Asynchronous Ring Opening of Cyclic Carbonate and Glycidyl Ether Induced Phase Evolution Towards Heat-Free and Rapid-Bonding Superior Epoxy Adhesive.

Structural adhesives that do not require heating are in high demand in the automotive and electronics industries. However, it remains a challenge to develop robust adhesives that rapidly achieve super adhesion near ambient temperature. Herein, a room-temperature curable, fast-bonding, and super strong epoxy-based structural adhesive was designed from the perspective of cross-scale structure, which lies in threefold pivotal aspects: (i) high branching topology of glycerol carbonate-capped polyurethane (PUGC) increases the kinetics of the ring-opening reaction, contributing to fast crosslinking and the formation of abundant urethane and hydroxyl moieties; (ii) asynchronous crosslinking of epoxy and PUGC synergistically induces phase separation of PUGC within the epoxy resin and the resulting PUGC domains surrounded by interpenetrated shell serves to efficiently toughen the matrix; (iii) abundant dynamic hydrogen bonds including urethane and hydroxyl moieties, along with the elastomeric PUGC domains, dissipate energy of shearing force. As a result, the adhesive strength rapidly grows to 16 MPa within 4 hours, leveling off to 21 MPa after 7 hours, substantially outperforming commercial room-temperature curable epoxy adhesives. The results of this study could advance the field of high-performance adhesives and provide valuable insights into designing materials for efficient curing at room temperature.

Emulsion-Assisted Polymerization-Induced Hierarchical Self-Assembly of Giant Sea Urchin-like Aggregates on a Large Scale.

Hierarchical solution self-assembly has become an important biomimetic method to prepare highly complex and multifunctional supramolecular structures. However, despite great progress, it is still highly challenging to prepare hierarchical self-assemblies on a large scale because the self-assembly processes are generally performed at high dilution. Now, an emulsion-assisted polymerization-induced self-assembly (EAPISA) method with the advantages of in situ self-assembly, scalable preparation, and facile functionalization was used to prepare hierarchical multiscale sea urchin-like aggregates (SUAs). The obtained SUAs from amphiphilic alternating copolymers have a micrometer-sized rattan ball-like capsule (RBC) acting as the hollow core body and radiating nanotubes tens of micrometers in length as the hollow spines. They can capture model proteins effectively at an ultra-low concentration (ca. 10 nm) after functionalization with amino groups through click copolymerization.

Polymer Vesicle Sensor for Visual and Sensitive Detection of SO2 in Water.

This study reports the first polymer vesicle sensor for the visual detection of SO2 and its derivatives in water. A strong binding ability between tertiary alkanolamines and SO2 has been used as the driving force for the detection by the graft of tertiary amine alcohol (TAA) groups onto an amphiphilic hyperbranched multiarm polymer, which can self-assemble into vesicles with enriched TAA groups on the surface. The polymer vesicles will undergo proton exchange with cresol red (CR) to produce CR-immobilized vesicles (CR@vesicles). Subsequently, through competitive binding with the TAA groups between CR and SO2 or HSO3-, the CR@vesicles (purple) can quickly change into SO2@vesicles (colorless) with the release of protonated CR (yellow). Such a fast purple to yellow transition in the solution allows the visual detection of SO2 or its derivatives in water by the naked eye. A visual test paper for SO2 gas has also been demonstrated by the adsorption of CR@vesicles onto paper. Meanwhile, the detection limit of CR@vesicles for HSO3- is approximately 25 nM, which is improved by approximately 30 times when compared with that of small molecule-based sensors with a similar structure (0.83 µM). Such an enhanced detection sensitivity should be related to the enrichment of TAA groups as well as the CR in CR@vesicles. In addition, the CR@vesicle sensors also show selectivity and specificity for the detection of SO2 or HSO3- among anions such as F-, Br-, Cl-, SO42-, NO2-, C2O42-, S2O32-, SCN-, AcO-, SO32-, S2-, and HCO3-.

Extremely strengthening fatigue resistance, elastic restorability and thermodynamic stability of a soft transparent self-healing network based on a dynamic molecular confinement-induced bioinspired nanostructure.

