzing multiple distance matrices. Our extensive simulations indicated that PERMANOVA-med always controlled the type I error and had compelling power over MedTest and MODIMA. Frequently, MedTest had diminished power and MODIMA had inflated type I error. Using real data on melanoma immunotherapy response, we demonstrated the wide applicability of PERMANOVA-med through 16 different mediation analyses, only 6 of which could be performed by MedTest and 4 by MODIMA.

Low temperature decreased insecticidal protein contents of cotton and its physiological mechanism.

Low temperature delayed cotton growth, increased abscission of reproductive organs, and seriously reduced quality and yield. Moreover, failed or unstable performance of insecticidal resistance due to adverse environments have been reported. In order to study the impact of low temperature on the insecticidal protein contents at square stage in Bacillus Thuringenesis (Bt) transgenic cotton, different temperature regimes and durations were imposed on two Bt cotton cultivars, Sikang1 (the conventional cultivar, SK1) and Sikang3 (the hybrid cultivar, SK3). Low temperature stress exhibited a significant inhibitory effect on insecticidal protein expression in squares and leaves of Bt transgenic cotton plants, with insecticidal protein contents decreased up to 30% with decreasing temperature. In addition, the threshold temperature resulting in significant reduction of insecticidal protein contents symbolized a rising trend as stress duration extended, together with a greater reduction observed. Thus, at square stage, the detrimental influence of low temperature on Bt protein contents was closely related to the low temperature level and duration. The square Bt protein content was positively correlated with leaf Bt protein content, but was more sensitive to low temperature. Across the whole treatment duration in both years, square Bt protein level was significantly negatively correlated with malondialdehyde (MDA) contents, as well as the activities of catalase (CAT) and superoxide dismutase (SOD), indicating the negative effect of cold induced oxidative stress on Bt protein contents. The reduced Bt protein contents under low temperature were also related to altered N metabolism. Glutamate oxaloacetate transaminase (GOT) and glutamate pyruvate transaminase (GPT) activities, as well as soluble protein contents in squares reduced, and greater reduction was recorded with decreasing temperature. In contrast, the free amino acid contents, and peptidase and protease activities increased, and greater elevation was noted with decreasing temperature. These results suggested in Bt cotton production, it is necessary to be alert to low temperature disasters that may last for more than 24 hours and lower than 15-17°C during the square stage, which may lead to reduced insecticidal resistance causing serious economic losses.

Effect of different ionic liquids and organic solvents on the structural and physicochemical properties of cellulose-protein complexes extracted from Se-enriched peanut leaves.

Abundant cellulose and insoluble protein were contained in the Se-enriched peanut leaf residue, a by-product from leaf protein extraction. Ionic liquids (ILs) were used to extract the cellulose-protein complexes (CPCs) from Se-enriched peanut leaf residue. The effects of various ILs as extractants and organic solvents as regenerant on the physicochemical properties of CPCs were compared. The results showed that the yield of CPCs and recovery yield of [AMIM]Cl (1-allyl-3-methylimidazole chloride) were better than those of [BMIM]Cl (1-butyl-3-methylimidazolium chloride). Simultaneously, it could be seen from the infrared absorption peaks and secondary structure fitting results that [BMIM]Cl seemed stronger than [AMIM]Cl in destroying the secondary structure of CPCs. Scanning electron microscope (SEM) showed that the CPCs extracted by [BMIM]Cl were lamellate with holes on the surface, and the CPCs extracted by [AMIM]Cl were rough, almost without holes on the surface. Furthermore, the transmittance and tensile strength of the film which contained BA-CPC ([BMIM]Cl as extractant and acetonitrile as regenerant) film were better than those contained AA-CPC ([AMIM]Cl as extractant and acetonitrile as regenerant) film, which might be mainly because the types of ILs and regenerants affect the particle size of CPCs, thereby influencing the mechanical properties of the film.

Paeoniflorin-6'-o-benzene sulfonate ameliorates the progression of adjuvant-induced arthritis by inhibiting the interaction between Ahr and GRK2 of fibroblast-like synoviocytes.

Aryl hydrocarbon receptor (Ahr) is thought to be a crucial factor that regulates immune responses, which may be involved in the pathogenesis of autoimmune inflammation including rheumatoid arthritis (RA). The results of our group in recent years have shown that Paeoniflorin-6'-O-benzene sulfonate (code: CP-25), a novel ester derivative of paeoniflorin, has a good effect on improving RA animal models. However, whether the anti-arthritis effect of CP-25 is related to Ahr remains unclear. Here, we showed that CP-25 treatment ameliorated adjuvant-induced arthritis (AA), a rat model of RA, by inhibiting Ahr-related activities in fibroblasts like synoviocytes (FLS). AA rats were treated with CP-25 or paroxetine from days 17 to 33 after immunization. We showed that CP-25 alleviated arthritis symptoms and the pathological changes. Treatment with CP-25 decreased the expression of Ahr in the synovium of AA rats. CP-25 inhibited the expression of Ahr and the G protein-coupled receptor kinase 2 (GRK2) as well as the co-expression of GRK2 with Ahr in FLS of AA rats. Furthermore, CP-25 down-regulated the production of Kyn in FLS of AA rats. These results suggested that CP-25 may inhibit the expression and activation of Ahr. Besides, treatment with CP-25 reduced the proliferation and migration of MH7A caused by Ahr activation. In addition, we also demonstrated that CP-25 down-regulated the total and nuclear expression of Ahr and the expression of GRK2 in Kyn-treated MH7A. Moreover, the co-expression and co-localization of Ahr and GRK2in Kyn-treated MH7A were also repressed by CP-25. The data presented here demonstrated that CP-25 suppressed FLS dysfunction in rats with AA, which were associated with reduced Ahr activation and the interaction between Ahr and GRK2.

