The role of cannabinoid receptor 2 in bone remodeling during orthodontic tooth movement.

BACKGROUND: The purpose of this study is to explore the effects of CB2 on bone regulation during orthodontic tooth movement. METHODS: Thirty male mice were allocated into 2 groups (n = 15 in each group): wild type (WT) group and CB2 knockout (CB2-/-) group. Orthodontic tooth movement (OTM) was induced by applying a nickel-titanium coil spring between the maxillary first molar and the central incisors. There are three subgroups within the WT groups (0, 7 and 14 days) and the CB2-/- groups (0, 7 and 14 days). 0-day groups without force application. Tooth displacement, alveolar bone mass and alveolar bone volume were assessed by micro-CT on 0, 7 and 14 days, and the number of osteoclasts was quantified by tartrate-resistant acid phosphatase (TRAP) staining. Moreover, the expression levels of RANKL and OPG in the compression area were measured histomorphometrically. RESULTS: The WT group exhibited the typical pattern of OTM, characterized by narrowed periodontal space and bone resorption on the compression area. In contrast, the accelerated tooth displacement, increased osteoclast number (P < 0.0001) and bone resorption on the compression area in CB2-/- group. Additionally, the expression of RANKL was significantly upregulated, while OPG showed low levels in the compression area of the CB2 - / - group (P < 0.0001). CONCLUSIONS: CB2 modulated OTM and bone remodeling through regulating osteoclast activity and RANKL/OPG balance.

Improved performance of InGaAs/AlGaAs quantum well lasers on silicon using InAlAs trapping layers.

InGaAs/AlGaAs multiple quantum well lasers grown on silicon (001) by molecular beam epitaxy have been demonstrated. By inserting InAlAs trapping layers into AlGaAs cladding layers, misfit dislocations easily located in the active region can be effectively transferred out of the active region. For comparison, the same laser structure without the InAlAs trapping layers was also grown. All these as-grown materials were fabricated into Fabry-Perot lasers with the same cavity size of 20 × 1000 µm2. The laser with trapping layers achieved a 2.7-fold reduction in threshold current density under pulsed operation (5 µs-pulsed width, 1%-duty cycle) compared to the counterpart, and further realized a room-temperature continuous-wave lasing with a threshold current of 537 mA which corresponds to a threshold current density of 2.7 kA/cm2. When the injection current reached 1000 mA, the single-facet maximum output power and slope efficiency were 45.3 mW and 0.143 W/A, respectively. This work demonstrates significantly improved performances of InGaAs/AlGaAs quantum well lasers monolithically grown on silicon, providing a feasible solution to optimize the InGaAs quantum well structure.

Diabetic Plantar Foot Segmentation in Active Thermography Using a Two-Stage Adaptive Gamma Transform and a Deep Neural Network.

Pathological conditions in diabetic feet cause surface temperature variations, which can be captured quantitatively using infrared thermography. Thermal images captured during recovery of diabetic feet after active cooling may reveal richer information than those from passive thermography, but diseased foot regions may exhibit very small temperature differences compared with the surrounding area, complicating plantar foot segmentation in such cold-stressed active thermography. In this study, we investigate new plantar foot segmentation methods for thermal images obtained via cold-stressed active thermography without the complementary information from color or depth channels. To better deal with the temporal variations in thermal image contrast when planar feet are recovering from cold immersion, we propose an image pre-processing method using a two-stage adaptive gamma transform to alleviate the impact of such contrast variations. To improve upon existing deep neural networks for segmenting planar feet from cold-stressed infrared thermograms, a new deep neural network, the Plantar Foot Segmentation Network (PFSNet), is proposed to better extract foot contours. It combines the fundamental U-shaped network structure, a multi-scale feature extraction module, and a convolutional block attention module with a feature fusion network. The PFSNet, in combination with the two-stage adaptive gamma transform, outperforms multiple existing deep neural networks in plantar foot segmentation for single-channel infrared images from cold-stressed infrared thermography, achieving an accuracy of 97.3% and 95.4% as measured by Intersection over Union (IOU) and Dice Similarity Coefficient (DSC) respectively.

