AIBI Modified Mesoporous Copper Sulfide Nanocomposites for Efficient Non-Oxygen Dependent Free Radicals-Assisted Photothermal Therapy in Uveal Melanoma.

Uveal melanoma (UM) is an ocular cancer predominantly affecting adults, characterized by challenging diagnostic outcomes. This research endeavors to develop an innovative multifunctional nanocomposite system sensitive to near-infrared (NIR) radiation, serving as both a non-oxygen free-radical generator and a photothermal agent. The designed system combines azobis isobutyl imidazoline hydrochloride (AIBI) with mesoporous copper sulfide (MCuS) nanoparticles. MCuS harnesses NIR laser energy to induce photothermal therapy, converting light energy into heat to destroy cancer cells. Simultaneously, AIBI is activated by the NIR laser to produce alkyl radicals, which induce DNA damage in remaining cancer cells. This distinctive feature equips the designed system to selectively eliminate cancers in the hypoxic tumor microenvironment. MCuS is also beneficial to scavenge the overexpressed glutathione (GSH) in the tumor microenvironment. GSH generally consumes free radicals and hiders the PDT effect. To enhance control over AIBI release in cancer cells, 1-tetradecyl alcohol (TD), a phase-changing material, is introduced onto the surface of MCuS nanoparticles to create the final AMPT nanoparticle system. In vitro and in vivo experiments confirm the remarkable anti-tumor efficacy of AMPT. Notably, the study introduces an orthotopic tumor model for UM, demonstrating the feasibility of precise and effective targeted treatment within the ocular system.

Adjusting Catalytic Activity of ß-Amyrin Synthase GgBAS by Utilizing the Plasticity Residues of an Active Site.

ß-Amyrin synthase (bAS) is a representative plant oxidosqualene cyclase (OSC), and previous studies have identified many functional residues and mutants that can alter its catalytic activity. However, the regulatory mechanism of the active site architecture for adjusting the catalytic activity remains unclear. In this study, we investigate the function of key residues and their regulatory effects on the catalytic activity of Glycyrrhiza glabra ß-amyrin synthase (GgbAS) through molecular dynamics simulations and site-directed mutagenesis experiments. We identified the plasticity residues located in two active site regions and explored the interactions between these residues and tetracyclic/pentacyclic intermediates. Based on computational and experimental results, we further categorize these plasticity residues into three types: effector, adjuster, and supporter residues, according to their functions in the catalytic process. This study provides valuable insights into the catalytic mechanism and active site plasticity of GgbAS, offering important references for the rational enzyme engineering of other OSC enzyme.

Inversion Method for Chlorophyll-a Concentration in High-Salinity Water Based on Hyperspectral Remote Sensing Data.

As one of the important lakes in the "One Lake and Two Seas" of the Inner Mongolia Autonomous Region, the monitoring of water quality in Lake Daihai has attracted increasing attention, and the concentration of chlorophyll-a directly affects the water quality, making the monitoring of chlorophyll-a concentration in Lake Daihai particularly crucial. Traditional methods of monitoring chlorophyll-a concentration are not only inefficient but also require significant human and material resources. Remote sensing technology has the advantages of wide coverage and short update cycles. For lakes such as Daihai with a high salinity content, salinity is considered a key factor when inverting the concentration of chlorophyll-a. In this study, machine learning models, including model stacking from ensemble learning, a ridge regression model, and a random forest model, were constructed. After comparing the training accuracy of the three models on Zhuhai-1 satellite data, the random forest model, which had the highest accuracy, was selected as the final training model. By comparing the accuracy changes before and after adding salinity factors to the random forest model, a high-precision model for inverting chlorophyll-a concentration in hypersaline lakes was obtained. The research results show that, without considering the salinity factor, the root mean square error (RMSE) of the model was 0.056, and the coefficient of determination (R2) was 0.64, indicating moderate model performance. After adding the salinity factor, the model accuracy significantly improved: the RMSE decreased to 0.047, and the R2 increased to 0.92. This study provides a solid basis for the application of remote sensing technology in hypersaline aquatic environments, confirming the importance of considering salinity when estimating chlorophyll-a concentration in hypersaline waters. This research helps us gain a deeper understanding of the water quality and ecosystem evolution in Daihai Lake.

