An effective magnetic nanobiocomposite: Preparation, characterization and its application for adsorption removal of P-nitroaniline from aquatic environments.

In this investigation, a magnetic nanobiocomposite, denoted as CoFe2O4/Activated Carbon integrated with Chitosan (CoFe2O4/AC@Ch), was synthesized based on a microwave-assisted for the efficacious adsorption of P-nitroaniline (PNA). The physicochemical properties of the said nano biocomposite were thoroughly characterized using a suite of analytical methodologies, namely FESEM/EDS, BET, FTIR, XRD, and VSM. The results confirm the successful synthesis of the nanobiocomposite, with its point of zero charge (pHZPC) determined to be 6.4. Adsorptive performance towards PNA was systematically examined over a spectrum of conditions, encompassing variations in PNA concentration (spanning 10-40 mg/L), adsorbent concentration (10-200 mg/L), contact periods (2.5-22.5 min), and solution pH (3-11). Upon optimization, the conditions converged to an adsorbent concentration of 200 mg/L, pH 5, PNA concentration of 10 mg/L, and a contact duration of 22.5 min, under which an impressive PNA adsorption efficacy of 98.6% was attained. Kinetic and isotherm analyses insinuated the adsorption mechanism to adhere predominantly to the pseudo-second-order kinetic and Langmuir isotherm models. The magnetic nanocomposite was recovered and used in 4 cycles, and the absorption rate reached 86%, which shows the good stability of the magnetic nanocomposite in wastewater treatment. Conclusively, these empirical outcomes underscore the viability of the formulated magnetic nanobiocomposite as a potent, recyclable adsorbent for the proficient extraction of PNA from aqueous matrices.

Ecological and Probabilistic Health Risk Assessment of Heavy Metals in Topsoils, Southeast of Iran.

This study aimed to assess ecological and health risk of heavy metals (HMs) in the 35 topsoils in southeastern Iran. Ecological and health risks were assessed based on the EPA method. The order of the HMs followed as: Zn > Cr>Cu>Pb>As>Cd. All samples, except As and Cu, had the moderate enrichment and low to moderate pollution, respectively. The As in both regions and Cu in the city was classified in the lack to minimal enrichment and no pollution category. The studied HMs in both regions were shown a low ecological risk. There was minimal possibility of adverse non-carcinogenic effects. The Cr and As had an acceptable or tolerable carcinogenic risk from ingestion route (ELCRing) in both regions. According to the important role of As, Cd and Cr from the aspect of ecological and health risk, control of their sources must be considered to attenuate ecological and human adverse effets in the studied areas.

Deep learning pan-specific model for interpretable MHC-I peptide binding prediction with improved attention mechanism.

Accurate prediction of peptide binding affinity to the major histocompatibility complex (MHC) proteins has the potential to design better therapeutic vaccines. Previous work has shown that pan-specific prediction algorithms can achieve better prediction performance than other approaches. However, most of the top algorithms are neural networks based black box models. Here, we propose DeepAttentionPan, an improved pan-specific model, based on convolutional neural networks and attention mechanisms for more flexible, stable and interpretable MHC-I binding prediction. With the attention mechanism, our ensemble model consisting of 20 trained networks achieves high and more stabilized prediction performance. Extensive tests on IEDB's weekly benchmark dataset show that our method achieves state-of-the-art prediction performance on 21 test allele datasets. Analysis of the peptide positional attention weights learned by our model demonstrates its capability to capture critical binding positions of the peptides, which leads to mechanistic understanding of MHC-peptide binding with high alignment with experimentally verified results. Furthermore, we show that with transfer learning, our pan model can be fine-tuned for alleles with few samples to achieve additional performance improvement. DeepAttentionPan is freely available as an open-source software at https://github.com/jjin49/DeepAttentionPan.

Spatial distribution and correlations among elements in smaller than 75 µm street dust: ecological and probabilistic health risk assessment.