Joint reconstruction of neuron and ultrastructure via connectivity consensus in electron microscope volumes.

BACKGROUND: Nanoscale connectomics, which aims to map the fine connections between neurons with synaptic-level detail, has attracted increasing attention in recent years. Currently, the automated reconstruction algorithms in electron microscope volumes are in great demand. Most existing reconstruction methodologies for cellular and subcellular structures are independent, and exploring the inter-relationships between structures will contribute to image analysis. The primary goal of this research is to construct a joint optimization framework to improve the accuracy and efficiency of neural structure reconstruction algorithms. RESULTS: In this investigation, we introduce the concept of connectivity consensus between cellular and subcellular structures based on biological domain knowledge for neural structure agglomeration problems. We propose a joint graph partitioning model for solving ultrastructural and neuronal connections to overcome the limitations of connectivity cues at different levels. The advantage of the optimization model is the simultaneous reconstruction of multiple structures in one optimization step. The experimental results on several public datasets demonstrate that the joint optimization model outperforms existing hierarchical agglomeration algorithms. CONCLUSIONS: We present a joint optimization model by connectivity consensus to solve the neural structure agglomeration problem and demonstrate its superiority to existing methods. The intention of introducing connectivity consensus between different structures is to build a suitable optimization model that makes the reconstruction goals more consistent with biological plausible and domain knowledge. This idea can inspire other researchers to optimize existing reconstruction algorithms and other areas of biological data analysis.

Multi-focus image fusion method using energy of Laplacian and a deep neural network.

Multi-focus image fusion consists in the integration of the focus regions of multiple source images into a single image. At present, there are still some common problems in image fusion methods, such as block artifacts, artificial edges, halo effects, and contrast reduction. To address these problems, a novel, to the best of our knowledge, multi-focus image fusion method using energy of Laplacian and a deep neural network (DNN) is proposed in this paper. The DNN is composed of multiple denoising autoencoders and a classifier. The Laplacian energy operator can effectively extract the focus information of source images, and the trained DNN model can establish a valid mapping relationship between source images and a focus map according to the extracted focus information. First, the Laplacian energy operator is used to perform focus measurement for two source images to obtain the corresponding focus information maps. Then, the sliding window technology is used to sequentially obtain the windows from the corresponding focus information map, and all of the windows are fed back to the trained DNN model to obtain a focus map. After binary segmentation and small region filtering, a final decision map with good consistency is obtained. Finally, according to the weights provided by the final decision map, multiple source images are fused to obtain a final fusion image. Experimental results demonstrate that the proposed fusion method is superior to other existing ones in terms of subjective visual effects and objective quantitative evaluation.

Antifungal Effects and Potential Mechanism of Essential Oils on Collelotrichum gloeosporioides In Vitro and In Vivo.

The development of natural essential oil as an alternative to synthetic chemicals in the control of postharvest decay is currently in the spotlight. In the present study, the efficacy of seven essential oils in suppressing Collelotrichum gloeosporioides identified from sweet cherry was evaluated in vitro and clove oil was proved to be the most promising inhibitor. Thus, the antifungal properties and potential mechanisms of clove oil in vitro and in vivo by fumigation and contact treatments were intensively investigated. For C. gloeosporioides, the minimal inhibitory concentrations (MIC) of clove oil in air and contact phase were 80 and 300 µL/L in vitro testing, respectively. Based on the radial growth of C. gloeosporioides mycelium in medium, the fumgitoxic ability of essential oil was observed in a dose-dependent manner, which was not as dramatic as that under in vivo conditions. Furthermore, scanning electron microscopy and transmission electron microscopy of C. gloeosporioides exposed to clove oil exhibited obviously deleterious morphological and ultrastructural alterations confirming the disruption of fungal cell wall and endomembrane system, which resulted in increasing in permeability and causing the loss of intracellular constituents. In future, essential oils, combined with nano-emulsification approaches, could be good candidates as safe and effective antifungal agents for fungal spoilage of fresh commodities.

Effects of diurnal temperature range on mortality in Hefei city, China.