Soft self-healing materials are crucial for the development of next-generation wearable electronics that could function in dynamic environments and resist mechanical damage. However, several challenges remain, including fatigue fracture, poor elasticity, and thermodynamic lability, which significantly limit their practical applications. Here, with a model system of soft self-healing polyurea, we propose a molecular engineering strategy of transforming inherently fragile materials with an island-like structure into resilient ones with a bicontinuous nanophase separation structure using 2-ureido-4-pyrimidinone (UPy) supramolecular motifs as structural regulators. The dynamic and continuous hard domains modified by UPy formed a repairable bicontinuous network similar to those of the reticular layer in animal dermis. This design allows for a simultaneous and tremendous improvement in the fatigue threshold (34.8-fold increase), elastic restorability (the maximum elongation for full dimensional recovery increasing from 6 times to 13 times), and thermodynamic stability (4 orders of magnitude improvement in the characteristic flow transition relaxation time), without significantly compromising the compliance, autonomous self-healing, and optical transparency. These mechanical and thermodynamic improvements address current limitations in unfilled soft self-healing materials as reliable substrates for transparent strain-electronics.

A strain-reinforcing elastomer adhesive with superior adhesive strength and toughness.

Strong and ductile adhesives often undergo both interfacial and cohesive failure during the debonding process. Herein, we report a rare self-reinforcing polyurethane adhesive that shows the different phenomenon of only interfacial failure yet still exhibiting superior adhesive strength and toughness. It is synthesized by designing a hanging adhesive moiety, hierarchical H-bond moieties, and a crystallizable soft segment into one macromolecular polyurethane. The former hanging adhesive moiety allows the hot-melt adhesive to effectively associate with the target substrate, providing sufficient adhesion energy; the latter hierarchical H-bond moieties and a crystallizable soft segment cooperate to enable the adhesive to undergo large lap-shear deformations through sacrificing weak bonds and mechano-responsive strength through the fundamental mechanism of strain-induced crystallization. As a result, this polyurethane adhesive can keep itself intact during the debonding process while still withstanding a high lap-shear strength and dissipating tremendous stress energy. Its adhesive strength and work of debonding are as high as 11.37 MPa and 10.32 kN m-1, respectively, outperforming most reported tough adhesives. This self-reinforcing adhesive is regarded as a new member of the family of strong and ductile adhesives, which will provide innovative chemical and structural inspirations for future conveniently detachable yet high-performance adhesives.

Prediction of Central Visual Field Measures From Macular OCT Volume Scans With Deep Learning.

Purpose: Predict central 10° global and local visual field (VF) measurements from macular optical coherence tomography (OCT) volume scans with deep learning (DL). Methods: This study included 1121 OCT volume scans and 10-2 VFs from 289 eyes (257 patients). Macular scans were used to estimate 10-2 VF mean deviation (MD), threshold sensitivities (TS), and total deviation (TD) values at 68 locations. A three-dimensional (3D) convolutional neural network based on the 3D DenseNet121 architecture was used for prediction. We compared DL predictions to those from baseline linear models. We carried out 10-fold stratified cross-validation to optimize generalizability. The performance of the DL and baseline models was compared based on correlations between ground truth and predicted VF measures and mean absolute error (MAE; ground truth - predicted values). Results: Average (SD) MD was -9.3 (7.7) dB. Average (SD) correlations between predicted and ground truth MD and MD MAE were 0.74 (0.09) and 3.5 (0.4) dB, respectively. Estimation accuracy deteriorated with worsening MD. Average (SD) Pearson correlations between predicted and ground truth TS and MAEs for DL and baseline model were 0.71 (0.05) and 0.52 (0.05) (P < 0.001) and 6.5 (0.6) and 7.5 (0.5) dB (P < 0.001), respectively. For TD, correlation (SD) and MAE (SD) for DL and baseline models were 0.69 (0.02) and 0.48 (0.05) (P < 0.001) and 6.1 (0.5) and 7.8 (0.5) dB (P < 0.001), respectively. Conclusions: Macular OCT volume scans can be used to predict global central VF parameters with clinically relevant accuracy. Translational Relevance: Macular OCT imaging may be used to confirm and supplement central VF findings using deep learning.

