GADRP: graph convolutional networks and autoencoders for cancer drug response prediction.

Drug response prediction in cancer cell lines is of great significance in personalized medicine. In this study, we propose GADRP, a cancer drug response prediction model based on graph convolutional networks (GCNs) and autoencoders (AEs). We first use a stacked deep AE to extract low-dimensional representations from cell line features, and then construct a sparse drug cell line pair (DCP) network incorporating drug, cell line, and DCP similarity information. Later, initial residual and layer attention-based GCN (ILGCN) that can alleviate over-smoothing problem is utilized to learn DCP features. And finally, fully connected network is employed to make prediction. Benchmarking results demonstrate that GADRP can significantly improve prediction performance on all metrics compared with baselines on five datasets. Particularly, experiments of predictions of unknown DCP responses, drug-cancer tissue associations， and drug-pathway associations illustrate the predictive power of GADRP. All results highlight the effectiveness of GADRP in predicting drug responses, and its potential value in guiding anti-cancer drug selection.

An enhanced cascade-based deep forest model for drug combination prediction.

Combination therapy has shown an obvious curative effect on complex diseases, whereas the search space of drug combinations is too large to be validated experimentally even with high-throughput screens. With the increase of the number of drugs, artificial intelligence techniques, especially machine learning methods, have become applicable for the discovery of synergistic drug combinations to significantly reduce the experimental workload. In this study, in order to predict novel synergistic drug combinations in various cancer cell lines, the cell line-specific drug-induced gene expression profile (GP) is added as a new feature type to capture the cellular response of drugs and reveal the biological mechanism of synergistic effect. Then, an enhanced cascade-based deep forest regressor (EC-DFR) is innovatively presented to apply the new small-scale drug combination dataset involving chemical, physical and biological (GP) properties of drugs and cells. Verified by the dataset, EC-DFR outperforms two state-of-the-art deep neural network-based methods and several advanced classical machine learning algorithms. Biological experimental validation performed subsequently on a set of previously untested drug combinations further confirms the performance of EC-DFR. What is more prominent is that EC-DFR can distinguish the most important features, making it more interpretable. By evaluating the contribution of each feature type, GP feature contributes 82.40%, showing the cellular responses of drugs may play crucial roles in synergism prediction. The analysis based on the top contributing genes in GP further demonstrates some potential relationships between the transcriptomic levels of key genes under drug regulation and the synergism of drug combinations.

Machine learning methods, databases and tools for drug combination prediction.

Combination therapy has shown an obvious efficacy on complex diseases and can greatly reduce the development of drug resistance. However, even with high-throughput screens, experimental methods are insufficient to explore novel drug combinations. In order to reduce the search space of drug combinations, there is an urgent need to develop more efficient computational methods to predict novel drug combinations. In recent decades, more and more machine learning (ML) algorithms have been applied to improve the predictive performance. The object of this study is to introduce and discuss the recent applications of ML methods and the widely used databases in drug combination prediction. In this study, we first describe the concept and controversy of synergism between drug combinations. Then, we investigate various publicly available data resources and tools for prediction tasks. Next, ML methods including classic ML and deep learning methods applied in drug combination prediction are introduced. Finally, we summarize the challenges to ML methods in prediction tasks and provide a discussion on future work.

Computational methods, databases and tools for synthetic lethality prediction.

Synthetic lethality (SL) occurs between two genes when the inactivation of either gene alone has no effect on cell survival but the inactivation of both genes results in cell death. SL-based therapy has become one of the most promising targeted cancer therapies in the last decade as PARP inhibitors achieve great success in the clinic. The key point to exploiting SL-based cancer therapy is the identification of robust SL pairs. Although many wet-lab-based methods have been developed to screen SL pairs, known SL pairs are less than 0.1% of all potential pairs due to large number of human gene combinations. Computational prediction methods complement wet-lab-based methods to effectively reduce the search space of SL pairs. In this paper, we review the recent applications of computational methods and commonly used databases for SL prediction. First, we introduce the concept of SL and its screening methods. Second, various SL-related data resources are summarized. Then, computational methods including statistical-based methods, network-based methods, classical machine learning methods and deep learning methods for SL prediction are summarized. In particular, we elaborate on the negative sampling methods applied in these models. Next, representative tools for SL prediction are introduced. Finally, the challenges and future work for SL prediction are discussed.