Although several studies indicated an association between diurnal temperature range (DTR) and mortality, the results about modifiers are inconsistent, and few studies were conducted in developing inland country. This study aims to evaluate the effects of DTR on cause-specific mortality and whether season, gender, or age might modify any association in Hefei city, China, during 2007-2016. Quasi-Poisson generalized linear regression models combined with a distributed lag non-linear model (DLNM) were applied to evaluate the relationships between DTR and non-accidental, cardiovascular, and respiratory mortality. We observed a J-shaped relationship between DTR and cause-specific mortality. With a DTR of 8.3 °C as the reference, the cumulative effects of extremely high DTR were significantly higher for all types of mortality than effects of lower or moderate DTR in full year. When stratified by season, extremely high DTR in spring had a greater impact on all cause-specific mortality than other three seasons. Male and the elderly (≥ 65 years) were consistently more susceptible to extremely high DTR effect than female and the youth (< 65 years) for non-accidental and cardiovascular mortality. To the contrary, female and the youth were more susceptible to extremely high DTR effect than male and the elderly for respiratory morality. The study suggests that extremely high DTR is a potential trigger for non-accidental mortality in Hefei city, China. Our findings also highlight the importance of protecting susceptible groups from extremely high DTR especially in the spring.

Mixed Responses to Systemic Therapy Revealed Potential Genetic Heterogeneity and Poor Survival in Patients with Non-Small Cell Lung Cancer.

BACKGROUND: A subset of patients with non-small cell lung cancer (NSCLC) fosters mixed responses (MRs) to epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) or chemotherapy. However, little is known about the clinical and molecular features or the prognostic significance and potential mechanisms. METHODS: The records of 246 consecutive patients with NSCLC receiving single-line chemotherapy or TKI treatment and who were assessed by baseline and interim positron emission tomography/computed tomography scans were collected retrospectively. The clinicopathological correlations of the MR were analyzed, and a multivariate analysis was performed to explore the prognostic significance of MR. RESULTS: The overall incidence of MR to systemic therapy was 21.5% (53/246) and predominated in patients with stage IIIB-IV, EGFR mutations and those who received TKI therapy (p < .05). Subgroup analyses based on MR classification (efficacious versus inefficacious) showed significant differences in subsequent treatment between the two groups (p < .001) and preferable progression-free survival (PFS) and overall survival (OS) in the efficacious MR group. Multivariate analyses demonstrated that the presence of MR was an independent unfavorable prognostic factor for PFS (hazard ratio [HR], 1.474; 95% confidence interval [CI], 1.018-2.134; p = .040) and OS (HR, 1.849; 95% CI, 1.190-2.871; p = .006) in patients with NSCLC. Induced by former systemic therapy, there were more T790M (18%), concomitant EGFR mutations (15%), and changes to EGFR wild type (19%) in the MR group among patients with EGFR mutations, which indicated higher incidence of genetic heterogeneity. CONCLUSION: MR was not a rare event in patients with NSCLC and tended to occur in those with advanced lung adenocarcinoma treated with a TKI. MR may result from genetic heterogeneity and is an unfavorable prognostic factor for survival. Further studies are imperative to explore subsequent treatment strategies. The Oncologist 2017;22:61-69Implications for Practice: Tumor heterogeneity tends to produce mixed responses (MR) to systemic therapy, including TKI and chemotherapy; however, the clinical significance and potential mechanisms are not fully understood, and the subsequent treatment after MR is also a clinical concern. The present study systemically assessed patients by PET/CT and differentiated MR and therapies. The study identified a relatively high incidence of MR in patients with advanced NSCLC, particularly those treated with targeted therapies. An MR may be an unfavorable prognostic factor and originate from genetic heterogeneity. Further studies are imperative to explore subsequent treatment strategies.

Health condition assessment for vegetation exposed to heavy metal pollution through airborne hyperspectral data.