A Clustering Approach for Atmospheric Phase Error Correction in Ground-Based SAR Using Spatial Autocorrelation.

When using ground-based synthetic aperture radar (GB-SAR) for monitoring open-pit mines, dynamic atmospheric conditions can interfere with the propagation speed of electromagnetic waves, resulting in atmospheric phase errors. These errors are particularly complex in rapidly changing weather conditions or steep terrain, significantly impacting monitoring accuracy. In such scenarios, traditional regression model-based atmospheric phase correction (APC) methods often become unsuitable. To address this issue, this paper proposes a clustering method based on the spatial autocorrelation function. First, the interferogram is uniformly divided into multiple blocks, and the phase consistency of each block is evaluated using the spatial autocorrelation function. Then, a region growing algorithm is employed to classify each block according to its phase pattern, followed by merging adjacent blocks based on statistical data. To verify the feasibility of the proposed method, both the traditional regression model-based method and the proposed method were applied to deformation monitoring of an open-pit mine in Northwest China. The experimental results show that for complex atmospheric phase scenarios, the proposed method significantly outperformed traditional methods, demonstrating its superiority.

Phase Noise Compensation Algorithm for Space-Borne Azimuth Multi-Channel SAR.

Azimuth multi-channel synthetic aperture radar (SAR) has always been an important technical means to achieve high-resolution wide-swath (HRWS) SAR imaging. However, in the space-borne azimuth multi-channel SAR system, random phase noise will be produced during the operation of each channel receiver. The phase noise of each channel is superimposed on the SAR echo signal of the corresponding channel, which will cause the phase imbalance between the channels and lead to the generation of false targets. In view of the above problems, this paper proposes a random phase noise compensation method for space-borne azimuth multi-channel SAR. This method performs feature decomposition by calculating the covariance matrix of the echo signal and converts the random phase noise estimation into the optimal solution of the cost function. Considering that the phase noise in the receiver has frequency-dependent and time-varying characteristics, this method calculates the phase noise estimation value corresponding to each range-frequency point in the range direction and obtains the phase noise estimation value by expectation in the azimuth direction. The proposed random phase noise compensation method can suppress false targets well and make the radar present a well-focused SAR image. Finally, the usefulness of the suggested method is verified by simulation experiments.

An Airborne Arc Array Synthetic Aperture Radar Vibration Error Compensation Method.

Compared to conventional radars, arc array synthetic aperture radar (SAR) enables wide-area observation under ideal conditions. However, helicopters carrying arc array SAR platforms are generally smaller in size and more sensitive to vibration, which has a greater impact on the imaging quality. In this paper, the vibration error of the arc array SAR platform is investigated, and a vibration error model of the arc array SAR platform is established. Based on the study of the vibration error model, a vibration phase estimation and compensation algorithm based on the delayed conjugate multiplication method is proposed. In the first step, distance pulse pressure processing is performed on the echo signal. In the second step, the pulse pressure signals and their delays in the same distance unit are subjected to conjugate multiplication, and the phase of the signal after conjugate multiplication is extracted. The extracted phase is then amplitude- and phase-compensated to estimate the vibration phase. In the third step, the vibration phase is compensated in the azimuthal direction of the distance pulse pressure signal, and the pairwise echo is eliminated, which completes the compensation of the airborne arc array SAR vibration platform.

Remote Sensing Monitoring of Grassland Locust Density Based on Machine Learning.

The main aim of this study was to utilize remote sensing data to establish regression models through machine learning to predict locust density in the upcoming year. First, a dataset for monitoring grassland locust density was constructed based on meteorological data and multi-source remote sensing data in the study area. Subsequently, an SVR (support vector regression) model, BP neural network regression model, random forest regression model, BP neural network regression model with the PCA (principal component analysis), and deep belief network regression model were built on the dataset. The experimental results show that the random forest regression model had the best prediction performance among the five models. Specifically, the model achieved a coefficient of determination (R2) of 0.9685 and a root mean square error (RMSE) of 1.0144 on the test set, which were the optimal values achieved among all the models tested. Finally, the locust density in the study area for 2023 was predicted and, by comparing the predicted results with actual measured data, it was found that the prediction accuracy was high. This is of great significance for local grassland ecological management, disaster warning, scientific decision-making support, scientific research progress, and sustainable agricultural development.

