Development and validation of a new diagnostic prediction model of ENHO and NOX4 for early diagnosis of systemic sclerosis.

Objective: Systemic sclerosis (SSc) is a chronic autoimmune disease characterized by fibrosis. The challenge of early diagnosis, along with the lack of effective treatments for fibrosis, contribute to poor therapeutic outcomes and high mortality of SSc. Therefore, there is an urgent need to identify suitable biomarkers for early diagnosis of SSc. Methods: Three skin gene expression datasets of SSc patients and healthy controls were downloaded from Gene Expression Omnibus (GEO) database (GSE130955, GSE58095, and GSE181549). GSE130955 (48 early diffuse cutaneous SSc and 33 controls) were utilized to screen differentially expressed genes (DEGs) between SSc and normal skin samples. Least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE) were performed to identify diagnostic genes and construct a diagnostic prediction model. The results were further validated in GSE58095 (61 SSc and 36 controls) and GSE181549 (113 SSc and 44 controls) datasets. Receiver operating characteristic (ROC) curves were applied for assessing the level of diagnostic ability. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to verify the diagnostic genes in skin tissues of out cohort (10 SSc and 5 controls). Immune infiltration analysis were performed using CIBERSORT algorithm. Results: A total of 200 DEGs were identified between SSc and normal skin samples. Functional enrichment analysis revealed that these DEGs may be involved in the pathogenesis of SSc, such as extracellular matrix remodeling, cell-cell interactions, and metabolism. Subsequently, two critical genes (ENHO and NOX4) were identified by LASSO and SVM-RFE. ENHO was found down-regulated while NOX4 was up-regulated in skin of SSc patients and their expression levels were validated by above three datasets and our cohort. Notably, these differential expressions were more pronounced in patients with diffuse cutaneous SSc than in those with limited cutaneous SSc. Next, we developed a novel diagnostic model for SSc using ENHO and NOX4, which demonstrated strong predictive power in above three cohorts and in our own cohort. Furthermore, immune infiltration analysis revealed dysregulated levels of various immune cell subtypes within early SSc skin specimens, and a negative correlation was observed between the levels of ENHO and Macrophages M1 and M2, while a positive correlation was observed between the levels of NOX4 and Macrophages M1 and M2. Conclusion: This study identified ENHO and NOX4 as novel biomarkers that can be serve as a diagnostic prediction model for early detection of SSc and play a potential role in the pathogenesis of the disease.

Tree shrews as a new animal model for systemic sclerosis research.

Objective: Systemic sclerosis (SSc) is a chronic systemic disease characterized by immune dysregulation and fibrosis for which there is no effective treatment. Animal models are crucial for advancing SSc research. Tree shrews are genetically, anatomically, and immunologically closer to humans than rodents. Thus, the tree shrew model provides a unique opportunity for translational research in SSc. Methods: In this study, a SSc tree shrew model was constructed by subcutaneous injection of different doses of bleomycin (BLM) for 21 days. We assessed the degree of inflammation and fibrosis in the skin and internal organs, and antibodies in serum. Furthermore, RNA sequencing and a series of bioinformatics analyses were performed to analyze the transcriptome changes, hub genes and immune infiltration in the skin tissues of BLM induced SSc tree shrew models. Multiple sequence alignment was utilized to analyze the conservation of selected target genes across multiple species. Results: Subcutaneous injection of BLM successfully induced a SSc model in tree shrew. This model exhibited inflammation and fibrosis in skin and lung, and some developed esophageal fibrosis and secrum autoantibodies including antinuclear antibodies and anti-scleroderma-70 antibody. Using RNA sequencing, we compiled skin transcriptome profiles in SSc tree shrew models. 90 differentially expressed genes (DEGs) were identified, which were mainly enriched in the PPAR signaling pathway, tyrosine metabolic pathway, p53 signaling pathway, ECM receptor interaction and glutathione metabolism, all of which are closely associated with SSc. Immune infiltration analysis identified 20 different types of immune cells infiltrating the skin of the BLM-induced SSc tree shrew models and correlations between those immune cells. By constructing a protein-protein interaction (PPI) network, we identified 10 hub genes that were significantly highly expressed in the skin of the SSc models compared to controls. Furthermore, these genes were confirmed to be highly conserved in tree shrews, humans and mice. Conclusion: This study for the first time comfirmed that tree shrew model of SSc can be used as a novel and promising experimental animal model to study the pathogenesis and translational research in SSc.

