Nitric oxide-releasing multifunctional catechol-modified chitosan/oxidized dextran hydrogel with antibacterial, antioxidant, and pro-angiogenic properties for MRSA-infected diabetic wound healing.

The study presents a multifunctional catechol-modified chitosan (Chi-Ca)/oxidized dextran (Dex-CHO) hydrogel (CDP-PB) that possesses antibacterial, antioxidant, and pro-angiogenic properties, aimed at improving the healing of diabetic wounds. The achievement of the as-prepared CDP-PB hydrogel with superb antibacterial property (99.9 %) can be realized through the synergistic effect of phenylboronic acid-modified polyethyleneimine (PEI-PBA) and photothermal therapy (PTT) of polydopamine nanoparticles loaded with the nitric oxide (NO) donor BNN6 (PDA@BNN6). Notably, CDP-PB hydrogel achieves ∼3.6 log10 CFU/mL MRSA of inactivation efficiency under 808 nm NIR laser irradiation. In order to mitigate oxidative stress, the Chi-Ca was synthesized and afterward subjected to a reaction with Dex-CHO via a Schiff-base reaction. The catechol-containing hydrogel demonstrated its effectiveness in scavenging DPPH, •OH, and ABTS radicals (> 85 %). In addition, the cellular experiment illustrates the increased migration and proliferation of cells by the treatment of CDP-PB hydrogel in the presence of oxidative stress conditions. Moreover, the findings from the animal model experiments provide evidence that the CDP-PB hydrogel exhibited efficacy in the eradication of wound infection, facilitation of angiogenesis, stimulation of granulation, and augmentation of collagen deposition. These results indicate the potential of the CDP-PB hydrogel for use in clinical applications.

Convergence of resistance and evolutionary responses in Escherichia coli and Salmonella enterica co-inhabiting chicken farms in China.

Sharing of genetic elements among different pathogens and commensals inhabiting same hosts and environments has significant implications for antimicrobial resistance (AMR), especially in settings with high antimicrobial exposure. We analysed 661 Escherichia coli and Salmonella enterica isolates collected within and across hosts and environments, in 10 Chinese chicken farms over 2.5 years using data-mining methods. Most isolates within same hosts possessed the same clinically relevant AMR-carrying mobile genetic elements (plasmids: 70.6%, transposons: 78%), which also showed recent common evolution. Supervised machine learning classifiers revealed known and novel AMR-associated mutations and genes underlying resistance to 28 antimicrobials, primarily associated with resistance in E. coli and susceptibility in S. enterica. Many were essential and affected same metabolic processes in both species, albeit with varying degrees of phylogenetic penetration. Multi-modal strategies are crucial to investigate the interplay of mobilome, resistance and metabolism in cohabiting bacteria, especially in ecological settings where community-driven resistance selection occurs.

Machine learning and metagenomics reveal shared antimicrobial resistance profiles across multiple chicken farms and abattoirs in China.

China is the largest global consumer of antimicrobials and improving surveillance methods could help to reduce antimicrobial resistance (AMR) spread. Here we report the surveillance of ten large-scale chicken farms and four connected abattoirs in three Chinese provinces over 2.5 years. Using a data mining approach based on machine learning, we analysed 461 microbiomes from birds, carcasses and environments, identifying 145 potentially mobile antibiotic resistance genes (ARGs) shared between chickens and environments across all farms. A core set of 233 ARGs and 186 microbial species extracted from the chicken gut microbiome correlated with the AMR profiles of Escherichia coli colonizing the same gut, including Arcobacter, Acinetobacter and Sphingobacterium, clinically relevant for humans, and 38 clinically relevant ARGs. Temperature and humidity in the barns were also correlated with ARG presence. We reveal an intricate network of correlations between environments, microbial communities and AMR, suggesting multiple routes to improving AMR surveillance in livestock production.

Dissecting microbial communities and resistomes for interconnected humans, soil, and livestock.