[Mono-specific serum preparation and specificity of gp85 gene of subgroup A avian leukosis virus].

OBJECTIVE: In order to get a rapid specific diagnostic reagent for subgroup A Avian Leukosis Virus detection. METHODS: The Avian Leukosis Virus Subgroup A (ALV-A) SDAU09E1 strain was inoculated into DF1 cells, an ALV-A- gp85 DNA fragment of 1023 bp was amplified from infected cells and inserted into PET-32a(+) plasmid at the location between restriction endonucleases BamH I and Not I sites. The recombinant plasmid PET-SDAU09E1 -gp85 was transformed into E coli. BL21 (Rosetta) for gp85 gene expression. Then we used the purified recombinant fusion protein to immunize 6 weeks old Kunming white mice, and the antiserum were prepared. RESULTS: The recombinant ALV-A gp85 fusion protein with a molecular weight of 52.8 kDa demonstrated a good antigenecity. Mon-specific serum produced by vaccinated mice came out reactive with subgroups A and B ALV (ALV-A and ALV-B but not subgroup J ALV) by the indirect immunofluorescence (IFA) method. CONCLUSION: This was the first time to demonstrate a mono-specific antiserum specific to ALV-A and ALV-B, it could be used for differential diagnosis of exogenous ALV infections in CEF cultures when in complement with ALV-J specific monoclonal antibodies. Chickens in our country are now distressed by both classic ALV-A/B and emerging ALV-J, making differential diagnosis necessary, so studying this reagent has high practical value.

K-Module Algorithm: An Additional Step to Improve the Clustering Results of WGCNA Co-Expression Networks.

Among biological networks, co-expression networks have been widely studied. One of the most commonly used pipelines for the construction of co-expression networks is weighted gene co-expression network analysis (WGCNA), which can identify highly co-expressed clusters of genes (modules). WGCNA identifies gene modules using hierarchical clustering. The major drawback of hierarchical clustering is that once two objects are clustered together, it cannot be reversed; thus, re-adjustment of the unbefitting decision is impossible. In this paper, we calculate the similarity matrix with the distance correlation for WGCNA to construct a gene co-expression network, and present a new approach called the k-module algorithm to improve the WGCNA clustering results. This method can assign all genes to the module with the highest mean connectivity with these genes. This algorithm re-adjusts the results of hierarchical clustering while retaining the advantages of the dynamic tree cut method. The validity of the algorithm is verified using six datasets from microarray and RNA-seq data. The k-module algorithm has fewer iterations, which leads to lower complexity. We verify that the gene modules obtained by the k-module algorithm have high enrichment scores and strong stability. Our method improves upon hierarchical clustering, and can be applied to general clustering algorithms based on the similarity matrix, not limited to gene co-expression network analysis.

Stratification of Estrogen Receptor-Negative Breast Cancer Patients by Integrating the Somatic Mutations and Transcriptomic Data.

Patients with estrogen receptor-negative breast cancer generally have a worse prognosis than estrogen receptor-positive patients. Nevertheless, a significant proportion of the estrogen receptor-negative cases have favorable outcomes. Identifying patients with a good prognosis, however, remains difficult, as recent studies are quite limited. The identification of molecular biomarkers is needed to better stratify patients. The significantly mutated genes may be potentially used as biomarkers to identify the subtype and to predict outcomes. To identify the biomarkers of receptor-negative breast cancer among the significantly mutated genes, we developed a workflow to screen significantly mutated genes associated with the estrogen receptor in breast cancer by a gene coexpression module. The similarity matrix was calculated with distance correlation to obtain gene modules through a weighted gene coexpression network analysis. The modules highly associated with the estrogen receptor, called important modules, were enriched for breast cancer-related pathways or disease. To screen significantly mutated genes, a new gene list was obtained through the overlap of the important module genes and the significantly mutated genes. The genes on this list can be used as biomarkers to predict survival of estrogen receptor-negative breast cancer patients. Furthermore, we selected six hub significantly mutated genes in the gene list which were also able to separate these patients. Our method provides a new and alternative method for integrating somatic gene mutations and expression data for patient stratification of estrogen receptor-negative breast cancers.