MICA+ Tumor Cell Upregulated Macrophage-Secreted MMP9 via PROS1-AXL Axis to Induce Tumor Immune Escape in Advanced Hepatocellular Carcinoma (HCC).

BACKGROUND: tumor-associated macrophages (TAMs) constitute a significant proportion of non-cancerous cells within the intricate tumor microenvironment (TME) of hepatocellular carcinoma (HCC). Understanding the communication between macrophages and tumor cells, as well as investigating potential signaling pathways, holds promise for enhancing therapeutic responses in HCC. METHODS: single-cell RNA-sequencing data and bulk RNA-sequencing data were derived from open source databases Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Through this analysis, we elucidated the interactions between MICA+ tumor cells and MMP9+ macrophages, primarily mediated via the PROS1-AXL axis in advanced HCC. Subsequently, we employed a range of experimental techniques including lentivirus infection, recombinant protein stimulation, and AXL inhibition experiments to validate these interactions and unravel the underlying mechanisms. RESULTS: we presented a single-cell atlas of advanced HCC, highlighting the expression patterns of MICA and MMP9 in tumor cells and macrophages, respectively. Activation of the interferon gamma (IFN-γ) signaling pathway was observed in MICA+ tumor cells and MMP9+ macrophages. We identified the existence of an interaction between MICA+ tumor cells and MMP9+ macrophages mediated via the PROS1-AXL axis. Additionally, we found MMP9+ macrophages had a positive correlation with M2-like macrophages. Subsequently, experiments validated that DNA damage not only induced MICA expression in tumor cells via IRF1, but also upregulated PROS1 levels in HCC cells, stimulating macrophages to secrete MMP9. Consequently, MMP9 led to the proteolysis of MICA. CONCLUSION: MICA+ HCC cells secreted PROS1, which upregulated MMP9 expression in macrophages through AXL receptors. The increased MMP9 activity resulted in the proteolytic shedding of MICA, leading to the release of soluble MICA (sMICA) and the subsequent facilitation of tumor immune escape.

Macrophage metabolism, phenotype, function, and therapy in hepatocellular carcinoma (HCC).

The pivotal role of the tumor microenvironment (TME) in the initiation and advancement of hepatocellular carcinoma (HCC) is widely acknowledged, as it fosters the proliferation and metastasis of HCC cells. Within the intricate TME of HCC, tumor-associated macrophages (TAMs) represent a significant constituent of non-malignant cells. TAMs engage in direct communication with cancer cells in HCC, while also exerting influence on other immune cells to adopt a tumor-supportive phenotype that facilitates tumor progression. Among the multifaceted mechanisms at play, the metabolic reprogramming of both tumor cells and macrophages leads to phenotypic alterations and functional modifications in macrophages. This comprehensive review elucidates the intricate interplay between cellular metabolism and macrophage phenotype/polarization, while also providing an overview of the associated signaling molecules and potential therapeutic strategies for HCC.

Comigration and interactions between two species of rice planthopper (Laodelphax striatellus and Sogatella furcifera) and natural enemies in eastern Asia.