Recent advancements in hyperspectral remote sensing technology now provide improved diagnostic capabilities to assess vegetation health conditions. This paper uses a set of 13 vegetation health indices related to chlorophyll, xanthophyll, blue/green/red ratio and structure from airborne hyperspectral reflectance data collected around a derelict mining area in Yerranderie, New South Wales, Australia. The studied area has ten historic mine shafts with a legacy of heavy metals and acidic contamination in a pristine ecosystem now recognised as Great Blue Mountain World Heritage Area. The forest is predominantly comprised of different species of Eucalyptus trees. In addition to the airborne survey, ground-based spectra of the tree leaves were collected along the two accessible heavy metal contaminated pathways. The stream networks in the area were classified and the geospatial patterns of vegetation health were analysed along the Tonalli River, a major water tributary flowing through the National Park. Despite the inflow of contaminated water from the near-mine streams, the measured vegetation health indices along Tonalli River were found to remain unchanged. The responses of the vegetation health indices between the near-mine and away-mine streams were found similar. Based on the along-stream and inter-stream analysis of the spectral indices of vegetation health, no significant impact of the heavy metal pollution could be noticed. The results indicate the possibility of the vegetation having developed immunity towards the high levels of heavy metal pollution over a century of exposure.

Structure and Optimum Luminescence for Nearly Block-Like LaOCl:Eu3+ Nanoparticles.

In this work, we report a simple method for the synthesis of block-like Eu3+ doping LaOCl nanophosphors with different doping content. It was found that the average grain diameter of Eu3+ doping LaOCl samples decreased with increasing Eu3+ doping concentration. The lattice volume shrinked due to different response for different axial under high pressure that led to lower lattice symmetry of LaOCl:Eu3+. The emission of LaOCI:Eu3+ increased with the increasing Eu3+ concentration due to the lower local symmetry, which also led to a gradual reduction in lifetime.

DeepMulticut: Deep Learning of Multicut Problem for Neuron Segmentation from Electron Microscopy Volume.

Superpixel aggregation is a powerful tool for automated neuron segmentation from electron microscopy (EM) volume. However, existing graph partitioning methods for superpixel aggregation still involve two separate stages-model estimation and model solving, and therefore model error is inherent. To address this issue, we integrate the two stages and propose an end-to-end aggregation framework based on deep learning of the minimum cost multicut problem called DeepMulticut. The core challenge lies in differentiating the NPhard multicut problem, whose constraint number is exponential in the problem size. With this in mind, we resort to relaxing the combinatorial solver-the greedy additive edge contraction (GAEC)-to a continuous Soft-GAEC algorithm, whose limit is shown to be the vanilla GAEC. Such relaxation thus allows the DeepMulticut to integrate edge cost estimators, Edge-CNNs, into a differentiable multicut optimization system and allows a decision-oriented loss to feed decision quality back to the Edge-CNNs for adaptive discriminative feature learning. Hence, the model estimators, Edge-CNNs, can be trained to improve partitioning decisions directly while beyond the NP-hardness. Also, we explain the rationale behind the DeepMulticut framework from the perspective of bi-level optimization. Extensive experiments on three public EM datasets demonstrate the effectiveness of the proposed DeepMulticut.

A robust transformer-based pipeline of 3D cell alignment, denoise and instance segmentation on electron microscopy sequence images.

Germline cells are critical for transmitting genetic information to subsequent generations in biological organisms. While their differentiation from somatic cells during embryonic development is well-documented in most animals, the regulatory mechanisms initiating plant germline cells are not well understood. To thoroughly investigate the complex morphological transformations of their ultrastructure over developmental time, nanoscale 3D reconstruction of entire plant tissues is necessary, achievable exclusively through electron microscopy imaging. This paper presents a full-process framework designed for reconstructing large-volume plant tissue from serial electron microscopy images. The framework ensures end-to-end direct output of reconstruction results, including topological networks and morphological analysis. The proposed 3D cell alignment, denoise, and instance segmentation pipeline (3DCADS) leverages deep learning to provide a cell instance segmentation workflow for electron microscopy image series, ensuring accurate and robust 3D cell reconstructions with high computational efficiency. The pipeline involves five stages: the registration of electron microscopy serial images; image enhancement and denoising; semantic segmentation using a Transformer-based neural network; instance segmentation through a supervoxel-based clustering algorithm; and an automated analysis and statistical assessment of the reconstruction results, with the mapping of topological connections. The 3DCADS model's precision was validated on a plant tissue ground-truth dataset, outperforming traditional baseline models and deep learning baselines in overall accuracy. The framework was applied to the reconstruction of early meiosis stages in the anthers of Arabidopsis thaliana, resulting in a topological connectivity network and analysis of morphological parameters and characteristics of cell distribution. The experiment underscores the 3DCADS model's potential for biological tissue identification and its significance in quantitative analysis of plant cell development, crucial for examining samples across different genetic phenotypes and mutations in plant development. Additionally, the paper discusses the regulatory mechanisms of Arabidopsis thaliana's germline cells and the development of stamen cells before meiosis, offering new insights into the transition from somatic to germline cell fate in plants.