A New Permanent Scatterer Selection Method Based on Gaussian Mixture Model for Micro-Deformation Monitoring Radar Images.

The micro-deformation monitoring radar is usually based on Permanent Scatterer (PS) technology to realize deformation inversion. When the region is continuously monitored for a long time, the radar image amplitude and pixel variance will change significantly with time. Therefore, it is difficult to select phase-stable scatterers by conventional amplitude deviation methods, as they can seriously affect the accuracy of deformation inversion. For different regions studied within the same scenario, using a PS selection method based on the same threshold often increases the size of the deformation error. Therefore, this paper proposes a new PS selection method based on the Gaussian Mixture Model (GMM). Firstly, PS candidates (PSCs) are selected based on the pixels' amplitude information. Then, the amplitude deviation index of each PSC is calculated, and each pixel's probability values in different Gaussian distributions are acquired through iterations. Subsequently, the cluster types of pixels with larger probability values are designated as low-amplitude deviation pixels. Finally, the coherence coefficient and phase stability of low-amplitude deviation pixels are calculated. By comparing the probability values of each of the pixels in different Gaussian distributions, the cluster type with the larger probability, such as high-coherence pixels and high-phase stability pixels, is selected and designated as the final PS. Our analysis of the measured data revealed that the proposed method not only increased the number of PSs in the group, but also improved the stability of the number of PSs between groups.

Analysis and Prediction of Urban Surface Transformation Based on Small Baseline Subset Interferometric Synthetic Aperture Radar and Sparrow Search Algorithm-Convolutional Neural Network-Long Short-Term Memory Model.

With the acceleration of urbanisation, urban areas are subject to the combined effects of the accumulation of various natural factors, such as changes in temperature leading to the thermal expansion or contraction of surface materials (rock, soil, etc.) and changes in precipitation and humidity leading to an increase in the self-weight of soil due to the infiltration of water along the cracks or pores in the ground. Therefore, the subsidence of urban areas has now become a serious geological disaster phenomenon. However, the use of traditional neural network prediction models has limitations when examining the causal relationships between time series surface deformation data and multiple influencing factors and when applying multiple influencing factors for predictive analyses. To this end, Sentinel-1A data from March 2017 to February 2023 were used as the data source in this paper, based on time series deformation data acquired using the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique. A sparrow search algorithm-convolutional neural network-long short-term memory (SSA-CNN-LSTM) neural network prediction model was built. The six factors of temperature, humidity, precipitation, and ground temperature at three different depths below the surface (5 cm, 10 cm, and 15 cm) were taken as the input of the model, and the surface deformation data were taken as the output of the neural network model. The correlation between the spatial and temporal evolution characteristics of the ground subsidence in urban areas and various influencing factors was analysed using grey correlation analysis, which proved that these six factors contribute to some extent to the deformation of the urban surface. The main urban area of Hohhot City, Inner Mongolia Autonomous Region, was used as the study area. In order to verify the efficacy of this neural network prediction model, the prediction effects of the multilayer perceptron (MLP), backpropagation (BP), and SSA-CNN-LSTM models were compared and analysed, with the values of the correlation coefficients of the feature points of A1, B1, and C1 being in the range of 0.92, 0.83, and 0.93, respectively. The results show that compared with the traditional MLP and BP neural network models, the SSA-CNN-LSTM model achieves a higher performance in predicting time series surface deformation data in urban areas, which provides new ideas and methods for this area of research.

Research on Time Series Monitoring of Surface Deformation in Tongliao Urban Area Based on SBAS-PS-DS-InSAR.