BACKGROUND: Natural enemies are important in pest control. However, control by natural enemies is hindered by the migration of rice planthoppers. Therefore, comigration and interactions between Laodelphax striatellus (Fallén) and Sogatella furcifera (Horváth) and five predator species, Chrysoperla sinica Tjeder, Harmonia axyridis (Pallas), Episyrphus balteatus, Syrphus corollae (Fab.) and Chrysopa pallens (Rambur) in eastern Asia were investigated. RESULTS: From 2012 to 2021, the migration patterns of two rice planthoppers and five natural enemy species were monitored by suction trapping on Beihuang Island, Shandong Province, China. Both planthoppers and the five natural enemies regularly comigrated from late April to late October each year. There were significant interannual and seasonal differences in the numbers of two rice planthoppers migrating across this island. Simulated seasonal migration trajectories indicated different source areas for the two rice planthoppers, which mainly originated in northeast, north and east China. The biomass of planthoppers was significantly positively correlated with that of the ladybug H. axyridis in all migration periods, and significant differences in the ratio of rice planthoppers to natural enemies among months. A time-lag effect between seasons was obtained when natural enemies and pests comigrated. CONCLUSION: Migration was coordinated between rice planthoppers and natural enemies in East Asia. When natural enemies and rice planthoppers comigrated, time lags between seasons were observed. The unique insights into the migration patterns will help to increase understanding of the occurrence of rice planthoppers in eastern Asia and provide an important theoretical basis for regional monitoring and management of rice planthoppers. © 2023 Society of Chemical Industry.

Inhibition of Checkpoint Kinase 1 (CHK1) Upregulates Interferon Regulatory Factor 1 (IRF1) to Promote Apoptosis and Activate Anti-Tumor Immunity via MICA in Hepatocellular Carcinoma (HCC).

BACKGROUND: CHK1 is considered a key cell cycle checkpoint kinase in DNA damage response (DDR) pathway to communicate with several signaling pathways involved in the tumor microenvironment (TME) in numerous cancers. However, the mechanism of CHK1 signaling regulating TME in hepatocellular carcinoma (HCC) remains unclear. METHODS: CHK1 expression in HCC tissue was determined by IHC staining assay. DNA damage and apoptosis in HCC cells induced by cisplatin or CHK1 inhibition were detected by WB and flow cytometry. The interaction of CHK1 and IRF1 was analyzed by single-cell RNA-sequence, WB, and immunoprecipitation assay. The mechanism of IRF1 regulating MICA was investigated by ChIP-qPCR. RESULTS: CHK1 expression is upregulated in human HCC tumors compared to the background liver. High CHK1 mRNA level predicts advanced tumor stage and worse prognosis. Cisplatin and CHK1 inhibition augment cellular DNA damage and apoptosis. Overexpressed CHK1 suppresses IRF1 expression through proteolysis. Furthermore, single-cell RNA-sequence analyses confirmed that MICA expression positively correlated with IRF1 in HCC cells. Immunoprecipitation assay showed the binding between CHK1 and IRF1. Cisplatin and CHK1 inhibition upregulate MICA expression through IRF1-mediated transcriptional effects. A novel specific cis-acting IRF response element was identified at -1756 bp in the MICA promoter region that bound IRF1 to induce MICA gene transcription. MICA may increase NK cell and CD8+T cell infiltration in HCC. CONCLUSIONS: DNA damage regulates the interaction of CHK1 and IRF1 to activate anti-tumor immunity via the IRF1-MICA pathway in HCC.

Seasonal migratory activity of SPODOPTERA FRUGIPERDA (J.E. Smith) (Lepidoptera: Noctuidae) across China and Myanmar.