Whole-genome analysis of Escherichia coli isolated from wild Amur tiger (Panthera tigris altaica) and North China leopard (Panthera pardus japonensis).

Background: Escherichia coli is an important intestinal flora, of which pathogenic E. coli is capable of causing many enteric and extra-intestinal diseases. Antibiotics are essential for the treatment of bacterial infections caused by pathogenic E. coli; however, with the widespread use of antibiotics, drug resistance in E. coli has become particularly serious, posing a global threat to human, animal, and environmental health. While the drug resistance and pathogenicity of E. coli carried by tigers and leopards in captivity have been studied intensively in recent years, there is an extreme lack of information on E. coli in these top predators in the wild environment. Methods: Whole genome sequencing data of 32 E. coli strains collected from the feces of wild Amur tiger (Panthera tigris altaica, n = 24) and North China leopard (Panthera pardus japonensis, n = 8) were analyzed in this article. The multi-locus sequence types, serotypes, virulence and resistance genotypes, plasmid replicon types, and core genomic SNPs phylogeny of these isolates were studied. Additionally, antimicrobial susceptibility testing (AST) was performed on these E. coli isolates. Results: Among the E. coli isolates studied, 18 different sequence types were identified, with ST939 (21.9%), ST10 (15.6%), and ST3246 (9.4%) being the most prevalent. A total of 111 virulence genes were detected, averaging about 54 virulence genes per sample. They contribute to invasion, adherence, immune evasion, efflux pump, toxin, motility, stress adaption, and other virulence-related functions of E. coli. Sixty-eight AMR genes and point mutations were identified. Among the detected resistance genes, those belonging to the efflux pump family were the most abundant. Thirty-two E. coli isolates showed the highest rate of resistance to tetracycline (14/32; 43.8%), followed by imipenem (4/32; 12.5%), ciprofloxacin (3/32; 9.4%), doxycycline (2/32; 6.3%), and norfloxacin (1/32; 3.1%). Conclusions: Our results suggest that E. coli isolates carried by wild Amur tigers and North China leopards have potential pathogenicity and drug resistance.

Nanocrystalline diamond matrix deposited on copper substrate by radical species restricted diffusion.

Nanocrystalline diamond matrix (or patterned nanocrystalline diamond) have been grown by hot filament chemical vapor deposition (HFCVD) on copper substrates, which were masked by a copper template filled with through-holes. The influence of the mixing ratio for CH4/H2 source gases, total gas pressure and the aspect ratio (the ratio of hole depth to its diameter) on the morphology, grain size and quality of diamond films were investigated. Continuous diamond films were obtained under 2.0 kpa. When increasing the aspect ratio from 0.67 to 2.0, a gradual reduction of diamond grain size from micrometer to nanometers scale was observed. The formation of nanocrystalline diamond (NCD) matrix can be attributed to the restricted diffusion of radical species and the diamond nucleation kinetics on copper substrates. By through-holes of templates on copper substrates to restrict the diffusion and transport of radical species, NCD matrix was successfully deposited on copper substrates.

Cinnamon essential oil vapor alleviates the reduction of aroma-related volatiles in cold-stored "Feicheng" peach using HS-GC-IMS.