DEML: Drug Synergy and Interaction Prediction Using Ensemble-Based Multi-Task Learning.

Synergistic drug combinations have demonstrated effective therapeutic effects in cancer treatment. Deep learning methods accelerate identification of novel drug combinations by reducing the search space. However, potential adverse drug-drug interactions (DDIs), which may increase the risks for combination therapy, cannot be detected by existing computational synergy prediction methods. We propose DEML, an ensemble-based multi-task neural network, for the simultaneous optimization of five synergy regression prediction tasks, synergy classification, and DDI classification tasks. DEML uses chemical and transcriptomics information as inputs. DEML adapts the novel hybrid ensemble layer structure to construct higher order representation using different perspectives. The task-specific fusion layer of DEML joins representations for each task using a gating mechanism. For the Loewe synergy prediction task, DEML overperforms the state-of-the-art synergy prediction method with an improvement of 7.8% and 13.2% for the root mean squared error and the R2 correlation coefficient. Owing to soft parameter sharing and ensemble learning, DEML alleviates the multi-task learning 'seesaw effect' problem and shows no performance loss on other tasks. DEML has a superior ability to predict drug pairs with high confidence and less adverse DDIs. DEML provides a promising way to guideline novel combination therapy strategies for cancer treatment.

NeRD: a multichannel neural network to predict cellular response of drugs by integrating multidimensional data.

BACKGROUND: Considering the heterogeneity of tumors, it is a key issue in precision medicine to predict the drug response of each individual. The accumulation of various types of drug informatics and multi-omics data facilitates the development of efficient models for drug response prediction. However, the selection of high-quality data sources and the design of suitable methods remain a challenge. METHODS: In this paper, we design NeRD, a multidimensional data integration model based on the PRISM drug response database, to predict the cellular response of drugs. Four feature extractors, including drug structure extractor (DSE), molecular fingerprint extractor (MFE), miRNA expression extractor (mEE), and copy number extractor (CNE), are designed for different types and dimensions of data. A fully connected network is used to fuse all features and make predictions. RESULTS: Experimental results demonstrate the effective integration of the global and local structural features of drugs, as well as the features of cell lines from different omics data. For all metrics tested on the PRISM database, NeRD surpassed previous approaches. We also verified that NeRD has strong reliability in the prediction results of new samples. Moreover, unlike other algorithms, when the amount of training data was reduced, NeRD maintained stable performance. CONCLUSIONS: NeRD's feature fusion provides a new idea for drug response prediction, which is of great significance for precise cancer treatment.

A non-translational role of threonyl-tRNA synthetase in regulating JNK signaling during myogenic differentiation.

Aminoacyl-tRNA synthetases (aaRSs) are house-keeping enzymes that are essential for protein synthesis. However, it has become increasingly evident that some aaRSs also have non-translational functions. Here we report the identification of a non-translational function of threonyl-tRNA synthetase (ThrRS) in myogenic differentiation. We find that ThrRS negatively regulates myoblast differentiation in vitro and injury-induced skeletal muscle regeneration in vivo. This function is independent of amino acid binding or aminoacylation activity of ThrRS, and knockdown of ThrRS leads to enhanced differentiation without affecting the global protein synthesis rate. Furthermore, we show that the non-catalytic new domains (UNE-T and TGS) of ThrRS are both necessary and sufficient for the myogenic function. In searching for a molecular mechanism of this new function, we find the kinase JNK to be a downstream target of ThrRS. Our data further reveal MEKK4 and MKK4 as upstream regulators of JNK in myogenesis and the MEKK4-MKK4-JNK pathway to be a mediator of the myogenic function of ThrRS. Finally, we show that ThrRS physically interacts with Axin1, disrupts Axin1-MEKK4 interaction and consequently inhibits JNK signaling. In conclusion, we uncover a non-translational function for ThrRS in the maintenance of homeostasis of skeletal myogenesis and identify the Axin1-MEKK4-MKK4-JNK signaling axis to be an immediate target of ThrRS action.