Characteristics of Micro/Nanopores and Their Petroleum Significance in the Eastern Segment of the Altun Piedmont, Qaidam Basin, Western China.

With continuous improvements in nanotechnology, the development of micro/nanoscale pores and fractures in reservoirs can be more clearly identified, and great progress has been made in tight sandstone and shale. Bedrock has an ultralow porosity and is a reservoir with low permeability. To study the characteristics of micro/nanoscale pore development and reveal their petroleum significance in the eastern segment of the Altun Piedmont, research has been conducted with the use of cathodoluminescence, field emission scanning electron microscopy and energy spectrum analysis, formation microresistivity image logging, high-pressure mercury injection and nuclear magnetic logging. The results have shown that the porosity of the bedrock reservoir in the eastern segment of the Altun Piedmont, as measured by helium injection and nuclear magnetic logging, is between 0.004% and 9.76%, the average porosity is between 1.663% and 3.844%, and the permeability is between the maximum of 0.002 mD and 33.239 mD. The average permeability is between 0.02 mD and approximately 3.836 mD. Micro/nanopores are generally developed, with the majority being intragranular micro/nanopores, intercrystalline micro/nanopores and microcracks, as summarized by the field emission scanning electron microscopy and energy dispersive spectroscopy analysis. Four differently sized pores develop: micropores account for approximately 20%, transition pores account for approximately 30%, and mesopores and macropores account for approximately 25% each. The pore throat development below 100 nm is greater than 50% according to the collation of experimental data from high-pressure mercury intrusion; therefore, micro/nanopores are the main storage space in the study area, and the gas logging shows good results. Micro/nanopores are also one of the main reservoir spaces of bedrock reservoirs in conjunction with the conventional reservoir space, and thus, micro/nanopores have important petroleum significance.

A Multiscale Evaluation of the Coupling Relationship between Urban Land and Carbon Emissions: A Case Study of Chongqing, China.

Exploring the coupling relationship between urban land and carbon emissions (CE) is one of the important premises for coordinating the urban development and the ecological environment. Due to the influence of the scale effect, a systematic evaluation of the CE at different scales will help to develop more reasonable strategies for low-carbon urban planning. However, corresponding studies are still lacking. Hence, two administrative scales (e.g., region and county) in Chongqing were selected as experimental objects to compare and analyze the CE at different scales using the spatiotemporal coupling and coupling coordination models. The results show that urban land and carbon emissions presented a significant growth trend in Chongqing at different scales from 2000 to 2015. The strength of the spatiotemporal coupling relationship between urban land and total carbon emissions gradually increased with increasing scale. At the regional scale, the high coupling coordination between urban land and total carbon emissions was mainly concentrated in the urban functional development region. Additionally, the high coupling coordination between urban land and carbon emission intensity (OI) was still located in the counties within the metropolitan region of Chongqing, but the low OI was mainly distributed in the counties in the northeastern and southeastern regions of Chongqing at the county level. This study illustrates the multiscale trend of CE and suggests differentiated urban land and carbon emission reduction policies for controlling urban land sprawl and reducing carbon emissions.

Amphiphilic Organic Cages: Self-Assembly into Nanotubes and Enhanced Anion-π Interactions.

An amphiphilic organic cage was synthesized and used as self-assembly synthon for the fabrication of novel functional supramolecular structures in solution. The transmission electron microscopy (TEM) results showed that this amphiphilic cage self-assembled in aqueous solution into unilamellar nanotubes with a diameter of 29±4 nm at a concentration of 0.05 mg mL-1 . Interestingly, the self-assembly of this cage significantly enhanced the anion-π interactions as indicated by a remarkable increasement of association constant (Ka ) between Cl- and this amphiphilic cage after self-assembly. In specific, Ka was increased from 223 M-1 for discrete cages in methanol to 6800 M-1 for aggregated cages after self-assembly in water at the same concentration of 2.26×10-5  M. A mechanism based on a synergistic effect was proposed in order to explain this self-assembly process through enhanced anion-π interactions.