BACKGROUND: The fall armyworm (FAW) Spodoptera frugiperda Smith (Lepidoptera: Noctuidae) invaded Myanmar and China in 2018 and greatly impacted agricultural production and ecosystem balance in these areas. FAW is a migratory insect, but its seasonal migration pattern between the two countries has been largely unknown. From 2019 to 2021, we monitored the seasonal migration of FAW in the China-Myanmar border area using a searchlight trap, assessed the reproductive development status of female migrants and traced the migratory routes by trajectory simulation. RESULTS: FAW moths were trapped by the searchlight trap in Lancang County (Yunnan, China) all year, with obvious seasonal differences in the number caught. There were small-scale persistent trapping peaks in spring and summer, and obvious peaks in autumn; only a small number of moths were trapped in winter. Examination of the ovaries of female moths collected in different seasons showed that most females had matured, indicating that the moths were migrating and did not take off from the local area. In the migration trajectory simulation, FAW mainly migrated from Myanmar to Southwest China in spring and summer and back to Myanmar in autumn. CONCLUSION: Our findings indicate that FAW migrates between China and Myanmar according to the monsoon circulation, which will help guide cross-border regional monitoring and management strategies against this pest. © 2022 Society of Chemical Industry.

Cuprotosis-Related Genes: Predicting Prognosis and Immunotherapy Sensitivity in Pancreatic Cancer Patients.

Based on TCGA, GTEx, and TIMER databases and various bioinformatics analysis methods, the potential biological roles of cuprotosis-related genes in pancreatic cancer were deeply explored, and a predictive model for pancreatic cancer patients was constructed. We downloaded the RNA-Seq data and clinicopathological and predictive data of 179 pancreatic cancer tissues and 332 adjacent normal tissues from TCGA and GTEx databases. The differential expression of cuprotosis-related genes in pancreatic cancer tissue and adjacent normal tissue was analyzed, and the LASSO regression algorithm was used to construct a prediction model and verify the validity of the model prediction. Based on the LASSO regression algorithm, a predictive model composed of three genes LIPT1, LIAS, and DLAT was screened. The corresponding survival curves showed that the constructed prediction model could significantly distinguish the prognosis of pancreatic cancer patients, and the prognosis of patients in the high-risk group was worse (P = 0.00557). The ROC curve showed that the area under the curve of the predictive model for predicting the 4-, 5-, and 6-year survival rates in pancreatic cancer was 0.816, 0.836, and 0.956, respectively. The AUC value of this risk model was significantly higher than 0.7, which could more accurately predict the prognosis of pancreatic cancer patients. This study determined a risk-scoring model of cuprotosis-related genes, which can provide an essential basis for judging the prognosis of pancreatic cancer patients.

Artificial Intelligence Algorithm in Classification and Recognition of Primary Hepatic Carcinoma Images under Magnetic Resonance Imaging.

This study aimed to discuss the application value of the bias field correction algorithm in magnetic resonance imaging (MRI) images of patients with primary hepatic carcinoma (PHC). In total, 52 patients with PHC were selected as the experimental group and divided into three subgroups: mild (15 cases), moderate (19 cases), and severe (18 cases) according to pathological grading. Another 52 patients with hepatic nodules in the same period were included in the control group. All the patients underwent dynamic contrast-enhanced (DCE) MRI examination, and the image qualities of MRI before and after bias field correction were compared. The DCE-MRI perfusion parameters were measured, including the transport constant Ktrans, reverse rate constant Kep, extravascular extracellular volume fraction (Ve), plasma volume (Vp), microvascular density (MVD), hepatic artery perfusion index (HPI), mean transit time of contrast agent (MTT), time to peak (TTP), blood volume (BV), hepatic arterial perfusion (HAP), full perfusion (FP), and portal venous perfusion (PVP). It was found that the sensitivity (93.63%), specificity (71.62%), positive predictive value (95.63%), negative predictive value (71.62%), and accuracy (90.01%) of MRI examination processed by the bias field correction algorithm were all significantly greater than those before processing (P < 0.05). The Ktrans, Kep, Ve, Vp, and MVD of patients in the experimental group were significantly larger than those of the control group, and severe group> moderate group> mild group (P < 0.05). HPI, MTT, TTP, BV, and HAP of patients in the experimental group were also significantly greater than those of the control group, which was shown as severe group > moderate group > mild group (P < 0.05). FP and PVP of the experimental group were significantly lower than those of the control group, and severe group < moderate group < mild group (P < 0.05). It was suggested that in MRI images of patients with PHC, the bias field correction algorithm could significantly improve the diagnosis rate. Each perfusion parameter was related to the pathological grading, which could be used to evaluate the prognosis of patients.

