Exploring the stability of the gender gap in faculty perceptions of gender climate at a rural regional university.

Increasing awareness of gender barriers and biases in academic institutions is an essential component of institutional change strategies to promote equity and inclusion. There is an established perception gap in recognizing gender inequities in the workplace, whereby men faculty under acknowledge the stressors, barriers, and biases faced by their women faculty colleagues. This study explored the gender gap in faculty perceptions of institutional diversity climate at a rural comprehensive regional university in the United States. In addition to gender, differences across academic discipline and time were explored using 2 (men and women) x 2 (STEM and other) x 2 (2017 and 2022) between-groups ANOVAs. Results revealed a gender gap that persisted across time and perceptions of stressors, diversity climate, student behavior, leadership, and fairness in promotion/tenure procedures, with marginalized (women) faculty consistently reporting greater barriers/concern for women faculty relative to the perceptions of their men faculty colleagues. These findings are largely consistent with the extant literature and are discussed both with regard to future research directions and recommendations for reducing the perception gap and addressing institutional barriers to gender equity.

Children with severe neurological symptoms associated with SARS-CoV-2 infection during Omicron pandemic in China.

BACKGROUND: To analyze the clinical characteristics and outcomes of children with severe neurological symptoms associated with the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection during the Omicron pandemic in China. METHODS: This study used a questionnaire to obtain data from pediatric intensive care unit (PICU) centers in seven tertiary hospitals in Northeast China from December 1, 2022, to January 31, 2023. RESULTS: A total of 255 patients were confirmed to have SARS-CoV-2 infection, and 45 patients (17.65 %) were included in this study. Of these, seven (15.6%) patients died, and the median time from admission to death was 35 h (IQR, 14-120 h). Twenty (52.6%) survivors experienced neurological sequelae. Patients with platelet counts lower than 100 × 109/L had a higher incidence of complications such as multiple organ dysfunction, mechanical ventilation rate, and mortality. Cranial magnetic resonance imaging (MRI) always reveals cerebral tissue edema, with some severe lesions forming a softening site. CONCLUSION: Children infected with SARS-CoV-2 often exhibit severe neurological symptoms, and in some cases, they may rapidly develop malignant cerebral edema or herniation, leading to a fatal outcome. An early decrease in platelet count may associated with an unfavorable prognosis. IMPACT: Since early December 2022, China has gradually adjusted its prevention and control policy of SARS-CoV-2; Omicron outbreaks have occurred in some areas for a relatively short period. Due to the differences in ethnicity, endemic strains and vaccination status, there was a little difference from what has been reported about children with SARS-CoV-2 infection with severe neurological symptoms in abroad. This is the first multicenter clinical study in children with nervous system involvement after acute SARS-CoV-2 infection in China, and helpful for pediatricians to have a more comprehensive understanding of the clinical symptoms and prognosis of such disease.

Self-Reported Neurological Symptoms Two Years After Hospital Discharge Among COVID-19 Survivors.

Background: The acute stage of COVID-19 often presents with neurological manifestations. Objective: This study aims to investigate the long-term neurological effects on survivors. Methods: This study recruited 1,546 COVID-19 survivors from Wuhan, including 1,119 nonsevere cases and 427 severe survivors. Participants were interviewed two years after discharge to report their neurological symptoms. The neurological symptoms of COVID-19 were compared between survivors of severe and nonsevere COVID-19. Results: Among the 1,546 COVID-19 survivors, 44.24% discovered at least one neurological symptom. The most prevalent self-reported symptom was fatigue (28.33%), memory deficit (13.26%), attention deficit (9.96%), myalgia (8.34%), dizziness (3.82%), and headache (2.52%). Severe cases had higher incidences of fatigue, myalgia, memory deficit, attention deficit than nonsevere cases. Older age, severe COVID-19, and comorbidity burden were associated with long-term neurological symptoms. Conclusion: Neurological symptoms are common among COVID-19 survivors, especially in severe cases.

Tubular cell transcriptional intermediary factor 1γ deficiency exacerbates kidney injury-induced tubular cell polyploidy and fibrosis.