A debate is currently ongoing as to whether intensive livestock farms may constitute reservoirs of clinically relevant antimicrobial resistance (AMR), thus posing a threat to surrounding communities. Here, combining shotgun metagenome sequencing, machine learning (ML), and culture-based methods, we focused on a poultry farm and connected slaughterhouse in China, investigating the gut microbiome of livestock, workers and their households, and microbial communities in carcasses and soil. For both the microbiome and resistomes in this study, differences are observed across environments and hosts. However, at a finer scale, several similar clinically relevant antimicrobial resistance genes (ARGs) and similar associated mobile genetic elements were found in both human and broiler chicken samples. Next, we focused on Escherichia coli, an important indicator for the surveillance of AMR on the farm. Strains of E. coli were found intermixed between humans and chickens. We observed that several ARGs present in the chicken faecal resistome showed correlation to resistance/susceptibility profiles of E. coli isolates cultured from the same samples. Finally, by using environmental sensing these ARGs were found to be correlated to variations in environmental temperature and humidity. Our results show the importance of adopting a multi-domain and multi-scale approach when studying microbial communities and AMR in complex, interconnected environments.

Time-Modulated Transmissive Programmable Metasurface for Low Sidelobe Beam Scanning.

Programmable metasurfaces have great potential for the implementation of low-complexity and low-cost phased arrays. Due to the difficulty of multiple-bit phase control, conventional programmable metasurfaces suffer a relatively high sidelobe level (SLL). In this manuscript, a time modulation strategy is introduced in the 1-bit transmissive programmable metasurface for reducing the SLLs of the generated patterns. After the periodic time modulation, harmonics are generated in each reconfigurable unit and the phase of the first-order harmonic can be dynamically controlled by applying different modulation sequences onto the corresponding unit. Through the high-speed modulation of the real-time periodic coding sequences on the metasurface by the programmable bias circuit, the equivalent phase shift accuracy to each metasurface unit can be improved to 6-bit and thus the SLLs of the metasurface could be reduced remarkably. The proposed time-modulated strategy is verified both numerically and experimentally with a transmissive programmable metasurface, which obtains an aperture efficiency over 34% and reduced SLLs of about -20 dB. The proposed design could offer a novel approach of a programmable metasurface framework for radar detection and secure communication applications.

Time-frequency joint mappings of a terahertz metasurface for multi-dimensional analysis of biological cells.

Traditional fast Fourier transform is used to extract the frequency component at the cost of losing the time domain, which is critical for metasurface biosensing. In this Letter, a more comprehensive algorithm, continuous wavelet transform (CWT), to process signals from THz time-domain spectroscopy is introduced. By comparing the metasurface-enhanced 2D time-frequency mappings (TFMs) of HaCaT and HSC3 cells, the two types of biological cells can be clearly differentiated, showing the great potential of CWT in the label-free recognition of biological cells. Also, the 2D TFMs serve as effective visualization indicators, successfully detecting the concentration of cancer cells characterized by being label free and low cost. In addition, the 2D TFMs of different metasurfaces under the same cell concentration reveal the correlation of TFMs and localized fields. Such a feature provides evidence of an interaction between biological cells and electromagnetic waves, implying the absorption of THz radiation by biological cells can be effectively controlled by properly designing split ring resonators (SRRs) of metasurfaces.

Terahertz meta-biosensor based on high-Q electrical resonance enhanced by the interference of toroidal dipole.

Electrical dipole resonances typically have low Q factor and broad resonant linewidth caused by strong free-space coupling with high radiative loss. Here, we present a strategy for enhancing the Q factor of the electrical resonance via the interference of a toroidal dipole. To validate such a strategy, a metasurface consisting of two resonators is designed that responsible to the electric and toroidal dipoles. According to constructive and destructive hybridizations of the two dipole modes, enhanced and decreased Q factors are found respectively for the two hybrid modes, compared to the one for the conventional electric dipole resonance. As a practical application of such high Q resonance, we further experimentally investigate the sensing performance of the metasurface biosensor by detecting the cell concentration of lung cancer cells (type A549). Moreover, through monitoring both resonance frequency and amplitude variation of the metasurface biosensor, the dielectric permittivity of the lung cancer cells is delicately estimated by the conjoint analysis of both simulated and measured results. Our proposed metasurface paves a promising way for the study of multipole interference in the field of nanophotonics and validates its effectiveness in biomedical sensing.

Whole-genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals, humans and environment in livestock farming.