Talaromynoids A-E: Five New Fusicoccane Diterpenoids from the Endophytic Fungus Talaromyces sp. DC-26.

Talaromynoids A-E (1-5), five new fusicoccane diterpenoids, were obtained from the endophytic fungus Talaromyces sp. DC-26, which was isolated from a wild leech. Talaromynoid A (1) represents the first fusicoccane diterpenoid bearing an unexpected 5-7-5 tricyclic ring system, which is possibly derived from normal 5-8-5 ones by ring contraction. Talaromynoid E (5) is characterized by an unusual oxygen bridge between C-1 and C-8 that establishes the eight-membered ring B to be a 9-oxo-bicyclo[3.3.1]nonane. Structures of 1-5 with absolute configurations were determined by extensive NMR spectral analyses, electronic circular dichroism (ECD) calculations, X-ray diffraction analyses, and acid hydrolysis.

Pesimquinolones I-S, eleven new quinolone alkaloids produced by Penicillium simplicissimum and their inhibitory activity on NO production.

Eleven undescribed quinolone alkaloids, pesimquinolones I-S (1-4 and 6-12), as well as eleven known congeners (5 and 13-22), were isolated from the solid culture broth of the fungus Penicillium simplicissimum. Their chemical structures with absolute configurations were established by a combination of NMR spectroscopy, single-crystal X-ray crystallography, and modified Mosher's methods. Pesimquinolones I-K (1-3) represent the first examples of natural occurring quinolone alkaloids that possess a 6/6/6/6 tetracyclic ring system. The anti-inflammatory activities of selected compounds on LPS-induced nitric oxide (NO) production in adherent cells were evaluated. Compounds 1 and 2 showed suppressive effects on the production of NO, with IC50 values of 10.13 and 8.10 µM, respectively.

The regeneration of Acer rubrum L. "October Glory" through embryonic callus.

BACKGROUND: Tissue culture and rapid propagation technology is an important way to solve the difficulties of plant propagation. This experiment aims to explore the appropriate conditions at each stage of the red maple's tissue culture process and to obtain plantlets, thus providing a theoretical basis for the establishment of the red maple's tissue culture system. RESULTS: The results showed that the stem segment is the most suitable explant for inducing embryogenic callus. The MS (Murashige&Skoog) + 0.8 mg/L TDZ (Thidiazuron) + 1.0 mg/L 6-BA (6-Benzylaminopurine) + 0.5 mg/L IAA(Indole-3-acetic acid) + 35 g/L sucrose+ 7.5 g/L semi-fixed medium was the best for callus formation. When selecting type VI callus as embryonic callus induction material, MS + 0.6 mg/L TDZ + 0.5 mg/L 6-BA + 2.0 mg/L IAA + 35 g/L sucrose+ 7.5 g/L semi-fixed medium can get embryonic callus. The optimal medium for adventitious bud induction is MS + 1.0 mg/L TDZ + 3.0 mg/L 6-BA+ 0.2 mg/L NAA (1-Naphthaleneacetic acid) + 1.2 mg/L IAA + 35 g/L sucrose+ 7.5 g/L semi-fixed medium. The induction rate of adventitious roots in MS + 0.6 mg/L TDZ + 1.0 mg/L 6-BA+ 3 mg/L NAA + 35 g/L sucrose+ 7.5 g/L semi-fixed medium was the highest, reaching 76%. CONCLUSIONS: In the course of our research, we found that PGRs play an important role in the callus induction stage, and the effect of TDZ is particularly obvious; The callus cells grow and proliferate according to the "S" growth curve, and can be sub-cultured when the highest growth point is reached to maintain the rapid proliferation of the callus cells and to avoid inactivation of callus caused by tight niche.

Emeridones A-F, a Series of 3,5-Demethylorsellinic Acid-Based Meroterpenoids with Rearranged Skeletons from an Endophytic Fungus Emericella sp. TJ29.