Development and Validation of a Novel PPAR Signaling Pathway-Related Predictive Model to Predict Prognosis in Breast Cancer.

This study is aimed at exploring the potential mechanism of the PPAR signaling pathway in breast cancer (BRCA) and constructing a novel prognostic-related risk model. We used various bioinformatics methods and databases to complete our exploration in this research. Based on TCGA database, we use multiple extension packages based on the R language for data conversion, processing, and statistics. We use LASSO regression analysis to establish a prognostic-related risk model in BRCA. And we combined the data of multiple online websites, including GEPIA, ImmuCellAI, TIMER, GDSC, and the Human Protein Atlas database to conduct a more in-depth exploration of the risk model. Based on the mRNA data in TCGA database, we conducted a preliminary screening of genes related to the PPAR signaling pathway through univariate Cox analysis, then used LASSO regression analysis to conduct a second screening, and successfully established a risk model consisting of ten genes in BRCA. The results of ROC curve analysis show that the risk model has good prediction accuracy. We can successfully divide breast cancer patients into high- and low-risk groups with significant prognostic differences (P = 1.92e - 05) based on this risk model. Combined with the clinical data in TCGA database, there is a correlation between the risk model and the patient's N, T, gender, and fustat. The results of multivariate Cox regression show that the risk score of this risk model can be used as an independent risk factor for BRCA patients. In particular, we draw a nomogram that can predict the 5-, 7-, and 10-year survival rates of BRCA patients. Subsequently, we conducted a series of pancancer analyses of CNV, SNV, OS, methylation, and immune infiltration for this risk model gene and used GDSC data to investigate drug sensitivity. Finally, to gain insight into the predictive value and protein expression of these risk model genes in breast cancer, we used GEO and HPA databases for validation. This study provides valuable clues for future research on the PPAR signaling pathway in BRCA.

Comprehensive Analysis of Necroptosis-Related Genes as Prognostic Factors and Immunological Biomarkers in Breast Cancer.

Breast cancer (BC) is a lethal malignancy with a poor prognosis. Necroptosis is critical in the progression of cancer. However, the expression of genes involved in necroptosis in BC and their association with prognosis remain unclear. We investigated the predictive potential of necroptosis-related genes in BC samples from the TCGA dataset. We used LASSO regression to build a risk model consisting of twelve necroptosis-related genes in BC. Using the necroptosis-related risk model, we were able to successfully classify BC patients into high- and low-risk groups with significant prognostic differences (p = 4.872 × 10 -7). Additionally, we developed a matched nomogram predicting 5, 7, and 10-year overall survival in BC patients based on this necroptosis-related risk model. Our next step was to perform multiple GSEA analyses to explore the biological pathways through which these necroptosis-related risk genes influence cancer progression. For these twelve risk model genes, we analyzed CNV, SNV, OS, methylation, immune cell infiltration, and drug sensitivity in pan-cancer. In addition, immunohistochemical data from the THPA database were used to validate the protein expression of these risk model genes in BC. Taken together, we believe that necroptosis-related genes are considered potential therapeutic targets in BC and should be further investigated.

Comprehensive Analysis of the Expression and Prognostic Value of SPINT1/2 in Breast Carcinoma.