This study aimed to investigate spatial distribution, correlations among elements and ecological and probabilistic health risk assessment in smaller than 75 µm street dust in Kerman city, Iran. Street dust samples were collected from 35 different points. Elements were detected by ICP-AES. Pollution degree was characterized through Enrichment Factor (EF), Contamination Factor (CF), Geo-accumulation Index (Igeo) and Potential Ecological Risk (PER). The health risk was assessed using the Monte Carlo simulation method. The mean values of elements were in the order of Al > Mn > Zn > Cu > V > Pb > Cr > Ni > Li > As > Co > Mo > Sb > Cd > Ag. The results of Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) showed that Al, As, Co, Li, Mn and V were possibly derived from natural sources (local soil), while traffic and mining activities were proposed as the main source of Cd, Cr, Cu, Mo, Ni, Pb, Sb and Zn. The order of EF and CF mean values decreased as follows: Mn > Ag > Cu > Zn > Pb > Sb > Mo > Li > Co > V > Cd > As > Cr > Ni. In addition, 73% of Cu and 35% of Zn, Ag and Mn had significant enrichment in the street dust samples. Also, Ag and Mn were categorized in the significant and very significant pollution category. In terms of the PER index, all samples could be classified at low-risk category. Ingestion of street dust was the significant route for exposure of residents of Kerman to the elements studied. No significant ecological hazards and health risks were observed from street dust in the study area in the period of the study. The improvement in the fuels quality and development of green spaces can be suggested to control natural and anthropogenic street dust pollution sources in the Kerman city.

Graph convolutional neural networks with global attention for improved materials property prediction.

The development of an efficient and powerful machine learning (ML) model for materials property prediction (MPP) remains an important challenge in materials science. While various techniques have been proposed to extract physicochemical features in MPP, graph neural networks (GNN) have also shown very strong capability in capturing effective features for high-performance MPP. Nevertheless, current GNN models do not effectively differentiate the contributions from different atoms. In this paper we develop a novel graph neural network model called GATGNN for predicting properties of inorganic materials. GATGNN is characterized by its composition of augmented graph-attention layers (AGAT) and a global attention layer. The application of AGAT layers and global attention layers respectively learn the local relationship among neighboring atoms and overall contribution of the atoms to the material's property; together making our framework achieve considerably better prediction performance on various tested properties. Through extensive experiments, we show that our method is able to outperform existing state-of-the-art GNN models while it can also provide a measurable insight into the correlation between the atoms and their material property. Our code can found on - https://github.com/superlouis/GATGNN.

Preparation of CoFe2O4/activated carbon@chitosan as a new magnetic nanobiocomposite for adsorption of ciprofloxacin in aqueous solutions.

Ciprofloxacin (CIP) is considered as a biological resistant pollutant. The CoFe2O4/activated carbon@chitosan (CoFe2O4/AC@Ch) prepared as a new magnetic nanobiocomposite and used for adsorption of CIP. CoFe2O4/AC@Ch was characterized by Fourier transform-infrared (FT-IR), field emission scanning electron microscope (FESEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), vibrating-sample magnetometer (VSM), and Brunauer-Emmett-Teller (BET) surface area measurements. The pHZPC value of the nanobiocomposite was estimated to be 6.4 by solid addition method. The prepared magnetic nanobiocomposites can be separated easily from water by an external magnet and reused. The effect of CIP concentration (10-30 mg/L), adsorbent dosage (12-100 mg/L), contact time (5-30 min) and pH (3-11) as independent variables on ciprofloxacin removal efficiency was evaluated. Optimum conditions were obtained in CIP concentration: 10 mg/L, adsorbent dosage: 100 mg/L, contact time: 15 min and pH: 5. In this condition, maximum CIP removal was obtained as 93.5%. The kinetic and isotherm equations showed that the process of adsorption followed the pseudo-second order kinetic and Langmuir isotherm. The results indicate that the prepared magnetic nanobiocomposite can be used as good adsorbent for the removal of CIP from aqueous solution and can be also recycled.

Changes in phytochemical synthesis, chalcone synthase activity and pharmaceutical qualities of sabah snake grass (Clinacanthus nutans L.) in relation to plant age.