Six new 3,5-demethylorsellinic acid-based meroterpenoids, emeridones A-F (1-6), and eight known analogues (7-14) were isolated from Emericella sp. TJ29. Their structures and absolute configurations were elucidated by comprehensive spectroscopic analyses, single-crystal X-ray diffraction experiments, and electronic circular dichroism calculations. Emeridone A (1) represents the first meroterpenoid featuring a unique rigid 6/6/5/6 tetracyclic carbon ring system with two additional lactone rings. Emeridones B and C (2 and 3) possess a 2,6-dioxabicyclo[2.2.1]heptane and a spiro[bicyclo[3.2.2]nonane-2,1'-cyclohexane] moiety, respectively, and both functionalities were found for the second time in meroterpenoids. These new compounds were evaluated for their cytotoxic activities against five human cancer cells, and compounds 2, 4, and 6 exhibited moderate cytotoxic activities, with IC50 values ranging from 8.19 to 18.80 µM.

Aggregation of ferrihydrite nanoparticles: Effects of pH, electrolytes,and organics.

To better understand the fate and transport of ferrihydrite nanoparticles (FNPs), which carry many contaminants in natural and engineered aquatic environments, the aggregation of FNPs was systematically investigated in this study. The pH isoelectric point (pHIEP), surface zeta potential, and particle size evolutions of FNPs were measured under varied aqueous conditions using dynamic light scattering (DLS). The influence of pH (5.0 ±â€¯0.1 and 7.0 ±â€¯0.1), ionic strength (IS), electrolytes (NaCl, CaCl2 and Na2SO4), and organics (humic acid, fulvic acid and CH3COONa) on the aggregation behaviors of FNPs were explored. Meanwhile, Derjaguin-Landau-Verwey-Overbeek (DLVO) theory was employed to better understand the controlling mechanisms of FNP aggregation. In the presence of sulfate, the surface charge of FNPs was neutralized under varied pH and ionic strength due to ion adsorption and FNPs phase transformation to schwertmannite based on FT-IR results. This phase transformation resulted in rapid aggregation in all water chemistries tested, whereas other salt species affected the aggregation primarily by ion adsorption and charge screening. Presence of increasing concentrations of the organic acids significantly shifted the pHIEP of FNPs (7.0 ±â€¯0.2) to lower pH (< 4.0) due to adsorption of organics on FNPs surfaces making them negatively charged. The adsorption of HA/FA inhibited FNP aggregation significantly while CH3COONa did not, due to different effects on steric and/or electrosteric interactions among FNPs by organics with varied pKa values and molecular weights. After accounting for the important effects of pH, electrolytes, and organics in modifying FNPs' surface charge, DLVO calculations agreed well with measured critical coagulation concentrations (CCC) values of FNPs at both pH 5.0 ±â€¯0.1 and 7.0 ±â€¯0.1 in the presence of NaCl. This study will hence be useful to better predict and control the fate and transport of FNPs in the presence of electrolytes and organics with different molecular weights, as well as the fate of the associated contaminants in natural and engineered systems.

Formation and Aggregation of Lead Phosphate Particles: Implications for Lead Immobilization in Water Supply Systems.

Phosphate is commonly added to drinking water to inhibit lead release from lead service lines and lead-containing materials in premise plumbing. Phosphate addition promotes the formation of lead phosphate particles, and their aggregation behaviors may affect their transport in pipes. Here, lead phosphate formation and aggregation were studied under varied aqueous conditions typical of water supply systems. Under high aqueous PO4/Pb molar ratios (>1), phosphate adsorption made the particles more negatively charged. Therefore, enhanced stability of lead phosphate particles was observed, suggesting that although addition of excess phosphate can lower the dissolved lead concentrations in tap water, it may increase concentrations of particulate lead. Adsorption of divalent cations (Ca2+ and Mg2+) onto lead phosphate particles neutralized their negative surface charges and promoted their aggregation at pH 7, indicating that phosphate addition for lead immobilization may be more efficient in harder waters. The presence of natural organic matter (NOM, ≥ 0.05 mg C/L humic acid and ≥ 0.5 mg C/L fulvic acid) retarded particle aggregation at pH 7. Consequently, removal of organic carbon during water treatment to lower the formation of disinfection-byproducts (DBPs) may have the additional benefit of minimizing the mobility of lead-containing particles. This study provided insight into fundamental mechanisms controlling lead phosphate aggregation. Such understanding is helpful to understand the observed trends of total lead in water after phosphate addition in both field and pilot-scale lead pipe studies. Also, it can help optimize lead immobilization by better controlling the water chemistry during phosphate addition.