Background: Hepatocyte growth factor (HGF) signaling plays a plethora of roles in tumorigenesis and progression in many cancer types. As HGF activator inhibitors, serine protease inhibitor, Kunitz types 1 and 2 (SPINT1 and SPINT2) have been reported to be differentially expressed in breast cancer, but their prognostic significance and functioning mechanism remain unclear. Methods: In our study, multiple databases and bioinformatics tools were used to investigate SPINT1/2 expression profiles, prognostic significance, genetic alteration, methylation, and regulatory network in breast carcinoma. Results: SPINT1/2 expression was upregulated in breast cancer, and was relatively higher in human epidermal growth factor receptor 2 (HER2) and node positive patients. Elevated SPINT1/2 expression was significantly correlated with a poorer prognosis. Genetic alterations and SPINT1/2 hypomethylation were observed. In breast carcinoma, SPINT1/2 were reciprocally correlated and shared common co-expressed genes. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that their common co-expressed genes were primarily involved in regulating cell attachment and migration. Conclusions: Our study identified the expression profiles, prognostic significance and potential roles of SPINT1/2 in breast carcinoma. These study results showed that the SPINT1/2 were potential prognostic biomarker for patients with breast cancer.

Trajectory modeling revealed a southwest-northeast migration corridor for fall armyworm Spodoptera frugiperda (Lepidoptera: Noctuidae) emerging from the North China Plain.

The fall armyworm Spodoptera frugiperda, an invasive insect pest native to the Americas, has established populations throughout eastern China. The North China Plain-a key corn-producing area in East China with a unique topography-was invaded by fall armyworm in 2019 and is seriously threatened by this migratory pest. However, the spatiotemporal extent of the migratory movements of fall armyworm from the North China Plain remains poorly understood. Using an air transport-based trajectory modeling approach that incorporates flight behavior, we simulated the potential nocturnal migration trajectories of fall armyworm from the North China Plain based on historical meteorological data from June to October of 2015-2019, and examined the night-time atmospheric conditions associated with their possible flights. The emigration patterns showed monthly variation in the main landing area and common migration direction. The displacement of newly emerged moths from the North China Plain was concentrated in the Northeast China Plain (including Liaoning, Jilin and Heilongjiang provinces) before late summer, after which they were most likely to undertake return flights to the south (especially into Hubei, Anhui and Hunan provinces). This southwest-northeast aerial migration corridor follows the topography of East China and is affected by the East Asian monsoon. These topographic-atmospheric conditions have resulted in the North China Plain becoming a key stopover for fall armyworm populations engaging in multigenerational long-distance migration across East China. These findings contribute to our knowledge of fall armyworm migration and will aid in the implementation of management and control strategies against this highly migratory agricultural pest.

KLHL5 Is a Prognostic-Related Biomarker and Correlated With Immune Infiltrates in Gastric Cancer.

Background: KLHL5 (Kelch Like Family Member 5) is differentially expressed in gastric cancer, but its correlation with prognosis and functioning mechanism in gastric cancer remain unclear. Methods: The Oncomine database and TIMER were employed to appraise the KLHL5 expression in a variety of cancers. The correlation between KLHL5 expression and patient prognosis was extracted from the Kaplan-Meier plotter, GEPIA, and PrognoScan database. Then the relationship between KLHL5 expression and inflammatory infiltrate profiles was inquired by TIMER. Finally, GEPIA and TIMER were explored for the correlative significance between KLHL5 expression and immune cell-related marker sets. Results: KLHL5 was found to be differentially expressed and correlated with clinical outcomes in several types of cancers in the TCGA database. Especially, KLHL5 mRNA expression was upregulated and correlated with poorer overall survival and progression-free survival in gastric cancer. Moreover, elevated KLHL5 expression was significantly related with patient node stage, infiltration level, and expression of multiple immune marker sets. Conclusions: These results implicate that KLHL5 expression is closely linked with patient clinical outcomes and the microenvironmental infiltration level in different neoplasms. This indicates that KLHL5 is a modulator in infiltrate recruitment, shaping the landscape of immune cell infiltration. Thus, it represents an eligible prognostic predictor for gastric malignancy.

The hypoglycemic and renal protective effects of Grifola frondosa polysaccharides in early diabetic nephropathy.