In the current study, changes in secondary metabolite synthesis and the pharmaceutical quality of sabah snake grass leaves and buds were considered in relation to plant age (1 month, 6 months, and 1 year old). The activity of the enzyme chalcone synthase (CHS, EC 2.3.1.74) was measured, as it is a key enzyme for flavonoid production. Significant differences in total flavonoid (TF) production were observed between the three plant growth periods and the different plant parts. The highest contents of TF (6.32 mg/g dry weight [DW]) and total phenolic (TP) (18.21 mg/g DW) were recorded in 6-month-old buds. Among the flavonoids isolated in this study the most important ones based on concentration were from high to low as follows: catechin > quercetin > kaempferol > luteolin. Production of phenolic acids increased from 1 to 6 months, but after 6 months up to 1 year of age, they decreased significantly. The highest contents of caffeic acid (0.307 mg/g DW) and gallic acid (5.96 mg/g DW) were recorded in 1-year and 6-month-old buds, respectively. The lowest and highest activity of CHS was recorded in 1-month and 6-month-old buds with values of 3.6 and 9.5 nkat/mg protein, respectively. These results indicate that the increment in flavonoids and phenolic acids in 6-month-old buds can be attributed to an increase in CHS activity. The highest 1,1-diphenyl-2-picrylhydrazyl (DPPH) activity was observed in the extract of 1-year-old buds followed by 6-month-old buds, with 50% of free radical scavenging (IC50) values of 64.6 and 73.5 µg/mL, respectively. Interestingly, a ferric reducing antioxidant power (FRAP) assay showed a higher activity in 6-month-old buds (488 µM of Fe(II)/g) than in 1-year-old buds (453 µM of Fe(II)/g), in contrast to the DPPH result. Significant correlations (p < 0.05) were observed between CHS enzyme activity and FRAP activity, TF, catechin, and kaempferol content. Extracts of 6-month-old bud exhibited a significant in vitro anticancer activity against HeLa cancer cells with IC50 value of 56.8 µg/mL. These results indicate that early harvesting of snake grass (6-month-old) may yield increased concentrations of secondary metabolites, which are potent antioxidant compounds.

Facile and green synthesis of recyclable, environmentally friendly, chemically stable, and cost-effective magnetic nanohybrid adsorbent for tetracycline adsorption.

Antibiotic contamination of water sources, particularly tetracycline (TC) contamination, has emerged as one of the global issues that needs action. In this research, ZnCoFe2O4@Chitosan (Ch) as a magnetic nanohybrid adsorbent was synthesized using the microwave-assisted co-precipitation method, and their efficiency for the TC adsorption process was investigated. FESEM (Field Emission Scanning Electron Microscope), EDX (Energy Dispersive X-ray), Mapping and line Scan, XRD (X-Ray Diffraction), FTIR (Fourier Transform Infrared Spectrometer), VSM (Vibrating Sample Magnetometer), Thermogravimetric analysis (TGA) and BET (Brunauer Emmett Teller) techniques were used to check and verify its physical and chemical properties. The removal of TC via the adsorption process from synthetic and real wastewater samples was investigated. The factors determining the TC adsorption process, comprising tetracycline concentration (5-30 mg/L), adsorbent dosage (0.7-2 g/L), contact time (2-45 min), and pH (3-11), were evaluated. The removal effectiveness for the synthetic sample and the real wastewater sample was 93 % and 80 %, respectively, under the ideal TC adsorption process parameters of pH 3, adsorbent dosage 1 g/L, TC initial concentration 5 mg/L, and contact time 30 min. According to kinetic and equilibrium studies, the adsorption of TC by ZnCoFe2O4@Ch follows pseudo-second-order kinetics and the Freundlich isotherm. Additionally, it was determined through the analysis of thermodynamic data that the process of exothermic adsorption is spontaneous and is followed by a decrease in disorder (ΔH = -15.16 kJ/mol, ΔS = -28.69 kJ/mol, and ΔG = -6.62 kJ/mol). After five cycles of recovery and regeneration, the ZnCoFe2O4@Ch magnetic nanocomposite was able to remove 65 % of the TC pollutant and had good chemical stability. The results showed that the magnetic nano-adsorbent ZnCoFe2O4@Ch is a novel magnetic nano-adsorbent with high adsorption capacity that can be utilized to eliminate pharmaceutical contaminants from aqueous solutions.