As urban economies flourish and populations become increasingly concentrated, urban surface deformation has emerged as a critical factor in city planning that cannot be overlooked. Surface deformation in urban areas can lead to deformations in structural supports of infrastructure such as road bases and bridges, thereby posing a serious threat to public safety and creating significant safety hazards. Consequently, research focusing on the monitoring of urban surface deformation holds paramount importance. Interferometric synthetic aperture radar (InSAR), as an important means of earth observation, has all-day, wide-range, high-precision, etc., characteristics and is widely used in the field of surface deformation monitoring. However, traditional solitary InSAR techniques are limited in their application scenarios and computational characteristics. Additionally, the manual selection of ground control points (GCPs) is fraught with errors and uncertainties. Permanent scatterers (PS) can maintain high interferometric coherence in man-made building areas, and distributed scatterers (DS) usually show moderate coherence in areas with short vegetation; the combination of DS and PS solves the problem of manually selecting GCPs during track re-flattening and regrading, which affects the monitoring results. In this paper, 45 Sentinel-1B data from 16 February 2019 to 14 December 2021 are used as the data source in the urban area of Horqin District, Tongliao City, Inner Mongolia Autonomous Region, for example. A four-threshold (coherence coefficient threshold, FaSHPS adaptive threshold, amplitude divergence index threshold, and deformation velocity interval) GCPs point screening method for PS-DS, as well as a Small Baseline Subset-Permanent Scatterers-Distributed Scatterers-Interferometric Synthetic Aperture Radar (SBAS-PS-DS-InSAR) method for selecting PS and DS points as ground control points for orbit refinement and re-flattening, are proposed. The surface deformation results obtained using the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) and the SBAS-PS-DS-InSAR proposed in this paper were comparatively analysed and verified. The maximum cumulative line-of-sight settlements were -90.78 mm and -83.68 mm, and the maximum cumulative uplifts are 74.94 mm and 97.56 mm, respectively; the maximum annual average line-of-sight settlements are -35.38 mm/y and -30.38 mm/y, and the maximum annual average uplifts are 25.27 mm/y and 27.92 mm/y. The results were evaluated and analysed in terms of correlation, mean absolute error (MAE), and root mean square error (RMSE). The deformation results of the two InSAR methods were evaluated and analysed in terms of correlation, MAE, and RMSE. The errors show that the Pearson correlation coefficients between the vertical settlement results obtained using the SBAS-PS-DS-InSAR method and the GPS monitoring results were closer to 1. The maximum MAE and RMSE were 13.7625 mm and 14.8004 mm, respectively, which are within the acceptable range; this confirms that the monitoring results of the SBAS-PS-DS-InSAR method were better than those of the original SBAS-InSAR method. SBAS-InSAR method, which is valid and reliable. The results show that the surface deformation results obtained using the SBAS-InSAR, SBAS-PS-DS-InSAR, and GPS methods have basically the same settlement locations, extents, distributions, and temporal and spatial settlement patterns. The deformation results obtained using these two InSAR methods correlate well with the GPS monitoring results, and the MAE and RMSE are within acceptable limits. By comparing the deformation information obtained using multiple methods, the surface deformation in urban areas can be better monitored and analysed, and it can also provide scientific references for urban municipal planning and disaster warning.

Research on the Application of Dynamic Process Correlation Based on Radar Data in Mine Slope Sliding Early Warning.

With the gradual expansion of mining scale in open-pit coal mines, slope safety problems are increasingly diversified and complicated. In order to reduce the potential loss caused by slope sliding and reduce the major threat to the safety of life and property of residents in the mining area, this study selected two mining areas in Xinjiang as cases and focused on the relationship between phase noise and deformation. The study predicts the specific time point of slope sliding by analyzing the dynamic history correlation tangent angle between the two. Firstly, the time series data of the micro-variation monitoring radar are used to obtain the small deformation of the study area by differential InSAR (D-InSAR), and the phase noise is extracted from the radar echo in the sequence data. Then, the volume of the deformation body is calculated by analyzing the small deformation at each time point, and the standard deviation of the phase noise is calculated accordingly. Finally, the sliding time of the deformation body is predicted by combining the tangent angle of the ratio of the volume of the deformation body to the standard deviation of the phase noise. The results show that the maximum deformation rates of the deformation bodies in the studied mining areas reach 10.1 mm/h and 6.65 mm/h, respectively, and the maximum deformation volumes are 2,619,521.74 mm3 and 2,503,794.206 mm3, respectively. The predicted landslide time is earlier than the actual landslide time, which verifies the effectiveness of the proposed method. This prediction method can effectively identify the upcoming sliding events and the characteristics of the slope, provide more accurate and reliable prediction results for the slope monitoring staff, and significantly improve the efficiency of slope monitoring and early warning.