Anthropogenic environments such as those created by intensive farming of livestock, have been proposed to provide ideal selection pressure for the emergence of antimicrobial-resistant Escherichia coli bacteria and antimicrobial resistance genes (ARGs) and spread to humans. Here, we performed a longitudinal study in a large-scale commercial poultry farm in China, collecting E. coli isolates from both farm and slaughterhouse; targeting animals, carcasses, workers and their households and environment. By using whole-genome phylogenetic analysis and network analysis based on single nucleotide polymorphisms (SNPs), we found highly interrelated non-pathogenic and pathogenic E. coli strains with phylogenetic intermixing, and a high prevalence of shared multidrug resistance profiles amongst livestock, human and environment. Through an original data processing pipeline which combines omics, machine learning, gene sharing network and mobile genetic elements analysis, we investigated the resistance to 26 different antimicrobials and identified 361 genes associated to antimicrobial resistance (AMR) phenotypes; 58 of these were known AMR-associated genes and 35 were associated to multidrug resistance. We uncovered an extensive network of genes, correlated to AMR phenotypes, shared among livestock, humans, farm and slaughterhouse environments. We also found several human, livestock and environmental isolates sharing closely related mobile genetic elements carrying ARGs across host species and environments. In a scenario where no consensus exists on how antibiotic use in the livestock may affect antibiotic resistance in the human population, our findings provide novel insights into the broader epidemiology of antimicrobial resistance in livestock farming. Moreover, our original data analysis method has the potential to uncover AMR transmission pathways when applied to the study of other pathogens active in other anthropogenic environments characterised by complex interconnections between host species.

Highly sensitive detection of malignant glioma cells using metamaterial-inspired THz biosensor based on electromagnetically induced transparency.

Metamaterial-inspired biosensors have been extensively studied recently years for fast and low-cost THz detection. However, only the variation of the resonance frequency has been closely concerned in such sensors so far, whiles the magnitude variation, which also provide important information of the analyte, has not been sufficiently analyzed. In this paper, by the observation of two degree of variations, we propose a label-free biosensing approach for molecular classification of glioma cells. The metamaterial biosensor consisting of cut wires and split ring resonators are proposed to realize polarization-independent electromagnetic induced transparency (EIT) at THz frequencies. Simulated results show that the EIT-like resonance experiences both resonance frequency and magnitude variations when the properties of analyte change, which is further explained with coupled oscillators model theory. The theoretical sensitivity of the biosensor is evaluated up to 496.01 GHz/RIU. In experiments, two types of glioma cells (mutant and wild-type) are cultured on the biosensor surface. The dependences of frequency shifts and the peak magnitude variations on the cells concentrations for different types give new perspective for molecular classification of glioma cells. The measured results indicate that the mutant and wild-type glioma cells can be distinguished directly by observing both the variations of EIT resonance frequency and magnitude at any cells concentrations without antibody introduction. Our metamaterial-based biosensor shows a great potential in the recognition of molecule types of glioma cells, opening alternative way to sensitive biosensing technology.

Complex Internal Microstructure of Feather Follicles on Chicken Skin Promotes the Bacterial Cross-Contamination of Carcasses During the Slaughtering Process.

Chicken skin is considered the most susceptible to bacterial contamination during slaughter. It is rich in bushy feather follicles with complex internal structures that can absorb bacteria via cross-contamination during slaughter. Until now, the microstructural changes and local bacterial composition of feather follicles during slaughter have not been thoroughly investigated. This study used hematoxylin-eosin (HE) staining of the tissue paraffin section to investigate the structure of the feather follicles on chicken skin. In addition, the biopsy sampling method was employed for the high-throughput sequencing of 16S RNA genes to study the composition and source of bacterial contamination during slaughter. The results show that the feather follicles on chicken skin form a closed cavity structure during the slaughtering process. The volume of the irregular follicle cavity was about Ø: 200 µm × D: 1040 µm, which provides a place for the bacteria to absorb and resist the cleaning and disinfection during the slaughtering process. The composition of bacteria in the feather follicle was mainly Acinetobacter (37%), Psychrobacter (8%), Macrococcus (5%), and Comamonas (2%). The heat map obtained via the species abundance analysis of the feather follicle samples as well as the slaughter environment samples suggests that the gastrointestinal feces contaminated the feather follicles on the chicken skin mainly during the evisceration, defeathering, and chilling processes, and the last-stage chilling water also caused severe cross-contamination to the feather follicles during the chilling process.