Advances in three-dimensional electrochemical degradation: A comprehensive review on pharmaceutical pollutants removal from aqueous solution.

Water pollution, stemming from various contaminants including organic and pharmaceutical pollutants, poses a significant global challenge. Amidst the array of methods available for pollutant mitigation, the three-dimensional electrochemical approach emerges as a standout solution due to its environmental compatibility, cost-effectiveness, and rapid efficiency. This study delves into the efficacy of three-dimensional electrochemical processes in purging organic and pharmaceutical pollutants from aqueous media. Existing research indicates that the three-dimensional electrochemical process, particularly when employing particle electrodes, exhibits notable success in degrading organic and pharmaceutical pollutants. This achievement is largely attributed to the ample specific surface area of particle electrodes and the shortened mass transfer distance, which collectively enhance efficiency in comparison to traditional two-dimensional electrochemical methods. Moreover, this approach is lauded for its environmental friendliness and cost-effectiveness. However, it is imperative to note that the efficacy of the process is subject to various factors including temperature, pH levels, and current intensity. While the addition of oxidants can augment process efficiency, it also carries the risk of generating intermediate compounds that impede the reaction. In conclusion, the three-dimensional electrochemical method proves to be a viable and practical approach, provided that process conditions are meticulously considered and adhered to. Offering advantages from both environmental and economic perspectives, this method presents a promising alternative to conventional water and wastewater treatment techniques.

Photocatalytic degradation of Acid Red 18 by synthesized AgCoFe2O4@Ch/AC: Recyclable, environmentally friendly, chemically stable, and cost-effective magnetic nano hybrid catalyst.

Chitosan (Ch) is a linear biodegradable natural carbohydrate polymer and the most appealing biopolymer, such as low-cost biodegradability, biocompatibility, hydrophilicity, and non-toxicity. In this case, Ch was utilized to synthesize AgCoFe2O4@Ch/Activated Carbon (AC) by the modified microwave-assisted co-precipitation method. The physical and chemical structure of magnetic nanocomposites was analyzed and characterized by Field Emission Scanning Electron Microscope (FESEM), Transmission electron microscopy (TEM), X-ray diffraction (XRD), Energy Dispersive Spectroscopy (EDS), Diffuse Reflection Spectroscopy (DRS), Value stream mapping (VSM), Fourier transform spectroscopy (FTIR) and BET. The effects of various parameters on the removal of dye (Acid Red18), including catalyst dose, dye concentration, pH, and time were studied. Results showed that the highest removal efficiencies were 96.68 % and 84 % for the synthetic sample and actual wastewater, respectively, in optimal conditions (pH: 3, the initial dye concentration: 10 mgL-1, the catalyst dose: 0.14 gL-1, time: 50 min). Mineralization, according to the COD analysis, was 89.56 %. Photocatalytic degradation kinetics of Acid Red 18 followed pseudo-first order and Langmuir-Hinshelwood with constants of kc = 0.12 mg L-1 min-1 and KL-H = 0.115 Lmg-1. Synthesized photocatalytic AgCoFe2O4@Ch/AC showed high stability and after five recycling cycles was able to remove the pollutant with an efficiency of 85.6 %. So, the synthesized heterogenous magnetic nanocatalyst AgCoFe2O4@Ch/AC was easily recycled from aqueous solutions and it can be used in the removal of dyes from industries with high efficiency.

Heterogeneous Sono-Fenton like catalytic degradation of metronidazole by Fe3O4@HZSM-5 magnetite nanocomposite.