Cytochalasans Produced by the Coculture of Aspergillus flavipes and Chaetomium globosum.

The cocultivation of Aspergillus flavipes and Chaetomium globosum, rich sources of cytochalasans, on solid rice medium, resulted in the production of 13 new, highly oxygenated cytochalasans, aspochalasinols A-D (1-4) and oxichaetoglobosins A-I (5-13), as well as seven known compounds (14-20). Of these compounds, 13 is a novel cytochalasan with an unexpected 2-norindole group. The isolated compounds were characterized by NMR spectroscopy, single-crystal X-ray crystallography, and ECD experiments. Compounds 1-4 represent the first examples of Asp-type cytochalasans with C-12 hydroxy groups, which may be a result of the coculture, as hydroxylated Me-12 groups are frequently found in Chae-type cytochalasans from C. globosum. In addition, 5-10 are unusual cytochalasans with an oxygenated C-10. Interestingly, 13 is the first example of a naturally occurring cytochalasan possessing a uniquely degraded indole ring that is derived from chaetoglobosin W, with 11 and 12 both serving as its biosynthetic intermediates. In the coculture of A. flavipes and C. globosum, most of these cytochalasans are more functionalized than normal cytochalasans, and the underlying causes may attract substantial attention from synthetic biologists. The cytotoxicities against five human cancer cell lines (SW480, HL-60, A549, MCF-7, and SMMC-7721) and the immunomodulatory activities of these new compounds were evaluated in vitro.

Aqueous aggregation behavior of citric acid coated magnetite nanoparticles: Effects of pH, cations, anions, and humic acid.

Improving the colloidal stability of magnetite nanoparticles (MNPs) is essential for their successful applications. In this study, the surface zeta potential and particle size evolutions of citric acid coated magnetite nanoparticles (CA-MNPs) were measured under varied aqueous conditions using dynamic light scattering (DLS). The effects of pH (5.0-9.0), ionic strength (IS), cations (Na+ and Ca2+), anions (phosphate, sulfate, and chloride) and humic acid on the aggregation behaviors of CA-MNPs were explored. Compared with bare MNPs, the stability of CA-MNPs were greatly improved over the typical pH range of natural aquatic environments (pH = 5.0-9.0), as the coated CA-MNPs were highly negatively charged over the pH range due to the low pKa1 value (3.13) of citrate acid. CA-MNPs were more stable in the presence of monovalent cation (Na+) compared with divalent cation (Ca2+), as Ca2+ could neutralize the surface charge of MNPs more significantly than Na+. In the presence of anions, the surface charges of CA-MNPs became more negative, and the stability of CA-MNPs followed the order: in phosphate > sulfate > chloride. The observed aggregation trend could be explained by the differences in the valences of the anions and their adsorption behaviors onto CA-MNPs, which altered the surface charges of CA-MNPs. The measured critical coagulation concentrations (CCC) values of CA-MNPs in these electrolyte solutions agreed well with Derjaguin-Landau-Verwey-Overbeek (DLVO) calculations. With the addition of Humic acid (HA), the aggregation of CA-MNPs was inhibited in all electrolyte solutions even with the critical coagulation concentrations. This is due to the adsorption of HA onto CA-MNPs, which enhanced the electrostatic and steric repulsive forces between CA-MNPs. Considering the good stability of CA-MNPs in solutions with varied pH and electrolyte compositions, as well as with the easy synthesis of CA-MNPs and their non-toxicity, this study suggested CA coating as a good strategy to increase the stability of MNPs.