"Feicheng" peach is popular for its unique aroma, but its defect of being highly sensitive to chilling injury (CI) often leads to aroma loss and internal browning. Essential oils (EOs) are often used to enhance the antioxidant capacity of plants and fruits, as well as to trigger their defense against biotic/abiotic stresses. This study aimed to examine the effect of cinnamon essential oil (CEO) vapor treatment on the aroma quality of peach fruit during cold storage using HS-GC-IMS. The results showed that 50 µL/L CEO vapor reduced the severity of internal browning (IB) in peaches at the stage of 7 ~ 21 d during refrigeration (Significantly, the L* value was higher and the IB index was lower than that of control, p < 0.05). Meanwhile, the evident reduction or loss of aroma content caused by CI was restored to a higher level than the control (p < 0.05). Furthermore, CEO treatment promoted the release of aroma-related volatiles as evidenced by more propyl acetate, and the dimer of amyl acetate, isoamyl acetate, butyl acetate detected than that on harvest day and no-treated group after 21 d of cold storage plus 2 d of shelf life. Genes of PpLOX1, PpLOX2, PpHPL1 and PpADH1 associated with aroma-related volatile biosynthesis revealed higher transcript abundance in peach fruits treated with CEO than the control (p < 0.05). Overall, our study demonstrated that CEO in vapor phase may be beneficial to alleviate the quality deterioration in aroma and flesh color of "Feicheng" peaches caused by CI, which lays a theoretical reference for maintaining postharvest quality of peach fruits.

Inhibitory effect and underlying mechanism of cinnamon and clove essential oils on Botryosphaeria dothidea and Colletotrichum gloeosporioides causing rots in postharvest bagging-free apple fruits.

Bagging-free apple is more vulnerable to postharvest disease, which severely limits the cultivation pattern transformation of the apple industry in China. This study aimed to ascertain the dominant pathogens in postharvest bagging-free apples, to evaluate the efficacy of essential oil (EO) on inhibition of fungal growth, and to further clarify the molecular mechanism of this action. By morphological characteristics and rDNA sequence analyses, Botryosphaeria dothidea (B. dothidea) and Colletotrichum gloeosporioides (C. gloeosporioides) were identified as the main pathogens isolated from decayed bagging-free apples. Cinnamon and clove EO exhibited high inhibitory activities against mycelial growth both in vapor and contact phases under in vitro conditions. EO vapor at a concentration of 60 µL L-1 significantly reduced the incidence and lesion diameter of inoculated decay in vivo. Observations using a scanning electron microscope (SEM) and transmission electron microscope (TEM) revealed that EO changed the mycelial morphology and cellular ultrastructure and destroyed the integrity and structure of cell membranes and major organelles. Using RNA sequencing and bioinformatics, it was demonstrated that clove EO treatment impaired the cell membrane integrity and biological function via downregulating the genes involved in the membrane component and transmembrane transport. Simultaneously, a stronger binding affinity of trans-cinnamaldehyde and eugenol with CYP51 was assessed by in silico analysis, attenuating the activity of this ergosterol synthesis enzyme. Moreover, pronounced alternations in the oxidation/reduction reaction and critical materials metabolism of clove EO-treated C. gloeosporioides were also observed from transcriptomic data. Altogether, these findings contributed novel antimicrobial cellular and molecular mechanisms of EO, suggesting its potential use as a natural and useful preservative for controlling postharvest spoilage in bagging-free apples.

Self-Cross-Linked Chitosan/Albumin-Bound Nanoparticle Hydrogel for Inhibition of Postsurgery Malignant Glioma Recurrence.