In this research, Fe3O4@HZSM-5 magnetic nanocomposite was synthesized via a coprecipitation method for metronidazole (MNZ) degradation from aqueous solutions under ultrasonic irradiation which showed superb sonocatalytic activity. The synthesized magnetite nanocomposite was characterized by using field-emission scanning electron microscope-energy dispersive X-ray Spectroscopy, (FESEM-EDS), Line Scan, Dot Mapping, X-ray diffraction (XRD), vibrating sample magnetometer (VSM), and Brunauer-Emmett-Teller (BET). To investigate the sonocatalytic activity of the Fe3O4@HZSM-5 magnetite nanocomposite, the sonocatalytic removal conditions were optimized by evaluating the influences of operating parameters like the dosage of catalyst, reaction time, pH, the concentration of H2O2, MNZ concentration, and pH on the MNZ removal. The MNZ maximum removal efficiency and TOC at reaction time 40 min, catalyst dose 0.4 g/L, H2O2 concentration 1 mM, MNZ initial concentration 25 mg/L, and pH 7 were achieved at 98% and 81%, respectively. Additionally, the MNZ removal efficiency in the real wastewater sample under optimal conditions was obtained at 83%. The achieved results showed that using Langmuir-Hinshelwood kinetic model KL-H = 0.40 L mg-1, KC = 1.38 mg/L min) can describe the kinetic removal of the process. The radical scavenger tests indicated that the major reactive oxygen species were formed by hydroxyl radicals in the Sono-Fenton-like process. Evaluation of the nanocomposite reusability showed an 85% reduction in the MNZ removal efficiency after seven cycles. Based on the results, it can be concluded that Fe3O4@HZSM-5 were synthesized as magnetic heterogeneous nano-catalysts to effectively degrade MNZ, and the observed stability and recyclability demonstrated that Fe3O4@HZSM-5 was promising for the treatment of wastewater contaminated with antibiotics.

Enhanced activation of persulfate by CuCoFe2O4@MC/AC as a novel nanomagnetic heterogeneous catalyst with ultrasonic for metronidazole degradation.

In this study, the degradation of Metronidazole (MNZ) using CuCoFe2O4@MC/AC catalyst synthesized by microwave-assisted method, as an efficient activator for persulfate (PS) in the presence of ultrasonic (US: 60 kHz) was investigated. X-ray powder diffraction (XRD), Field emission scanning electron microscope (FESEM), Energy dispersive spectroscopy (EDS)-Mapping and Line scan, Fourier transform infrared spectroscopy (FTIR), Vibrating-sample magnetometer (VSM), and Thermal gravimetric analysis (TGA) were conducted to characterize the structure of CuCoFe2O4@MC/AC catalyst and then the catalyst dose, PS dose, MNZ concentration, and pH parameters were optimized. The maximum MNZ degradation of 93.78 % was achieved after 15 min reaction at the optimized operation conditions: 0.4 g L-1 of catalyst, 6 mM of PS, 5 mg L-1 of MNZ, and pH of 3. The removal efficiency of Total Organic Carbon (TOC) was 87.5 % under optimal conditions. According to kinetic equations, it was found that the MNZ degradation followed both kinetics (pseudo-first-order and Langmuir-Hinshelwood) based on the coefficient of determination (R2) of 0.949, 0.9716, 0.9073, 0.9721, and 0.9662 at concentrations of 5, 10, 15, 20, and 30, respectively. The surface reaction rate constant (Kc) and the adsorption equilibrium constant (KL-H) of the Langmuir-Hinshelwood model were 0.81 (mg L-1 min-1) and 2.184 (L mg-1), respectively. The free radical scavenging experiments were conducted to illustration the proposed mechanism, which shown that the SO4-• was the predominant radicals involved in MNZ degradation. Finally, the regeneration of the catalyst was investigated and showed that after five cycles of use and regeneration by chemical and thermal methods, this catalyst has acceptable chemical stability.

Correlation between heavy metal concentration and oxidative potential of street dust.

The current study aimed to consider oxidative potential (OP), its spatial distribution, and correlations with heavy metals (HMs) in street dust in Kerman city, Iran. The concentration of HMs in 35 street dust samples was detected by ICP-AES. The OP in samples was measured through dithiothreitol (DTT). The mean concentration of elements followed Zn > Cu > Pb > Cr > As > Cd. The OP value was found to be 7.17 ± 2.98 nmol/min. µg dust in the current study. A strong correlation was observed among the concentrations of As and Cr and OP values in dust samples. More values of OP were observed in the center and west of the Kerman city. According to results of the current study, it could be concluded that OP can be applied as metrics of pollution originated from different sources and human health effects. The amount of OP in the street dust in the Kerman city can be reduced through the use of clean fuels.