Tubulointerstitial fibrosis is considered the final convergent pathway of progressive chronic kidney diseases (CKD) regardless of etiology. However, mechanisms underlying kidney injury-induced fibrosis largely remain unknown. Recent studies have indicated that transcriptional intermediary factor 1γ (TIF1γ) inhibits the progression of fibrosis in other organs. Here, we found that TIF1γ was highly expressed in the cytoplasm and nucleus of the kidney proximal tubule. Interestingly, we found tubular TIF1γ expression was decreased in patients with CKD, including those with diabetes, hypertension, and IgA nephropathy, and in mouse models with experimental kidney fibrosis (unilateral ureteral obstruction [UUO], folic acid nephropathy [FAN], and aristolochic acid-induced nephrotoxicity). Tubule-specific knock out of TIF1γ in mice exacerbated UUO- and FAN-induced tubular cell polyploidy and subsequent fibrosis, whereas overexpression of kidney TIF1γ protected mice against kidney fibrosis. Mechanistically, in tubular epithelial cells, TIF1γ exerted an antifibrotic role via transforming growth factor-ß (TGF-ß)-dependent and -independent signaling. TIF1γ hindered TGF-ß signaling directly by inhibiting the formation and activity of the transcription factor Smad complex in tubular cells, and we discovered that TIF1γ suppressed epidermal growth factor receptor (EGFR) signaling upstream of TGF-ß signaling in tubular cells by ubiquitylating EGFR at its lysine 851/905 sites thereby promoting EGFR internalization and lysosomal degradation. Pharmacological inhibition of EGFR signaling attenuated exacerbated polyploidization and the fibrotic phenotype in mice with tubule deletion of TIF1γ. Thus, tubular TIF1γ plays an important role in kidney fibrosis by suppressing profibrotic EGFR and TGF-ß signaling. Hence, our findings suggest that maintaining homeostasis of tubular TIF1γ may be a new therapeutic option for treating tubulointerstitial fibrosis and subsequent CKD.

Prediction of road dust concentration in open-pit coal mines based on multivariate mixed model.

The problem of dust pollution in the open-pit coal mine significantly impacts the health of staff, the regular operation of mining work, and the surrounding environment. At the same time, the open-pit road is the largest dust source. Therefore, it analyzes the influencing factors of road dust concentration in the open-pit coal mine. It is of practical significance to establish a prediction model for scientific and effective prediction of road dust concentration in the open pit coal mine. The prediction model helps reduce dust hazards. This paper uses the hourly air quality and meteorological data of an open-pit coal mine in Tongliao City, Inner Mongolia Autonomous Region, from January 1, 2020, to December 31, 2021. Create a CNN-BiLSTM-Attention multivariate hybrid model consisting of a Convolutional Neural Network (CNN), a bidirectional long short-term memory neural network (BiLSTM), and an attention mechanism, Prediction of PM2.5 concentration in the next 24h. Establish prediction models of parallel and serial structures, and carry out many experiments according to the change period of the data to determine the optimal configuration and the input and output size. Then, a comparison of the proposed model and Lasso regression, SVR, XGBoost, LSTM, BiLSTM, CNN-LSTM, and CNN-BiLSTM models for short-term prediction (24h) and long-term prediction (48h, 72h, 96h, and 120h). The results show that the CNN-BiLSTM-Attention multivariate mixed model proposed in this paper has the best prediction performance. The mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) of the short-term forecast (24h) are 6.957, 8.985, and 0.914, respectively. Evaluation indicators of long-term forecasts (48h, 72h, 96h, and 120h) are also superior to contrast models. Finally, we used field-measured data to verify, and the obtained evaluation indexes MAE, RMSE, and R2 are 3.127, 3.989, and 0.951, respectively. The model-fitting effect was good.

Research on fault diagnosis system for belt conveyor based on internet of things and the LightGBM model.

As an equipment failure that often occurs in coal production and transportation, belt conveyor failure usually requires many human and material resources to be identified and diagnosed. Therefore, it is urgent to improve the efficiency of fault identification, and this paper combines the internet of things (IoT) platform and the Light Gradient Boosting Machine (LGBM) model to establish a fault diagnosis system for the belt conveyor. Firstly, selecting and installing sensors for the belt conveyor to collect the running data. Secondly, connecting the sensor and the Aprus adapter and configuring the script language on the client side of the IoT platform. This step enables the collected data to be uploaded to the client side of the IoT platform, where the data can be counted and visualized. Finally, the LGBM model is built to diagnose the conveyor faults, and the evaluation index and K-fold cross-validation prove the model's effectiveness. In addition, after the system was established and debugged, it was applied in practical mine engineering for three months. The field test results show: (1) The client of the IoT can well receive the data uploaded by the sensor and present the data in the form of a graph. (2) The LGBM model has a high accuracy. In the test, the model accurately detected faults, including belt deviation, belt slipping, and belt tearing, which happened twice, two times, one time and one time, respectively, as well as timely gaving warnings to the client and effectively avoiding subsequent accidents. This application shows that the fault diagnosis system of belt conveyors can accurately diagnose and identify belt conveyor failure in the coal production process and improve the intelligent management of coal mines.