Omnidirectional Internal Fixation by Double Approaches for Treating Rüedi-Allgöwer Type III Pilon Fractures.

In the present study, we explored the effectiveness and complications of omnidirectional internal fixation using a double approach for treating Rüedi-Allgöwer type III pilon fractures. A retrospective analysis was performed of 19 cases of Rüedi-Allgöwer type III unilateral closed pilon fracture. With preoperative preparation and correct surgical timing, the reduction was performed using anteromedial and posterolateral approaches, and the fracture fragments were fixed by omnidirectional internal fixation. Imaging evaluation was performed using the Burwell-Charnley scoring system. The Johner-Wruhs scoring system was used to assess the functional status of the patients. A comprehensive evaluation of efficacy was performed using a 5-point Likert score. The complications were also recorded and analyzed. All patients were followed up for an average of 16.2 months. The operative incisions of 15 cases healed by primary intent and with delayed healing in 4. All patients had achieved bony union at an average of 16 weeks postoperatively. No deep infection, broken nail or withdrawn nail, exposed plate, or skin flap necrosis occurred. The Burwell-Charnley imaging evaluation showed that 14 patients had anatomic reduction of the articular surface and 5 had acceptable reduction. Using the Johner-Wruhs scoring system, the results were excellent for 8, good for 7, fair for 2, and poor for 2 patients; the combined rate of excellent and good results was 78.9%. The Likert score of efficacy self-reported by the patients was 3 to 4 points for 12 patients, 2 points for 4 patients, and 0 to 1 point for 3 patients. The Likert score of therapeutic efficacy reported by the physicians was 3 to 4 points for 10 patients, 2 points for 5 patients, and 0 to 1 point for 4 patients. Omnidirectional internal fixation using double approaches was an effective method to treat Rüedi-Allgöwer type III pilon fractures with satisfactory reduction and rigid fixation, good joint function recovery, and few complications.

Heterogeneous Nucleation and Growth of Barium Sulfate at Organic-Water Interfaces: Interplay between Surface Hydrophobicity and Ba(2+) Adsorption.

Barium sulfate (BaSO4) is a common scale-forming mineral in natural and engineered systems, yet the rates and mechanisms of heterogeneous BaSO4 nucleation are not understood. To address these, we created idealized interfaces on which to study heterogeneous nucleation rates and mechanisms, which also are good models for organic-water interfaces: self-assembled thin films terminated with different functional groups (i.e., -COOH, -SH, or mixed -SH & COOH) coated on glass slides. BaSO4 precipitation on coatings from Barite-supersaturated solutions (saturation index, SI, = 1.1) was investigated using grazing-incidence small-angle X-ray scattering. After reaction for 1 h, a little amount of BaSO4 formed on hydrophilic bare and -COOH coated glasses. Meanwhile, BaSO4 nucleation was significantly promoted on hydrophobic -SH and mixed -SH & COOH coatings. This is because substrate hydrophobicity likely affected the interfacial energy and hence thermodynamic favorability of heterogeneous nucleation. The heterogeneous BaSO4 nucleation and growth kinetics were found to be affected by the amount of Ba(2+) adsorption onto the substrate and incipient BaSO4 nuclei. The importance of Ba(2+) adsorption was further corroborated by the finding that precipitation rate increased under [Ba(2+)]/[SO4(2-)] concentration ratios >1. These observations suggest that thermodynamic favorability for nucleation is governed by substrate-water interfacial energy, while given favorable thermodynamics, the rate is governed by ion attachment to substrates and incipient nuclei.

Homogeneous and Heterogeneous (Fex, Cr1-x)(OH)3 Precipitation: Implications for Cr Sequestration.