The development of chemoimmunotherapy with reduced systemic toxicity using local formulations is an effective strategy for combating tumor recurrence. Herein, we reported a localized hydrogel system for antitumor chemoimmunotherapy, formed by doxorubicin (DXR)-loaded bovine serum albumin (BSA) nanoparticles self-cross-linked with natural polysaccharide chitosan (CS). The drug-loaded hydrogel (DXR-CBGel) with antiswelling performance and prolonged drug-release profile was combined with antiprogrammed cell death protein 1 (aPD-1) as an in situ vaccine for treating glioblastoma multiforme (GBM) lesions. The antiswelling hydrogel system shows excellent biosafety for volume-sensitive GBM lesions. Both the albumin-bound formulation and the in situ gelation design facilitate the local retention and sustained release of DXR to generate long-term chemoimmunotherapy with reduced systemic toxicity. The chemotherapy-induced immunogenic cell death of DXR with the assistance of immunotherapeutic CS can trigger tumor-specific immune responses, which are further amplified by an immune checkpoint blockade to effectively inhibit cancer recurrence. The strategy of combining albumin-bound drug formulation and biocompatible polymer-based hydrogel for localized chemoimmunotherapy shows great potential against postsurgery glioblastoma recurrence.

High-Precision Ultra-Long Air Slit Fabrication Based on MEMS Technology for Imaging Spectrometers.

The increasing demand for accurate imaging spectral information in remote sensing detection has driven the development of hyperspectral remote sensing instruments towards a larger view field and higher resolution. As the core component of the spectrometer slit, the designed length reaches tens of millimeters while the precision maintained within the µm level. Such precision requirements pose challenges to traditional machining and laser processing. In this paper, a high-precision air slit was created with a large aspect ratio through MEMS technology on SOI silicon wafers. In particular, a MEMS slit was prepared with a width of 15 µm and an aspect ratio exceeding 4000:1, and a spectral spectroscopy system was created and tested with a Hg-Cd light source. As a result, the spectral spectrum was linear within the visible range, and a spectral resolution of less than 1 nm was obtained. The standard deviation of resolution is only one-fourth of that is seen in machined slits across various view fields. This research provided a reliable and novel manufacturing technique for high-precision air slits, offering technical assistance in developing high-resolution wide-coverage imaging spectrometers.

A graphene oxide-loaded processed pyritum composite hydrogel for accelerated bone regeneration via mediation of M2 macrophage polarization.

A coordinated interaction between osteogenesis and the osteoimmune microenvironment plays a vital role in regulating bone healing. However, disturbances in the pro- and anti-inflammatory balance hinder the therapeutic advantages of biomaterials. In this study, a novel composite hydrogel was successfully fabricated using graphene oxide (GO)-loaded processed pyritum (PP) in combination with poly(ethylene glycol) diacrylate (PEGDA) and carboxymethyl chitosan (CMC). Subsequently, the immunomodulatory effects and bone regenerative potential of PP/GO@PEGDA/CMC were investigated. The results demonstrated that the PP/GO@PEGDA/CMC hydrogel possessed excellent mechanical properties, swelling capacity, and stability. Moreover, PP/GO@PEGDA/CMC prominently promoted M2 polarization and increased the levels of anti-inflammatory factors (interleukin (IL)-4, IL-10, and transforming growth factor-ß). These beneficial effects facilitated the proliferation and osteogenic differentiation of bone marrow mesenchymal stem cells in vitro. Additionally, the in vivo results further verified that the implantation of PP/GO@PEGDA/CMC markedly reduced local inflammation while enhancing bone regeneration at 8 weeks post-implantation. Therefore, the results of this study provide potential therapeutic strategies for bone tissue repair and regeneration by modulating the immune microenvironment.

Two suppressors of RNA silencing encoded by cereal-infecting members of the family Luteoviridae.

Several members of the family Luteoviridae are important pathogens of cultivated plant species of the family Gramineae. In this study, we explored RNA-silencing suppressors (RSSs) encoded by two cereal-infecting luteoviruses: barley yellow dwarf virus and wheat yellow dwarf virus (BYDV and WYDV, respectively). The P0 protein of WYDV-GPV (P0(GPV)) and the P6 protein of BYDV-GAV (P6(GAV)) displayed RSS activities when expressed in agro-infiltrated leaves of Nicotiana benthamiana, by their local ability to inhibit post-transcriptional gene silencing of GFP. Analysis of GFP, mRNA and GFP-specific small interfering RNA indicated that both P0(GPV) and P6(GAV) are suppressors of silencing that can restrain not only local but also systemic gene silencing. This is the first report of RSS activity of the P6 protein in a member of the genus Luteovirus.