The Antibody-Free Recognition of Cancer Cells Using Plasmonic Biosensor Platforms with the Anisotropic Resonant Metasurfaces.

It is vital and promising for portable and disposable biosensing devices to achieve on-site detection and analysis of cancer cells. Although traditional labeling techniques provide an accurate quantitative measurement, the complicated cell staining and high-cost measurements limit their further development. Here, we demonstrate a nonimmune biosensing technology. The plasmonic biosensors, which are based on anisotropic resonant split ring resonators in the terahertz range, successfully realize the antibody-free recognition of cancer cells. The dependences of Δf and the fitted phase slope on the cancer cell concentration at different polarizations give new perspective in hexagonal radar maps. The results indicate that the lung cancer cell A549 and liver cancer cell HepG2 can be distinguished and determined simply based on the enclosed shapes in the radar maps without any antibody introduction. The minimum concentration of identification reduces to as low as 1 × 104 cells/mL and such identification can be kept valid in a wide range of cell concentration, ranging from 104 to 105. The construction of two-dimensional extinction intensity cards of corresponding cancer cells based on the wavelet transform method also supplies corresponding information for the antibody-free recognition and determination of two cancer cells. Our plasmonic metasurface biosensors show a great potential in the determination and recognition of label-free cancer cells, being an alternative to nonimmune biosensing technology.

A multiple mode integrated biosensor based on higher order Fano metamaterials.

A multiple mode integrated biosensor based on higher order Fano metamaterials (FRMMs) is proposed. The frequency shifts (Δf) of x-polarized quadrupolar (Qx), octupolar (Ox), hexadecapolar (Hx), y-polarized quadrupolar (Qy) and octupolar (Oy) Fano resonance modes are integrated to detect the concentration of lung cancer cells. In experiments, the concentrations of lung cancer cells can be distinguished by the shape and distribution of integrated graphics. In addition, an anomalous response in Δf in resonant mode is surprisingly observed. As the cell concentration increases, the Δf at the Qx-dip, Qy-dip and Oy-dip successively experiences an increasing frequency shift stage (IFSS), decreasing frequency shift stage (DFSS) and re-increasing frequency shift stage (RIFSS). The extraordinary DFSS confirmed by single-factor analysis of variance (ANOVA) means an unusual physical phenomenon in metamaterial biosensors. By introducing a new dielectric constant εf, we amend perturbation theory to explain the unusual phenomenon in Δf. With the change of the mode order from Qx to Hx, the εf increases from -2.78 to 0.75, which implies that the negative εf leads to the appearance of the DFSS. As a platform for biosensing, this study opens a new window from the perspective of multiple mode integration.

Enhanced photoluminescence and energy transfer performance of Y3Al4GaO12:Mn4+,Dy3+ phosphors for plant growth LED lights.

Plant growth LEDs have attracted broad attention in modern society, desperate for specific phosphors with a characteristic emission band. A novel Mn4+ and Dy3+ co-doped Y3Al4GaO12 phosphor were successfully prepared through a conventional high-temperature solid-state reaction. A three band emission including red (625-700 nm), orange (550-607 nm) and blue (462-490 nm) is observed in these phosphors when excited under a near-UV lamp, which is ascribed to 2E → 4A2 of Mn4+, 4F9/2 → 6H15/2 and 4F9/2 → 6H13/2 of Dy3+, respectively. The three emissions match the absorption spectra of chlorophyll A and chlorophyll B well. Meanwhile, the energy transfer from Dy3+ to Mn4+ was confirmed by the luminescence spectra and lifetime analysis. Finally, an LED device was fabricated that consisted of a 365 nm ultraviolet chip and the Y3Al4GaO12:Mn4+,Dy3+ phosphor. The excellent properties indicate that the synthesized phosphor has a promising application in the optical agricultural industry.

The terahertz electromagnetically induced transparency-like metamaterials for sensitive biosensors in the detection of cancer cells.