[Retracted] MicroRNA­671­5p inhibits cell proliferation, migration and invasion in non­small cell lung cancer by targeting MFAP3L.

Following the publication of this paper, it was drawn to the Editors' attention by a concerned reader that the western blotting data shown in Fig. 4B and the Transwell cell invasion data shown in Figs. 2D and 4E were strikingly similar to data appearing in different form in other articles written by different authors at different research institutes that had already been published elsewhere prior to the submission of this paper to Molecular Medicine Reports (one of which has been retracted). Moreover, there appeared to be inappropriately edited western blot bands featured in Figs. 4 and 5. In view of the fact that certain of the abovementioned data had already apparently been published previously, the Editor of Molecular Medicine Reports has decided that this paper should be retracted from the Journal. After having been in contact with the authors, they agreed with the decision to retract the paper. The Editor apologizes to the readership for any inconvenience caused. [Molecular Medicine Reports 25: 30, 2022; DOI: 10.3892/mmr.2021.12546].

Resveratrol Ameliorates Retinal Ischemia-Reperfusion Injury by Modulating the NLRP3 Inflammasome and Keap1/Nrf2/HO-1 Signaling Pathway.

Glaucoma, as an ischemia-reperfusion (I/R) injury disease, leading irreversible blindness through the loss of retinal ganglion cells (RGCs), mediated by various pathways. Resveratrol (Res) is a polyphenolic compound that exerts protective effects against I/R injury in many tissues. This article aimed to expound the underlying mechanisms through which Res protects RGCs and reduces visual dysfunction in vivo. An experimental glaucoma model was created using 6-8-week wild-type male C57BL/6J mice. Res was injected intraperitoneally for 5 days. The mice were then grouped according to the number of days after surgery and whether Res treatment was administered. We applied the Brn3a-labeled immunofluorescence staining and flash electroretinography (ERG) to assess the survival of RGCs and visual function. The expression of components of the NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3) inflammasome, the interleukin-1-beta (IL-1ß), and vital indicators of kelch-like ECH-associated protein 1 (Keap1)/nuclear factor erythroid 2-related factor 2 (Nrf2)/heme-oxygenase 1 (HO-1) pathway at the protein and RNA levels were detected respectively. The survival of RGCs was reduced after surgery compared to controls, whereas Res application rescued RGCs and improved visual dysfunction. In conclusion, our results discovered that Res administration showed neuroprotective effects through inhibition of the NLRP3 inflammasome pathway and activation of Keap1/Nrf2/HO-1 pathway. Thus, we further elucidated the potential of Res in glaucoma therapy.

Acupoint transplantation versus non-acupoint transplantation using autologous peripheral blood mononuclear cells in treating peripheral arterial disease.