Morganella Morganii Infection in Hirudo Medicinalis (Iran): A Case Report.

Medicinal leeches (Hirudo medicinalis) are used in surgical and non-surgical manners. Morganella morganii is an opportunistic and zoonotic pathogenic bacterium causing serious clinical complications. In this study, we isolated, discovered and characterized M. morganii-infected H. medicinalis. We detected and identified M. morganii in all inflamed and swollen Hirudo medicinalis samples. The 16S rRNA sequence of the isolates confirmed all strains of M. morganii. All strains were sensitive to Ceftriaxone, Ceftiofur, Danofloxacin, Ciprofloxacin, Enrofloxacin, Oxytetracycline, and Meropenem and were resistant to Erythromycin, Amoxicillin, Ampicillin, Cefazolin, Colistin, Penicillin G, and Lincomycin. This pathogenic bacterium is a zoonotic pathogen, and monitoring the prevalence rate of this bacteria is strongly necessary for leeches used in human medical treatment and care. Finally, all infected leeches were treated successfully in this case report study.

DeepSeqPanII: An Interpretable Recurrent Neural Network Model With Attention Mechanism for Peptide-HLA Class II Binding Prediction.

Human leukocyte antigen (HLA) complex molecules play an essential role in immune interactions by presenting peptides on the cell surface to T cells. With significant deep learning progress, a series of neural network-based models have been proposed and demonstrated with their excellent performances for peptide-HLA class I binding prediction. However, there is still a lack of effective binding prediction models for HLA class II protein binding with peptides due to its inherent challenges. We present a novel sequence-based pan-specific neural network structure, DeepSeaPanII, for peptide-HLA class II binding prediction in this work. Our model is an end-to-end neural network model without the need for pre-or post-processing on input samples compared with existing pan-specific models. Besides state-of-the-art performance in binding affinity prediction, DeepSeqPanII can also extract biological insight on the binding mechanism over the peptide by its attention mechanism-based binding core prediction capability. The leave-one-allele-out cross-validation and benchmark evaluation results show that our proposed network model achieved state-of-the-art performance in HLA-II peptide binding. The source code and trained models are freely available at https://github.com/pcpLiu/DeepSeqPanII.

Effect of minocycline on the left ventricular function following ST-elevation myocardial infarction treated by primary percutaneous coronary intervention.

BACKGROUND: Cardiac remodeling following myocardial infarction is a pathological process. We aimed to examine the effect of early short-term minocycline on the left ventricular function following ST-elevation myocardial infarction treated by the primary percutaneous coronary intervention. METHODS: In this double-blind, randomized controlled trial, data of 73 patients STEMI patients who were candidates for primary PCI were enrolled. Patients were then randomized to receive minocycline 50 mg orally, followed by 50 mg once a day for 5 days or a placebo with the same schedule. Measurement of serum matrix metalloproteinase-9 (MMP-9) and 2-dimensional speckle tracking echocardiography was performed at baseline and between 4 and 6 months after discharge. Then the demographic, clinical, echocardiographic, and angiographic data, as well as the levels of MMP-9, were compared between the study groups. RESULTS: There was no statistically significant difference between the study groups regarding the baseline characteristics. Serum levels of MMP-9 did not change following the intervention within each group and were not significantly different between the groups after follow-up. In the follow-up echocardiography, we also did not observe any difference between the two groups CONCLUSION: In this study, we did not observe any effect of minocycline on cardiac remodeling based on 2-dimensional speckle tracking echocardiography and MMP-9 levels. TRIAL REGISTRATION: Iranian Registry of Clinical Trials IRCT201411188698N15 . Registered on 22 June 2015, prospectively.

Effect of titanium dioxide nanoparticles on DNA methylation of human peripheral blood mononuclear cells.