Targeting VPS72 inhibits ACTL6A/MYC axis activity in HCC progression.

BACKGROUND AND AIMS: HCC is a highly heterogeneous disease that is caused largely by genomic copy number variations. Herein, the mechanistic and therapeutically targeted role of vacuolar protein sorting 72 homologue (VPS72), a novel copy number variation cis-driven gained gene identified by genome-wide copy number variation and transcriptome analyses in HCC, is not well understood. APPROACH AND RESULTS: First, overexpression of VPS72 enhanced the initiation and progression of HCC in vitro and in vivo . Mechanistically, VPS72 interacted with the oncoproteins MYC and actin-like 6A (ACTL6A) and promoted the formation of the ACTL6A/MYC complex. Furthermore, ACTL6A regulated VPS72 protein stability by weakening the interaction between tripartite motif containing 21 (TRIM21) and VPS72. Thus, the interaction between VPS72 and ACTL6A enhanced the affinity of MYC for its target gene promoters and promoted their transcription, thereby contributing to HCC progression, which was inhibited by adeno-associated virus serotype 8 (AAV8)-mediated short hairpin RNA (shRNA) against VPS72. CONCLUSIONS: This study reveals the molecular mechanism of ACTL6A/VPS72/MYC in HCC, providing a theoretical basis and therapeutic target for this malignancy.

The role of YAP1 in liver cancer stem cells: proven and potential mechanisms.

YAP1 (Yes-associated protein 1) is one of the principal factors that mediates oncogenesis by acting as a driver of gene expression. It has been confirmed to play an important role in organ volume control, stem cell function, tissue regeneration, tumorigenesis and tumor metastasis. Recent research findings show that YAP1 is correlated with the stemness of liver cancer stem cells, and liver cancer stem cells are closely associated with YAP1-induced tumor initiation and progression. This article reviews the advancements made in research on the mechanisms by which YAP1 promotes liver cancer stem cells and discusses some potential mechanisms that require further study.

Design of PM2.5 monitoring and forecasting system for opencast coal mine road based on internet of things and ARIMA Mode.

The dust produced by transportation roads is the primary source of PM2.5 pollution in opencast coal mines. However, China's opencast coal mines lack an efficient and straightforward construction scheme of monitoring and management systems and a short-term prediction model to support dust control. In this study, by establishing a PM2.5 and other real-time environmental information to monitor, manage, visualize and predict the Internet of things monitoring and prediction system to solve these problems. This study solves these problems by establishing an Internet of things monitoring and prediction system, which can monitor PM2.5 and other real-time environmental information for monitoring, management, visualization, and prediction. We use Lua language to write interface protocol code in the APRUS adapter, which can simplify the construction of environmental monitoring system. The Internet of things platform has a custom visualization scheme, which is convenient for managers without programming experience to manage sensors and real-time data. We analyze real-time data using a time series model in Python, and RMSE and MAPE evaluate cross-validation results. The evaluation results show that the average RMSE of the ARIMA (4,1,0) and Double Exponential Smoothing models are 12.68 and 8.34, respectively. Both models have good generalization ability. The average MAPE of the fitting results are 10.5% and 1.7%, respectively, and the relative error is small. Because the ARIMA model has a more flexible prediction range and strong expansibility, and ARIMA model shows good adaptability in cross-validation, the ARIMA model is more suitable as the short-term prediction model of the prediction system. The prediction system can continuously predict PM2.5 dust through the ARIMA model. The monitoring and prediction system is very suitable for managers of opencast coal mines to prevent and control road dust.

Application of improved and optimized fuzzy neural network in classification evaluation of top coal cavability.