Grifola frondosa is a basidiomycete polypore fungus. Polysaccharides from G. frondosa (PGF) has recently attracted attention for its various physiological activities including antioxidant, antitumor, and anti-fatigue effects. In this study, hypoglycemic activity of PGF and its preventive effect against the progression of kidney fibrosis in Diabetic nephropathy (DN) rats were investigated. The results showed that PGF led to a significant decrease in fasting blood glucose levels and an increase in body weight in the treatment group compared with those of model group. Serum biochemical indexes including N-acetyl-ß-D-glucosaminidase (NAG), blood urea nitrogen (BUN), serum creatinine (SCr), and urine microalbumin (u-mAlb) levels of PGF-treated group were significantly lower than those of model group. Inflammatory cytokines and renal fibrosis indexes of PGF group were also decreased compared to the model group. The whole results demonstrated the renal-protective effects of PGF via reducing the inflammatory factor content and preventing renal fibrosis. PRACTICAL APPLICATIONS: G. frondosa constitutes a rich source of polysaccharides, steroid, and phenolic compounds. The results obtained revealed that the purified PGF have the effect of reducing inflammation cytokines and renal fibrosis indexes. These two factors are associated with the development and progression of diabetic nephropathy. Therefore, PGF may produce both hypoglycemic and renal-protective effects, and potentially be of use as a functional food for the treatment or prevention of diabetic nephropathy.

Compound Dan Zhi tablet attenuates experimental ischemic stroke via inhibiting platelet activation and thrombus formation.

BACKGROUND: Compound Dan Zhi tablet (DZT) is a commonly used traditional Chinese medicine formula. It has been used for the treatment of ischemic stroke for many years in clinical. However, its pharmacological mechanism is unclear. PURPOSE: The aim of the current study was to understand the protective effects and underlying mechanisms of DZT on ischemic stroke. METHODS: Fifteen representative chemical markers in DZT were determined by ultra-performance liquid chromatography coupled with tandem quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS). The protective effect of DZT against ischemic stroke was studied in a rat model of middle cerebral artery occlusion (MCAO), and the mechanism was further explored through a combination of network pharmacology and experimental verification. RESULTS: Quantitative analysis showed that the contents of phenolic acids, furan sulfonic acids, tanshinones, flavonoids, saponins and phthalides in DZT were calculated as 7.47, 0.788, 0.627, 0.531 and 0.256 mg/g, respectively. Phenolic acids were the most abundant constituents. Orally administered DZT (1.701 g kg-1) significantly alleviated the infarct size and neurological scores in MCAO rats. The network analysis predicted that 53 absorbed active compounds in DZT-treated plasma targeted 189 proteins and 47 pathways. Ten pathways were associated with anti-platelet activity. In further experiments, DZT (0.4 and 0.8 mg mL-1) markedly inhibited in vitro prostaglandin G/H synthase 1 (PTGS1) activity. DZT (0.4 and 0.8 mg mL-1) significantly inhibited in vitro platelet aggregation in response to ADP or AA. DZT (113 and 226 mg kg-1, p.o.) also produced a marked inhibition of ADP- or AA-induced ex vivo platelet aggregation with a short duration of action. DZT decreased the level of thromboxane A2 (TXA2) in MCAO rats. In the carrageenan-induced tail thrombosis model and ADP-induced acute pulmonary thromboembolism mice model, DZT (113 and 226 mg kg-1, p.o.) prevented thrombus formation. Importantly, DZT (113 and 226 mg kg-1, p.o.) exhibited a low bleeding liability. CONCLUSION: DZT protected against cerebral ischemic injury. The inhibition of TXA2 level, platelet aggregation and thrombosis formation might involve in the protective mechanism.

Correction: Wu, Q.-L.; et al. Estimation of the Potential Infestation Area of Newly-Invaded Fall Armyworm Spodoptera Frugiperda in the Yangtze River Valley of China. Insects 2019, 10, 298.