Solution Self-Assembly of an Alternating Copolymer toward Hollow Carbon Nanospheres with Uniform Micropores.

Controllable preparation of porous hollow carbon spheres (HCSs) has attracted considerable attention due to their potential applications, e.g., in energy conversion and storage. We report for the first time the synthesis of narrowly size-distributed HCSs with uniform micropores in the wall, through a simple template-free approach, which employs the solution self-assembly of an alternating copolymer (poly(9,9'-bis(4-glycidyloxyphenyl)fluorene-alt-2,3-dihydroxy-butylene dithioether) (P(BGF-a-DHBDT))). This alternating copolymer first self-assembled into previously undocumented hollow polymeric spheres (HPSs) in an N,N-dimethylformamide (DMF)/H2O solvent mixture. After the cross-linking of the BGF segments in the spheres, the stabilized HPSs (CL-HPSs) were carbonized at 800 °C under N2 atmosphere, yielding porous HCSs with uniform micropores of very narrow size distribution (0.4-0.8 nm) in the wall, benefiting from the uniform DHBDT block length in the alternating copolymer. Through KOH activation, which made the internal pores fully interconnected, uniform micropores (0.5-1.0 nm) of a narrow size distribution were retained within the activated HCSs (A-HCSs), while their specific surface areas (SSAs) were much increased to 2580 m2 g-1. As a proof of concept, the A-HCSs were applied as electrode materials of supercapacitors. They exhibited superior electrochemical performance with a high specific capacitance (292 F g-1 at 0.2 A g-1), good rate capability, and outstanding cycling stability with no apparent capacitance loss after 10 000 cycles.

Facile Synthesis of a H2O2-Responsive Alternating Copolymer Bearing Thioether Side Groups for Drug Delivery and Controlled Release.

A novel amphiphilic alternating copolymer with thioether side groups (P(MSPA-a-EG)) was synthesized through an amine-epoxy click reaction of 3-(methylthio)propylamine (MSPA) and ethylene glycol diglycidyl ether. P(MSPA-a-EG) was characterized in detail by nuclear magnetic resonance (NMR), gel permeation chromatography, Fourier transformed infrared, differential scanning calorimeter, and thermogravimetric analysis to confirm the successful synthesis. Due to its amphiphilic structure, P(MSPA-a-EG) could self-assemble into spherical micelles with an average diameter of about 151 nm. As triggered by H2O2, theses micelles could disassemble because hydrophobic thioether groups are transformed to hydrophilic sulfoxide groups in MSPA units. The oxidant disassemble process of micelles was systemically studied by dynamic light scattering, transmission electron microscopy, and 1H NMR measurements. The MTT assay against NIH/3T3 cells indicated that P(MSPA-a-EG) micelles exhibited good biocompatibility. Furthermore, they could be used as smart drug carriers to encapsulate hydrophobic anticancer drug doxorubicin (DOX) with 4.90% drug loading content and 9.81% drug loading efficiency. In vitro evaluation results indicated that the loaded DOX could be released rapidly, triggered by H2O2. Therefore, such a novel alternating copolymer was expected to be promising candidates for controlled drug delivery and release.

Potentially toxic elements and environmentally-related pollutants recognition using colorimetric and ratiometric fluorescent probes.

A safer detection or sensing of toxic pollutants is one among several environmental contamination issues, across the globe. The ever-increasing industrial practices and controlled or uncontrolled release of toxic pollutants from various industrial sectors is a key source of this environmental problem. Significant research efforts have been or being made to tackle this problematic issue to fulfill the growing needs of the modern world. Despite many useful aspects, heavy metals are posing noteworthy toxicological concerns and human-health related issues at various levels of the ecosystem. In this context, notable efforts from various regulatory authorities, the increase in the concentration of these toxic heavy metals in the environment is of serious concern, so real-time monitoring is urgently required. Herein, we reviewed fluorescent sensor based models and their potentialities to address the detection fate of hazardous pollutants including chromium, manganese, cobalt, nickel, copper, and zinc as model elements. The novel aspects of turn-on/off fluorescent sensors have also been discussed from a state of the art viewpoint. In summary, comprehensive literature regarding fluorescent sensor based models and their potentialities to detect various types of toxic pollutants is reviewed.