Longwall top coal caving technology is one of the main methods of thick coal seam mining in China, and the classification evaluation of top coal cavability in longwall top coal caving working face is of great significance for improving coal recovery. However, the empirical or numerical simulation method currently used to evaluate the top coal cavability has high cost and low-efficiency problems. Therefore, in order to improve the evaluation efficiency and reduce evaluation the cost of top coal cavability, according to the characteristics of classification evaluation of top coal cavability, this paper improved and optimized the fuzzy neural network developed by Nauck and Kruse and establishes the fuzzy neural network prediction model for classification evaluation of top coal cavability. At the same time, in order to ensure that the optimized and improved fuzzy neural network has the ability of global approximation that a neural network should have, its global approximation is verified. Then use the data in the database of published papers from CNKI as sample data to train, verify and test the established fuzzy neural network model. After that, the tested model is applied to the classification evaluation of the top coal cavability in 61,107 longwall top coal caving working face in Liuwan Coal Mine. The final evaluation result is that the top coal cavability grade of the 61,107 longwall top coal caving working face in Liuwan Coal Mine is grade II, consistent with the engineering practice.

Construction of an evapotranspiration model and analysis of spatiotemporal variation in Xilin River Basin, China.

Surface evapotranspiration is a water exchange process between the atmosphere, biosphere, and hydrosphere. Accurate evapotranspiration estimations in arid and semi-arid regions are important for monitoring droughts and protecting the ecological environment. The main objective of this study is to build an evapotranspiration estimation model suitable for an effective scientific and objective evaluation of water consumption in the arid and semi-arid regions of the Xilin River Basin based on comprehensive parameters, including meteorological parameters, vegetation coverage, and soil water content. In this study, the community evapotranspiration model was initially constructed using field data, which was then expanded for applicability to the Xilin River Basin based on Geographic Information System technology and spatial heterogeneity characteristics of remote sensing data; both models were significant at the 0.05 level. The monthly evapotranspiration values in July during 2000-2017 and those from April to September (growing season) during the dry, normal, and wet years were calculated using the model at the basin scale. The evapotranspiration showed a generally increasing trend, which was consistent with the fluctuation trend in precipitation in July during 2000-2017. The trend curve for evapotranspiration was gentle during the growing season in dry years, but steep during wet years. The evapotranspiration was the lowest in April, with negligible spatial variations throughout the Xilin River Basin. During May-July, the evapotranspiration was higher than that in other months, in the following order: upper reaches > middle reaches > lower reaches; this was consistent with the vegetation coverage. The evapotranspiration declined and spatial variations were not evident during August-September. The results of this study provide a reference for evapotranspiration model construction and a scientific basis for evaluating regional water resources and protecting the ecological environment.

The role of RNA m5C modification in cancer metastasis.

Epigenetic modification plays a crucial regulatory role in the biological processes of eukaryotic cells. The recent characterization of DNA and RNA methylation is still ongoing. Tumor metastasis has long been an unconquerable feature in the fight against cancer. As an inevitable component of the epigenetic regulatory network, 5-methylcytosine is associated with multifarious cellular processes and systemic diseases, including cell migration and cancer metastasis. Recently, gratifying progress has been achieved in determining the molecular interactions between m5C writers (DNMTs and NSUNs), demethylases (TETs), readers (YTHDF2, ALYREF and YBX1) and RNAs. However, the underlying mechanism of RNA m5C methylation in cell mobility and metastasis remains unclear. The functions of m5C writers and readers are believed to regulate gene expression at the post-transcription level and are involved in cellular metabolism and movement. In this review, we emphatically summarize the recent updates on m5C components and related regulatory networks. The content will be focused on writers and readers of the RNA m5C modification and potential mechanisms in diseases. We will discuss relevant upstream and downstream interacting molecules and their associations with cell migration and metastasis.

Characterization of TGFß-associated molecular features and drug responses in gastrointestinal adenocarcinoma.