Pre-aggregation of Al13 in optimizing coagulation for removal of humic acid.

The effective removal of humic acid (HA) by coagulation has been extensively investigated for water treatments. However, the limitations of pH variation and excessive residual aluminum issues were still factors needed to be considered. In this study, to investigate the coagulation mechanism for removing HA by Al13 and optimize Al13 operation for removing HA, Al13 and preformed Al13 aggregates (Al13agg) were applied to remove HA at different pH conditions. The results showed that preformed Al13agg exhibited superior HA removal performance than Al13 due to its wide pH range and low residual Al level. During coagulation, Al13 and Al13agg interacted with HA in their original status, but the DSlope325-375 difference implied that the complexation capacity between HA and Al13agg was stronger than Al13. The new peaks of HPSEC representing larger molecular weight substances were formed under acidic and neutral conditions, which indicated that HA firstly aggregated into larger complexed molecules by interacting with Al13 or its hydrolysates and was subsequently removed by forming large flocs which was completely different from Al13agg situation. Therefore, the different coagulation mechanisms played the roles in HA removal for Al13 and Al13agg which were studied in this paper. It was believed that the complexation and charge neutralization effects dominated coagulation process for Al13 while sweep flocculation and adsorption coagulation were main driving force for Al13agg in HA removing. This work provides significant understanding of HA removal by Al13 and Al13agg coagulation, which can help to design and optimize the high efficiency coagulant based on Al polycations.

Formation of Al30 aggregates and its correlation to the coagulation effect.

Al30 is the polycation with the highest degree of polymerization and surface charge in the currently known structural aluminum species. It shows excellent coagulation performance in water treatment process, and has the characteristics of wide application range of pH and dosage. pH value is one of the most important factors affecting the aggregation and coagulation process of Al30, but the influence of Al30 aggregation reaction on its coagulation effect is still unclear. Therefore, this article reports the deprotonation and aggregation reaction of Al30 by adjusting the basicity (B) of the solution, particularly to further understand the coagulation mechanism of Al30 under different conditions. The results showed that in the base titration process, when B < 2.86 in 0.01 M Al30 solution as AlT (the concentration of total Al), deprotonation and preliminary aggregation mainly occurred; when B > 2.86, the size of Al30 aggregates (Al30agg) increased rapidly, forming gels and gradually transforming into Al(OH)3. In this process, in addition to the reduction of electrostatic repulsion induced by Al30 deprotonation, the oligomers generated by the partial dissociation of Al30 also play the role of bridging-connection. Under the experimental titration conditions, the Al30agg always maintained a positive zeta potential. In addition, Al30 can deprotonate and aggregate at lower pH, which is an important reason for its unique coagulation characteristics. The larger structure size of Al30 also made it easy to form branched aggregates, so that it can play an effective role in a wider dosage range without destabilization of colloids. This study gives an insight in the advancement of coagulants and promotes the industrial application and commercialization of functional coagulants based on polyaluminum.

Deprotonation and aggregation of Al13 under alkaline titration: A simulating study related to coagulation process.

Unraveling the transformation of coagulants and their interaction with contaminants at the micro-level is vital to advancing our understanding of the coagulation mechanism. To the best of our knowledge, the coagulation effectiveness of [AlO4Al12(OH)24(H2O)12]7+ (Al13), regarded as the dominant species in polyaluminum chloride (PACl), is highly related to its aggregation characteristic, but the detailed process of Al13 aggregation in coagulation time scale was not well studies. Here we systematically studied the deprotonation and aggregation processes of Al13 by alkaline titration to simulate the reaction in coagulation case. By reacting with OH-, Al13 can continuously lose protons regardless of pH until its positive charge was well neutralized. The initial Al13 aggregates (Al13agg) appeared at B of 2.70 and large Al13agg was generated by coalescence of small initial Al13agg. Most Al13 polycations kept their main structure unchanged during aggregation and part was decomposed into monomers or oligomers. Density functional theory (DFT) results reveal that Al13 becomes unstable after deprotonation, but the aggregation of Al13 bridged by Al monomers can stabilize the polycations. Al13 needs to be hydrolyzed before interacting with colloidal particles, but particles can promote the aggregation of Al13 by weakening the repulsion force between the polymers. Strong and compact flocs can be generated induced by in-situ aggregation of Al13 in neutral and alkaline conditions. This study can provide a deep understanding about the role of Al13agg in removing particles and instruct the development of new efficient coagulants against the various water qualities.