Catalytic potential of bio-synthesized silver nanoparticles using Convolvulus arvensis extract for the degradation of environmental pollutants.

Herein, we reported a facile, green and environmental friendlier biosynthesis of silver nanoparticles using the Convolvulus arvensis extract. The influences of various physicochemical factors such as the concentration of the plant extract, reaction time, and different pH levels were investigated by UV-Vis spectroscopy. The UV-Visible absorption spectrum of biogenic silver nanoparticles at λmax around ~400 nm suggested the biosynthesis of silver nanoparticles. Fourier transform infrared spectroscopy was employed to confirm the chemical transformation and role of various phyto-reductants in the conversion of Ag+ to Ag0. The surface morphology, topography, and elemental composition were analyzed by scanning electron microscopy, transmission electron microscopy, and energy dispersive X-ray spectroscopy, respectively. X-ray diffraction corroborated the face-centered cubic crystalline structure. The dynamic light scattering and zeta potential demonstrate the size distribution (90.9 nm) and surface charge (-18.5). Finally, the newly developed C. arvensis based silver nanoparticles were exploited as a catalyst for the catalytic reduction of azo dyes in the presence of NaBH4 as a reducing agent, and reducing the activity of C. arvensis based silver nanoparticles was evaluated by a decrease in optical density using UV-Vis spectrophotometer. The nanoparticles developed herein displayed potential efficiency for the degradation of all the tested dye pollutants. Conclusively, plant-based synthesis of nanoparticles provides an environmentally-responsive option for the reduction of highly environmental-polluted organic compounds including toxic azo dyes as compared to chemical and physical methods.

Fluorescent sensor based models for the detection of environmentally-related toxic heavy metals.

The quest for industrial and biotechnological revolution has been contributed in increasing environmental contamination issues, worldwide. The controlled or uncontrolled release of hazardous pollutants from various industrial sectors is one of the key problems facing humanity. Among them, adverse influences of lead, cadmium, and mercury on human health are well known to cause many disorders like reproductive, neurological, endocrine system, and cardiovascular, etc. Besides their presence at lower concentrations, most of these toxic heavy metals are posing noteworthy toxicological concerns. In this context, notable efforts from various regulatory authorities, the increase in the concentration of these toxic heavy metals in the environment is of serious concern, so real-time monitoring is urgently required. This necessitates the exploration for novel and efficient probes for recognition of these toxic agents. Among various methodologies adopted for tailoring such probes, generally the methodologies, in which changes associated with spectral properties, are preferred for the deceptive ease in the recognition process. Accordingly, a promising modality has emerged in the form of radiometric and colorimetric monitoring of these toxic agents. Herein, we review fluorescent sensor based models and their potentialities to address the detection fate of hazardous pollutants for a cleaner environment. Second, recent advances regarding small molecule and rhodamine-based fluorescent sensors, radiometric and colorimetric probes are discussed. The information is also given on the photoinduced electron transfer (PET) mechanism, chelation enhancement fluorescence (CHEF) effect and spirocyclic ring opening mechanism.

Biomedical Potentialities of Taraxacum officinale-based Nanoparticles Biosynthesized Using Methanolic Leaf Extract.

BACKGROUND: In the present study, the potential of methanolic leaf extract of Taraxacum officinale plant as a function of bio-inspired green synthesis for the fabrication of silver nanoparticles (AgNPs) has been explored. METHODS: The bio-reduction of aqueous silver nitrate (AgNO3) solution was confirmed by visually detecting the color change from pale yellow to blackish-brown. Maximum absorbance was observed at 420 nm due to the presence of characteristic surface Plasmon resonance of nano silver by UV-visible spectroscopy. The role of various functional groups in the bio-reduction of silver and chemical transformation was verified by Fourier transform infrared spectroscopy (FTIR). Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX) predict the shape (rocky, flack type, ellipsoidal, etc.), size (68 nm) and elemental composition (Ag as a major constituent) of the biosynthesized AgNPs, respectively. RESULTS: Transmission electron microscopy (TEM) analysis further corroborated the morphology of the AgNPs. Color mapping and atomic force microscopy (AFM) confirmed the nano-sized topography. The dynamic light scattering (DLS) showed the charge, stability, and size of the AgNPs. The generated AgNPs presented potential antibacterial activities against Gram-positive and Gram-negative bacterial strains including Staphylococcus aureus, Escherichia coli, and Haemophilus influenzae. The biosynthesized AgNPs also showed antiproliferative activity against MCF-7 breast cancer cell line in a dosedependent manner. CONCLUSION: In conclusion, results clearly indicate that biosynthesized AgNPs could be used as effective nano drug for treating infectious diseases caused by multidrug resistant bacterial strains in the near future.