BACKGROUND: Gastrointestinal adenocarcinoma (GIAD) has caused a serious disease burden globally. Targeted therapy for the transforming growth factor beta (TGF-ß) signaling pathway is becoming a reality. However, the molecular characterization of TGF-ß associated signatures in GIAD requires further exploration. METHODS: Multi-omics data were collected from TCGA and GEO database. A pivotal unsupervised clustering for TGF-ß level was performed by distinguish status of TGF-ß associated genes. We analyzed differential mRNAs, miRNAs, proteins gene mutations and copy number variations in both clusters for comparison. Enrichment of pathways and gene sets were identified in each type of GIAD. Then we performed differential mRNA related drug response by collecting data from GDSC. At last, a summarized deep neural network for TGF-ß status and GIADs was constracted. RESULTS: The TGF-ßhigh group had a worse prognosis in overall GIAD patients, and had a worse prognosis trend in gastric cancer and colon cancer specifically. Signatures (including mRNA and proteins) of the TGF-ßhigh group is highly correlated with EMT. According to miRNA analysis, miR-215-3p, miR-378a-5p, and miR-194-3p may block the effect of TGF-ß. Further genomic analysis showed that TGF-ßlow group had more genomic changes in gastric cancer, such as TP53 mutation, EGFR amplification, and SMAD4 deletion. And drug response dataset revealed tumor-sensitive or tumor-resistant drugs corresponding to TGF-ß associated mRNAs. Finally, the DNN model showed an excellent predictive effect in predicting TGF-ß status in different GIAD datasets. CONCLUSIONS: We provide molecular signatures associated with different levels of TGF-ß to deepen the understanding of the role of TGF-ß in GIAD and provide potential drug possibilities for therapeutic targets in different levels of TGF-ß in GIAD.

A thorough screening based on QTLs controlling zinc and copper accumulation in the grain of different wheat genotypes.

Excess trace metals may cause damage to human health due to the consumption of food grain grown in contaminated soils. This study was designed to understand the genetic mechanisms of copper (Cu) and zinc (Zn) accumulation in wheat grain under stressed environments. The differences of Cu/Zn contents in the grain among 246 wheat varieties were analyzed, and the wheat varieties with low or high accumulation of Cu and Zn in the safe range were also screened out. The accumulation of Cu and Zn in grains of "Chushanbao" was lowest, which could be used as a novel germplasm for wheat breeding under heavy metal stress. We found that Cu contents of wheat grain were significantly and positively correlated with Zn. The quantitative trait loci (QTLs) for grain Cu content (GCuC) and grain Zn content (GZnC) were detected by genome-wide association study (GWAS). Twenty-three loci affecting GCuC were identified on chromosomes 1A, 1D, 2A, 2B, 2D, 3A, 3B, 3D, 4A, 4B 4D, 5A, 6D, 7A, and 7B, explaining 2.6-5.8% of the phenotypic variation. Sixteen loci associated with the GZnC on 11 different chromosomes 1B, 2B, 2D, 3A, 3D, 4A, 4B, 5A, 5D, 6B, and 7D were detected, which could explain 2.7~6.6% of phenotypic variance. We also determined five associated loci on chromosomes 2B, 2D, 3A, 4B, and 5A were in pleiotropic regions affecting both GCuC and GZnC. This study would help in better understanding the molecular basis of Cu/Zn accumulation in wheat grain, and the associated markers may be useful for marker-assisted selection (MAS) breeding program.

Genetic Dissection of Adult Plant Resistance to Sharp Eyespot Using an Updated Genetic Map of Niavt14 × Xuzhou25 Winter Wheat Recombinant Inbred Line Population.

Wheat sharp eyespot, a disease mainly caused by soilborne fungus Rhizoctonia cerealis, is a threat to world wheat production. Wheat's genetic resistance to sharp eyespot is a potential approach to reducing the application of fungicides and farming practice inputs. To identify the genetic basis of sharp eyespot resistance in Niavt14, a recombinant inbred line population comprising 215 F8 lines from Niavt14 × Xuzhou25, was developed. An earlier linkage map (148 simple sequence repeat markers) was updated with 5,792 polymorphic Affymetrix Axiom 55K single-nucleotide polymorphisms to a new map of 5,684.2 centimorgans with 1,406 nonredundant markers. The new linkage map covered all 21 chromosomes of common wheat and showed a good collinearity with the IWGSC RefSeq v1.0 genome. We conducted quantitative trait locus (QTL) mapping for sharp eyespot resistance using the adult plant response data from the field of five consecutive growing seasons and one greenhouse test. Two stable QTL on chromosomes 2B and 7D that were identified in the previous study were confirmed, and three novel, stable QTL, explaining 4.0 to 17.5% phenotypic variation, were mapped on 1D, 6D, and 7A, which were independent of QTL for phenology and plant height. The QTL on 1D, 2B, 6D, and 7A showed low frequencies in 384 landraces (0 to 10%) and 269 elite cultivars (5 to 23%) from the southern winter wheat region and the Yellow and Huai River Valley facultative wheat region in China, respectively. These identified QTL could be used in wheat breeding programs for improving sharp eyespot resistance through marker-assisted selection.