The formation of (Fe, Cr)(OH)3 nanoparticles determines the fate of aqueous Cr in many aquatic environments. Using small-angle X-ray scattering, precipitation rates of (Fe, Cr)(OH)3 nanoparticles in solution and on quartz were quantified from 0.1 mM Fe(III) solutions containing 0-0.25 mM Cr(III) at pH = 3.7 ± 0.2. Concentration ratio of aqueous Cr(III)/Fe(III) controlled the chemical composition (x) of (Fex, Cr1-x)(OH)3 precipitates, solutions' supersaturation with respect to precipitates, and the surface charge of quartz. Therefore, the aqueous Cr(III)/Fe(III) ratio affected homogeneous (in solution) and heterogeneous (on quartz) precipitation rates of (Fex, Cr1-x)(OH)3 through different mechanisms. The sequestration mechanisms of Cr(III) in precipitates were also investigated. In solutions with high aqueous Cr(III)/Fe(III) ratios, surface enrichment of Cr(III) on the precipitates occurred, resulting in slower particle growth in solutions. From solutions with 0-0.1 mM Cr(III), the particles on quartz grew from 2 to 4 nm within 1 h. Interestingly, from solution with 0.25 mM Cr(III), particles of two distinct sizes (2 and 6 nm) formed on quartz, and their sizes remained unchanged throughout the reaction. Our study provided new insights on homogeneous and heterogeneous precipitation of (Fex, Cr1-x)(OH)3 nanoparticles, which can help determine the fate of Cr in aquatic environments.

Fe(III) hydroxide nucleation and growth on quartz in the presence of Cu(II), Pb(II), and Cr(III): metal hydrolysis and adsorption.

Fe(III) hydroxide nanoparticles are an essential carrier for aqueous heavy metals. Particularly, iron hydroxide precipitation on mineral surfaces can immobilize aqueous heavy metals. Here, we used grazing-incidence small-angle X-ray scattering (GISAXS) to quantify nucleation and growth of iron hydroxide on quartz in 0.1 mM Fe(NO3)3 solution in the presence of Na(+), Cu(2+), Pb(2+), or Cr(3+) at pH = 3.7 ± 0.1. In 30 min, the average radii of gyration (R(g)) of particles on quartz grew from around 2 to 6 nm in the presence of Na(+) and Cu(2+). Interestingly, the particle sizes remained 3.3 ± 0.3 nm in the presence of Pb(2+), and few particles formed in the presence of Cr(3+). Quartz crystal microbalance dissipation (QCM-D) measurements showed that only Cr(3+) adsorbed onto quartz, while Cu(2+) and Pb(2+) did not. Cr(3+) adsorption changed the surface charge of quartz from negative to positive, thus inhibiting the precipitation of positively charged iron hydroxide on quartz. Masses and compositions of the precipitates were also quantified. This study provided new insights on interactions among quartz, iron hydroxide, and metal ions. Such information is helpful not only for environmental remediation but also for the doping design of iron oxide catalysts.

Combinatorial Biosynthesis Creates a Novel Aglycone Polyether with High Potency and Low Side Effects Against Bladder Cancer.

Polyethers play a crucial role in the development of anticancer drugs. To enhance the anticancer efficacy and reduce the toxicity of these compounds, thereby advancing their application in cancer treatment, herein, guided by the structure-activity relationships of aglycone polyethers, novel aglycone polyethers are rationally redesigned with potentially improved efficacy and reduced toxicity against tumors. To realize the biosynthesis of the novel aglycone polyethers, the gene clusters and the post-polyketide synthase tailoring pathways for aglycone polyethers endusamycin and lenoremycin are identified and subjected to combinatorial biosynthesis studies, resulting in the creation of a novel aglycone polyether termed End-16, which demonstrates significant potential for treating bladder cancer (BLCA). End-16 demonstrates the ability to suppress the proliferation, migration, invasion, and cellular protrusions formation of BLCA cells, as well as induce cell cycle arrest in the G1 phase in vitro. Notably, End-16 exhibits superior inhibitory activity and fewer side effects against BLCA compared to the frontline anti-BLCA drug cisplatin in vivo, thereby warranting further preclinical studies. This study highlights the significant potential of integrating combinatorial biosynthesis strategies with rational design to create unnatural products with enhanced pharmacological properties.