Green biosynthesis of silver nanoparticles using leaves extract of Artemisia vulgaris and their potential biomedical applications.

Biosynthesis of nanoparticles from plant extracts is receiving enormous interest due to their abundant availability and a broad spectrum of bioactive reducing metabolites. In this study, the reducing potential of Artemisia vulgaris leaves extract (AVLE) was investigated for synthesizing silver nanoparticles without the addition of any external reducing or capping agent. The appearance of blackish brown color evidenced the complete synthesis of nanoparticles. The synthesized silver nanoparticles were characterized by UV-vis spectroscopy, scanning electron microscope (SEM), energy dispersive X-ray spectroscopy (EDX), transmission electron microscope (TEM), atomic force microscopy (AFM) and Fourier transforms infrared spectroscopy (FT-IR) analysis. UV-vis absorption profile of the bio-reduced sample elucidated the main peak around 420nm, which correspond to the surface plasmon resonance of silver nanoparticles. SEM and AFM analyses confirmed the morphology of the synthesized nanoparticles. Similarly, particles with a distinctive peak of silver were examined with EDX. The average diameter of silver nanoparticles was about 25nm from Transmission Electron Microscopy (TEM). FTIR spectroscopy scrutinized the involvement of various functional groups during nanoparticle synthesis. The green synthesized nanoparticles presented effective antibacterial activity against pathogenic bacteria than AVLE alone. In-vitro antioxidant assays revealed that silver nanoparticles (AV-AgNPs) exhibited promising antioxidant properties. The nanoparticles also displayed a potent cytotoxic effect against HeLa and MCF-7 cell lines. In conclusion, the results supported the advantages of employing a bio-green approach for developing silver nanoparticles with antimicrobial, antioxidant, and antiproliferative activities in a simple and cost- competitive manner.

Development of silver nanoparticles loaded chitosan-alginate constructs with biomedical potentialities.

Herein, a facile biosynthesis of silver nanoparticles (AgNPs) and AgNPs-loaded chitosan-alginate constructs with biomedical potentialities is reported. The UV-vis spectroscopic profile confirmed the synthesis of AgNPs using methanolic leaves extract of Euphorbia helioscopia. The newly developed AgNPs were characterized using various analytical and imaging techniques including UV-vis and FT-IR spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), atomic force microscopy (AFM), and transmission electron microscopy (TEM). The optimally yielded AgNPs at 24h reaction period were loaded onto various chitosan-alginate constructs. A maximum of 95% loading efficiency (LE) was recorded with a chitosan: alginate ratio at 2:1, followed by 81% at 2:2 ratios. The anti-bacterial activities of AgNPs and AgNPs loaded chitosan-alginate constructs were tested against six bacterial strains i.e. Staphylococcus aureus, Pseudomonas aeruginosa, Klebsiella pneumoniae, Acinetobacter baumannii, Morganella morganii and Haemophilus influenza. A significant reduction in the log values was recorded for all test constructs, in comparison to the initial bacterial count (control value, i.e., 1.5×108 CFU/mL). The cytotoxicity profile revealed complete biocompatibility against normal cell line i.e. L929. Almost all constructs showed considerable cytotoxicity up to certain extant against human epithelial cells (HeLa) cancer cells. In summary, the highest antibacterial activities along with anti-cancer behavior both suggest the biomedical potentialities of newly engineered AgNPs and AgNPs-loaded chitosan-alginate constructs.