Microenvironment characterization and multi-omics signatures related to prognosis and immunotherapy response of hepatocellular carcinoma.

BACKGROUND: Immune cell infiltration in the tumor microenvironment (TME) affects tumor initiation, patients' prognosis and immunotherapy strategies. However, their roles and interactions with genomics and molecular processes in hepatocellular carcinoma (HCC) still have not been systematically evaluated. METHODS: We performed unsupervised clustering of total 1000 HCC samples including discovery and validation group from available public datasets. Immune heterogeneity of each subtype was explored by multi-dimension analysis. And a support vector machine (SVM) model based on multi-omics signatures was trained and tested. Finally, we performed immunohistochemistry to verify the immune role of signatures. RESULTS: We defined three immune subtypes in HCC, with diverse clinical, molecular, and genomic characteristics. Cluster1 had worse prognosis, better anti-tumor characteristics and highest immune scores, but also accompanied by immunosuppression and T cell dysfunction. Meanwhile, a better anti-PD1/CTLA4 immunotherapeutic response was predicted in cluster1. Cluster2 was enriched in TAM-M2 and stromal cells, indicating immunosuppression. Cluster3, with better prognosis, had lowest CD8 T cell but highest immune resting cells. Further, based on genomic signatures, we developed an SVM classifier to identify the patient's immunological status, which was divided into Type A and Type B, in which Type A had poorer prognosis, higher T cell dysfunction despite higher T cell infiltration, and had better immunotherapeutic response. At the same time, MMP9 may be a potential predictor of the immune characteristics and immunotherapeutic response in HCC. CONCLUSIONS: Our work demonstrated 3 immune clusters with different features. More importantly, multi-omics signatures, such as MMP9 was identified based on three clusters to help us recognize patients with different prognosis and responses to immunotherapy in HCC. This study could further reveal the immune status of HCC and provide potential predictors for immune checkpoint treatment response.

Quantitative Phosphoproteomic Analysis in Alpha-Synuclein Transgenic Mice Reveals the Involvement of Aberrant p25/Cdk5 Signaling in Early-stage Parkinson's Disease.

A30P and A53T mutations in the gene encoding alpha-synuclein-a presynaptic protein-are the most frequently identified genetic causes of Parkinson's disease (PD). Aberrant alpha-synuclein likely plays central roles in dopaminergic neuronal death and motor symptoms in PD. This study investigated the protein phosphorylation profile in early-stage PD through phosphoproteomic analyses of tissue samples from the substantia nigra pars compacta (SNpc) of 6-month-old alpha-synuclein transgenic mice (A30P/A53T double-mutant human alpha-synuclein; hm2α-SYN-39 strain). We identified 5351 phosphorylation sites in 2136 phosphoproteins. Of these, 357 upregulated sites in 245 proteins and 50 downregulated sites in 46 proteins were differentially phosphorylated between alpha-synuclein transgenic and wildtype mice. Bioinformatic analyses, including Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment, and motif analyses, were used to elucidate the molecular and cellular mechanisms underlying double-mutant human alpha-synuclein overexpression. Scansite-based computational analysis and prediction of differentially quantitated phosphoproteins identified the neuronal protein cyclin-dependent kinase 5 (Cdk5) as the most significantly enriched kinase. Biochemical experiments suggested that the p25/Cdk5 pathway was activated in an MPP+-induced cell culture model and MPTP-induced mouse model. Moreover, Cdk5 could directly phosphorylate the Ank2 protein at Ser1889 in vitro. Therefore, quantitative phosphoproteomic using an alpha-synuclein transgenic mouse model offers a powerful approach for elucidating the protein phosphorylation mechanism underlying SNpc dopaminergic neuronal death in an animal model of PD.

Estimation of Nitrogen Nutrition Status in Winter Wheat From Unmanned Aerial Vehicle Based Multi-Angular Multispectral Imagery.