The aim of the current study was to investigate the effect of well-characterized TiO2 nanoparticles on DNA methylation of peripheral blood mononuclear cells (PBMCs) in vitro. Maximum non-toxic concentration of nanoparticles for PBMCs was determined by MTT assay. The effect of TiO2 nanoparticles at concentrations of 25-100 µg/ml on DNA methylation of PBMCs was investigated by measuring the %5-mC alterations through an ELISA assay. The physicochemical analysis showed that the TiO2 nanoparticles were crystalline, pure and in the anatase phase. Peaks related to Ti-O tensile vibrations were observed in the range of 1510 cm-1. The size of nanoparticles was in the range of 39-74 nm with an average hydrodynamic diameter of 43.82 nm. According to the results of the MTT test, 100 µg/ml was found to be maximum non-toxic concentration. The %5-mC in treated PBMCs revealed that TiO2 nanoparticles could lead to DNA hypomethylation in PBMCs. The %5-mC difference compared with the negative control was found to be 2.07 ± 1.02% (P = 0.03). The difference of %5-mC between the 25 and 100 µg/ml concentration of nanoparticles was statistically significant (P = 0.02). The results of the current study show that the TiO2 nanoparticles cause DNA hypomethylation in PBMCs in a dose-response manner. Therefore, it is recommended to evaluate the effects of cytotoxicity and epigenotoxicity of commonly used nanoparticles before their use.

High-Throughput Discovery of Novel Cubic Crystal Materials Using Deep Generative Neural Networks.

High-throughput screening has become one of the major strategies for the discovery of novel functional materials. However, its effectiveness is severely limited by the lack of sufficient and diverse materials in current materials repositories such as the open quantum materials database (OQMD). Recent progress in deep learning have enabled generative strategies that learn implicit chemical rules for creating hypothetical materials with new compositions and structures. However, current materials generative models have difficulty in generating structurally diverse, chemically valid, and stable materials. Here we propose CubicGAN, a generative adversarial network (GAN) based deep neural network model for large scale generative design of novel cubic materials. When trained on 375 749 ternary materials from the OQMD database, the authors show that the model is able to not only rediscover most of the currently known cubic materials but also generate hypothetical materials of new structure prototypes. A total of 506 such materials have been verified by phonon dispersion calculation. Considering the importance of cubic materials in wide applications such as solar panels, the GAN model provides a promising approach to significantly expand existing materials repositories, enabling the discovery of new functional materials via screening. The new crystal structures discovered are freely accessible at www.carolinamatdb.org.

Photocatalytic degradation of ciprofloxacin using CuFe2O4@methyl cellulose based magnetic nanobiocomposite.

Herein, magnetically separable CuFe2O4@methyl cellulose (MC) as a novel magnetic nanobiocomposite photocatalyst was synthesized with a facile, rapid, green, and new microwave-assisted method. After that, CuFe2O4@MC was characterized with FESEM, EDS, FT-IR, XRD, TGA, and VSM techniques. To measure CuFe2O4@MC photocatalytic activity, ciprofloxacin (CIP) removal ability of CuFe2O4@MC was investigated under the conditions such as initial CIP concentrations (3, 5, 7, and 9 mg/L), pHs (3, 7, and 11), photocatalyst loadings (0.025, 0.05, 0.1, 0.2, 0.3, and 0.4 g), and irradiation time (15, 30, 45, 60, 75, and 90 min). Kinetic process was evaluated with the pseudo-first order and the Langmuir-Hinshelwood models. CIP concentration was measured with high performance liquid chromatography (HPLC). The maximum CIP removal efficiency in the optimal conditions which contained pH = 7, CIP initial concentration of 3 mg/L, photocatalyst loading of 0.2 g, and at irradiation time 90 min was achieved 72.87 % and 80.74 % from real and synthetic samples, respectively. Also, COD removal efficiency in the optimal conditions was achieved 68.26 %. Furthermore, the CuFe2O4@MC reusability and chemical stability were examined and 73.78 % of CIP was degraded after the fourth cycle. Advantages of this technique were as follows: •CuFe2O4@MC as a new nanobiomagnetic photocatalyst was synthesized with a facile, fast, and green method and were characterized with FESEM, EDS, FT-IR, XRD, TGA, and VSM techniques.•Ferromagnetic property and pure-phase spinel ferrites of CuFe2O4@MC were confirmed and significant photocatalytic activity of CuFe2O4@MC was observed.•Easily gathering, reusability and good chemical stability were interests of this nanobiomagnetic photocatalyst.