Numerous studies have discussed the therapeutic outcomes of using cell therapy or acupuncture to treat peripheral artery disease (PAD). However, there are no long-term studies on the safety and efficacy of transplanting peripheral blood mononuclear cells (PBMNCs) via acupoints to treat PAD. We first reviewed the short-term and long-term clinical results of PAD patients treated with PBMNCs through intramuscular non-acupoint transplantation (control group; n = 45) or intramuscular acupoint transplantation (acupoint group; n = 45) at a single university hospital general medical center between December 2002 and September 2022. Pain intensity (assessed with the verbal rating scale [VRS] score) in the acupoint group was considerably lower than that in the control group at month 1 (mean ± standard deviation [SD]: 1.29 ± 0.96 vs 1.76 ± 0.82; P = 0.016) and month 3 (mean ± SD: 1.27 ± 0.90 vs 1.61 ± 0.86; P = 0.042). We observed significant improvement of VRS score (P < .001 for all) and ankle-brachial index (ABI; P < .001 for all) from baseline in both groups at months 1, 3, 6, 12, 36, and 60. The 10-year cumulative rate of major amputation-free survival (MAFS) was higher in the acupoint group as compared to the control group (81.9%, 95% confidence interval [CI]: 71.3%-94.1% vs 78.5%, 95% CI: 66.7%-92.3%; P = 0.768). Compared with the routine injection method, intramuscular transplantation of PBMNCs via selected acupoints could significantly decrease the short-term pain intensity in patients with PAD, which remains an option for consideration.

Preparation and Performance Evaluation of a Zinc Oxide-Graphene Oxideloaded Chitosan-Based Thermosensitive Gel.

This study aimed to develop and assess a chitosan biomedical antibacterial gel ZincOxide-GrapheneOxide/Chitosan/ß-Glycerophosphate (ZnO-GO/CS/ß-GP) loaded with nano-zinc oxide (ZnO) and graphene oxide (GO), known for its potent antibacterial properties, biocompatibility, and sustained drug release. ZnO nanoparticles (ZnO-NPs) were modified and integrated with GO sheets to create 1% and 3% ZnO-GO/CS/ß-GP thermo-sensitive hydrogels based on ZnO-GO to Chitosan (CS) mass ratio. Gelation time, pH, structural changes, and microscopic morphology were evaluated. The hydrogel's antibacterial efficacy against Porphyromonas gingivalis, biofilm biomass, and metabolic activity was examined alongside its impact (MC3T3-e1). The findings of this study revealed that both hydrogel formulations exhibited temperature sensitivity, maintaining a neutral pH. The ZnO-GO/CS/ß-GP formulation effectively inhibited P. gingivalis bacterial activity and biofilm formation, with a 3% ZnO-GO/CS/ß-GP antibacterial rate approaching 100%. MC3T3-e1 cells displayed good biocompatibility when cultured in the hydrogel extract.The ZnO-GO/CS/ß-GP thermo-sensitive hydrogel demonstrates favorable physical and chemical properties, effectively preventing P. gingivalis biofilm formation. It exhibits promising biocompatibility, suggesting its potential as an adjuvant therapy for managing and preventing peri-implantitis, subject to further clinical investigations.

Down-regulation of miR-21-5p by pirfenidone to inhibit fibroblast proliferation in the treatment of acquired tracheal stenosis.

OBJECTIVE: Treatment options for acquired tracheal stenosis (ATS) are limited due to a series of pathophysiological changes including inflammation and cell proliferation. Micro ribonucleic acid-21-5p (miR-21-5p) may promote the excessive proliferation of fibroblasts. However, various types of fibrosis can be prevented with pirfenidone (PFD). Currently, the effect of PFD on miR-21-5p and its biological function has not been clarified. In this study, PFD was evaluated as a potential treatment for ATS by inducing fibroblast proliferation in lipopolysaccharide (LPS)-induced fibroblasts by targeting miR-21-5p. METHODS: For 48 h, 1 g/ml LPS was used to generate fibroblasts in vitro, followed by the separation of cells into four groups: control, PFD, mimic, and mimic + PFD. The Cell Counting Kit-8 (CCK-8) technique was adopted to measure the proliferation of fibroblasts. Real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot (WB) were used to measure the relative expressions of tumor necrosis factor-α (TNF-α), transforming growth factor-ß1 (TGF-ß1), drosophila mothers against decapentaplegic 7 (Smad7) and collagen type I alpha 1(COL1A1) messenger RNA (mRNA) and proteins, respectively. RESULTS: (1) At 0, 24, 48, and 72 h, fibroblast growth was assessed using the CCK-8 method. Compared with the control group, the mimic group showed the highest fibroblast viability, and the PFD group showed the lowest fibroblast viability. However, fibroblast viability increased in the mimic + PFD group but decreased in the mimic one. (2) RT-qPCR and WB showed that the mimic group exhibited a significant up-regulation in the relative expressions of TNF-α, TGF-ß1, and COL1A1 mRNA and proteins but a down-regulation in the relative expression of Smad7 mRNA and protein compared with the control one. In the PFD group, the results were the opposite. Nevertheless, the relative expressions of TNF-α, TGF-ß1, and COL1A1 mRNA and proteins were increased, whereas that of Smad7 mRNA was decreased in the mimic + PFD group. The change was less in the mimic group. CONCLUSION: PFD may have a preventive and curative effect on ATS by inhibiting fibroblast proliferation and the fibrotic process and possibly through down-regulating miR-21-5p and up-regulating Smad7 and its mediated fibrotic and inflammatory responses.