Rapid, non-destructive and accurate detection of crop N status is beneficial for optimized fertilizer applications and grain quality prediction in the context of precision crop management. Previous research on the remote estimation of crop N nutrition status was mostly conducted with ground-based spectral data from nadir or oblique angles. Few studies investigated the performance of unmanned aerial vehicle (UAV) based multispectral imagery in regular nadir views for such a purpose, not to mention the feasibility of oblique or multi-angular images for improved estimation. This study employed a UAV-based five-band camera to acquire multispectral images at seven view zenith angles (VZAs) (0°, ± 20°, ± 40° and ±60°) for three critical growth stages of winter wheat. Four representative vegetation indices encompassing the Visible Atmospherically Resistant Index (VARI), Red edge Chlorophyll Index (CIred-edge), Green band Chlorophyll Index (CIgreen), Modified Normalized Difference Vegetation Index with a blue band (mNDblue) were derived from the multi-angular images. They were used to estimate the N nutrition status in leaf nitrogen concentration (LNC), plant nitrogen concentration (PNC), leaf nitrogen accumulation (LNA), and plant nitrogen accumulation (PNA) of wheat canopies for a combination of treatments in N rate, variety and planting density. The results demonstrated that the highest accuracy for single-angle images was obtained with CIgreen for LNC from a VZA of -60° (R2 = 0.71, RMSE = 0.34%) and PNC from a VZA of -40° (R2 = 0.36, RMSE = 0.29%). When combining an off-nadir image (-40°) and the 0° image, the accuracy of PNC estimation was substantially improved (CIred-edge: R2 = 0.52, RMSE = 0.28%). However, the use of dual-angle images did not significantly increase the estimation accuracy for LNA and PNA compared to the use of single-angle images. Our findings suggest that it is important and practical to use oblique images from a UAV-based multispectral camera for better estimation of nitrogen concentration in wheat leaves or plants. The oblique images acquired from additional flights could be used alone or combined with the nadir-view images for improved crop N status monitoring.

Laser-induced fluorescence diagnostic via pulsed lasers in an argon plasma.

Laser-induced fluorescence (LIF) using a pulsed laser is successfully applied in an argon plasma. The laser system consists of a pumping pulse laser fixed at 532 nm and a tunable dye laser. Using a homemade Fabry-Perot interferometer, the large linewidth of the original output is reduced by one order from 4 GHz to 340 MHz. The measured ion temperature is 0.15 eV with a velocity resolution about 200 m/s. It provides great possibility for the combination of LIF and planar LIF using the same pulsed laser system.

The wheat AGC kinase TaAGC1 is a positive contributor to host resistance to the necrotrophic pathogen Rhizoctonia cerealis.

Considerable progress has been made in understanding the roles of AGC kinases in mammalian systems. However, very little is known about the roles of AGC kinases in wheat (Triticum aestivum). The necrotrophic fungus Rhizoctonia cerealis is the major pathogen of the destructive disease sharp eyespot of wheat. In this study, the wheat AGC kinase gene TaAGC1, responding to R. cerealis infection, was isolated, and its properties and role in wheat defence were characterized. R. cerealis-resistant wheat lines expressed TaAGC1 at higher levels than susceptible wheat lines. Sequence and phylogenetic analyses showed that the TaAGC1 protein is a serine/threonine kinase belonging to the NDR (nuclear Dbf2-related) subgroup of AGC kinases. Kinase activity assays proved that TaAGC1 is a functional kinase and the Asp-239 residue located in the conserved serine/threonine kinase domain of TaAGC1 is required for the kinase activity. Subcellular localization assays indicated that TaAGC1 localized in the cytoplasm and nucleus. Virus-induced TaAGC1 silencing revealed that the down-regulation of TaAGC1 transcripts significantly impaired wheat resistance to R. cerealis. The molecular characterization and responses of TaAGC1 overexpressing transgenic wheat plants indicated that TaAGC1 overexpression significantly enhanced resistance to sharp eyespot and reduced the accumulation of reactive oxygen species (ROS) in wheat plants challenged with R. cerealis. Furthermore, ROS-scavenging and certain defence-associated genes were up-regulated in resistant plants overexpressing TaAGC1 but down-regulated in susceptible knock-down plants. These results suggested that the kinase TaAGC1 positively contributes to wheat immunity to R. cerealis through regulating expression of ROS-related and defence-associated genes.