A kind of novel biosensor based on the electromagnetic induced transparency like (EIT-like) metamaterials (MMs) have been proposed. It demonstrates that the symmetry-breaking double-splits ring resonators can realize the EIT-like plasmonic resonance, the according transparency window occurs at 1.67 THz. The coupled oscillators model illustrates that with the increase of asymmetry degree of double splits, the coupling between bright and dark mode is enhanced. Consequently, the non-radiative damping γ2 grows from 1.45 to 1.85 THz and coupling coefficient κ from 3.46 to 4.49 THz2, while the radiative damping γ1 decreases from 11.5 to 9 THz. Such EIT-like MMs were evaluated in simulation as the refractive index sensors, which the theoretical sensitivity was calculated to 455.7 GHz/RIU (RIU, Refractive Index Unit) under 11 µm-thick analyte layer. Meanwhile, the dependence of full width at half maximum (FWHM) on analyte thickness was also studied. In experiments, it is found that the frequency shift Δf increases from 50 to 90 GHz when the oral cancer cells (HSC3) concentration improves from 1 × 105 to 7 × 105 cells/ml. The maximum experimental sensitivity approaches 900 kHz/cell ml-1 at 7 × 105 cells/ml. Additionally, the apoptosis of cancer cells under the effect of anti-cancer drug was investigated. It shows that with the increase of anti-cancer drug concentration from 1 to 15 µM and the extension of drug action duration from 24 to 72 h, the Δf changes from 140 to 70 GHz and 140-40 GHz, respectively. Besides, the corresponding FWHM also increases from 237.9 to 305.4 GHz and 237.8-337.6 GHz. The results measured by MMs biosensors and biological method exhibit a relatively good agreement, showing a great potential for cells measurement with the sensitive biosensors based on the EIT-like MMs.

Aluminum toxicity related to SOD and expression of presenilin and CREB in Bombyx mori.

Aluminum (Al) is an important environmental metal factor that can be potentially associated with pathological changes leading to neurotoxicity. The silkworm, Bombyx mori, is an important economic insect and has also been used as a model organism in various research areas. However, the toxicity of Al on silkworm physiology has not been reported. Here, we comprehensively investigate the toxic effects of Al on the silkworm, focusing on its effects on viability and development, superoxide dismutase (SOD) activity, and the expression of presenilin and cAMP response element-binding protein (CREB) in BmE cells and silkworm larvae. BmE cell viability decreased after treatment with aluminum chloride (AlCl3 ) in both dose- and time-dependent manners. When AlCl3 solution was injected into newly hatched fifth instar larvae, both larval weight gain and survival rate were significantly decreased in a manner correlating with AlCl3 dose and developmental stage. Furthermore, when BmE cells and silkworm larvae were exposed to AlCl3 , SOD activity decreased significantly relative to the control group, whereas presenilin expression increased more than twofold. Additionally, CREB and phosphorylated CREB (p-CREB) expression in the heads of fifth instar larvae decreased by 28.0% and 50.0%, respectively. These results indicate that Al inhibits the growth and development of silkworms in vitro and in vivo, altering SOD activity and the expressions of presenilin, CREB, and p-CREB. Our data suggest that B. mori can serve as a model animal for studying Al-induced neurotoxicity or neurodegeneration.

Whole-Genome Sequence of Streptococcus parauberis Strain SP-llh, Isolated from Cows with Mastitis in Western China.

Streptococcus parauberis strain SP-llh was isolated from cows with mastitis in western China in 2015. The 2,522,235-bp genome sequence consists of 46 large contigs in 14 scaffolds and contains 2,620 predicted protein-coding genes, with a G+C content of 35.3%.

[Research on Rapid and Non-Destructive Identification of Aging Wheat Based on ATR-Terahertz Spectroscopy Combined with PLS-DA].

In this research, the terahertz spectra data of the aging wheat processed under manual control environment by ATR accessory were collected. After the data diversity based on the composite score by PCA, the non-destructive identification models of aging wheat were developed by PLS-DA algorithm. The results showed that for the absorption coefficient spectrum, the accuracy of the experimental group, control group of the calibration set and cross validation set were 84.2%, 94.7%, 84.2% and 81.6% respectively, while the accuracy of the experimental group and control group of the external validation set were 73.7% and 100.0% respectively; for the refractive index spectrum, the accuracy of the experimental group, control group of the calibration set and cross validation set were 84.2%, 92.0%, 76.3% and 76.3% respectively, while the accuracy of the experimental group and control group of the external validation set were 84.2% and 89.5% respectively. The research indicates that ATR-THz technology should be of great potentials in the application in the non-destructive identification of aging wheat.