Genome-wide association analysis reveals genes controlling an antagonistic effect of biotic and osmotic stress on Arabidopsis thaliana growth.

While the response of Arabidopsis thaliana to drought, herbivory or fungal infection has been well-examined, the consequences of exposure to a series of such (a)biotic stresses are not well studied. This work reports on the genetic mechanisms underlying the Arabidopsis response to single osmotic stress, and to combinatorial stress, either fungal infection using Botrytis cinerea or herbivory using Pieris rapae caterpillars followed by an osmotic stress treatment. Several small-effect genetic loci associated with rosette dry weight (DW), rosette water content (WC), and the projected rosette leaf area in response to combinatorial stress were mapped using univariate and multi-environment genome-wide association approaches. A single-nucleotide polymorphism (SNP) associated with DROUGHT-INDUCED 19 (DI19) was identified by both approaches, supporting its potential involvement in the response to combinatorial stress. Several SNPs were found to be in linkage disequilibrium with known stress-responsive genes such as PEROXIDASE 34 (PRX34), BASIC LEUCINE ZIPPER 25 (bZIP25), RESISTANCE METHYLATED GENE 1 (RMG1) and WHITE RUST RESISTANCE 4 (WRR4). An antagonistic effect between biotic and osmotic stress was found for prx34 and arf4 mutants, which suggests PRX34 and ARF4 play an important role in the response to the combinatorial stress.

Differential expression of miRNAs revealed by small RNA sequencing in traumatic tracheal stenosis.

Introduction: Traumatic tracheal stenosis (TTS) is a major cause of complex difficult airways, without clinically definitive efficacious drugs available. The aim of this study was to provide a general view of interactions between micro and messenger ribonucleic acids (miRNAs and mRNAs) and many potential mechanisms in TTS via small RNA sequencing. Methods: In this study, the identification of miRNAs was completed using small RNA sequencing and samples from four TTS patients and four normal control cases. By using bioinformatics tools, such as miRanda and RNAhybrid, for identifying the candidate target genes of miRNAs with differential expression in each sample, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were employed for enriching the predicted target genes of miRNAs with differential expression based on the correspondence between miRNAs and their target genes. We detected the expression of the candidate miRNAs using quantitative real-time polymerase chain reaction (qRT-PCR). Results: Twenty-four miRNAs with significant differential expression were identified, including 13 upregulated and 11 downregulated ones. Bioinformation technology was adopted to predict 2,496 target genes. These miRNA-target genes were shown to be primarily enriched in cells and organelles with catalytic activity and binding function, such as binding proteins, small molecules, and nucleotides. Finally, they were observed to process into TTS through the intercellular and signal regulation of related inflammatory signaling and fibrosis signaling pathways. QRT-PCR confirmed the upregulation of miR21-5p and miR214-3p and the downregulation of miR141-3p and miR29b-3p, which was expected to become a high-specific miRNA for TTS. Conclusion: Among all the miRNAs detected, 24 miRNAs demonstrated differential expression between the TTS and normal control groups. A total of 2,496 target genes were predicted by bioinformation technology and enriched in inflammatory and fibrotic signaling pathways. These results provide new ideas for further studies and the selection of targets for TTS in the future.