The authors wish to make the following correction to this paper [...].

Prediction of migratory routes of the invasive fall armyworm in eastern China using a trajectory analytical approach.

BACKGROUND: The fall armyworm (FAW), an invasive pest from the Americas, is rapidly spreading through the Old World, and has recently invaded the Indochinese Peninsula and southern China. In the Americas, FAW migrates from winter-breeding areas in the south into summer-breeding areas throughout North America where it is a major pest of corn. Asian populations are also likely to evolve migrations into the corn-producing regions of eastern China, where they will pose a serious threat to food security. RESULTS: To evaluate the invasion risk in eastern China, the rate of expansion and future migratory range was modelled by a trajectory simulation approach, combined with flight behavior and meteorological data. Our results predict that FAW will migrate from its new year-round breeding regions into the two main corn-producing regions of eastern China (Huang-Huai-Hai Summer Corn and Northeast Spring Corn Regions), via two pathways. The western pathway originates in Myanmar and Yunnan, and FAW will take four migration steps (i.e. four generations) to reach the Huang-Huai-Hai Region by July. Migration along the eastern pathway from Indochina and southern China progresses faster, with FAW reaching the Huang-Huai-Hai Region in three steps by June and reaching the Northeast Spring Region in July. CONCLUSION: Our results indicate that there is a high risk that FAW will invade the major corn-producing areas of eastern China via two migration pathways, and cause significant impacts to agricultural productivity. Information on migration pathways and timings can be used to inform integrated pest management strategies for this emerging pest. © 2019 Society of Chemical Industry.

Seasonal Migration Patterns of Ostrinia furnacalis (Lepidoptera: Crambidae) Across the Bohai Strait in Northern China.

The Asian corn borer (ACB), Ostrinia furnacalis (Guenée), is a notorious polyphagous insect pest in China and other regions of East Asia. The long-distance flight behavior of the ACB moths, however, is not well understood, especially in the field conditions. In this study, nightly monitoring data for multiple years (2003-2017) on the long-distance flight of adults crossing the Bohai Strait in northern China, showed that a large number of the adults frequently flew across the Bohai Strait from May to September with the peak migrations usually occurred, followed in order by September, June, July, and May, and the number of southward migrants was larger than that of northward migrants. From May to September in 2010, 2011, and 2017, a subsample of trapped ACB females was dissected (879 individuals in 2010, 197 individuals in 2011, and 247 individuals in 2017), and the results showed that the sex ratio of the trapped ACB moths was unbiased each month from May to September. While the proportion of mated females in northward populations (May to July = 92.85 ± 4.86%) was significantly higher than that in southward population (August and September = 74.53 ± 8.55%) . The seasonal pattern in the proportion of sexually mature females was similar to the above proportion of mated females. We conclude that the ACBs have a strong propensity and ability for long-distance migration, although local dispersal is generally considered to be the primary movement of the ACB. These findings may be helpful to improve the forecasting systems and the pest management schemes for the ACBs.

Female bias in an immigratory population of Cnaphalocrocis medinalis moths based on field surveys and laboratory tests.

Sex ratio bias is common in migratory animals and can affect population structure and reproductive strategies, thereby altering population development. However, little is known about the underlying mechanisms that lead to sex ratio bias in migratory insect populations. In this study, we used Cnaphalocrocis medinalis, a typical migratory pest of rice, to explore this phenomenon. A total of 1,170 moths were collected from searchlight traps during immigration periods in 2015-2018. Females were much more abundant than males each year (total females: total males = 722:448). Sex-based differences in emergence time, take-off behaviour, flight capability and energy reserves were evaluated in a laboratory population. Females emerged 0.78 days earlier than males. In addition, the emigratory propensity and flight capability of female moths were greater than those of male moths, and female moths had more energy reserves than did male moths. These results indicate that female moths migrate earlier and can fly farther than male moths, resulting more female moths in the studied immigratory population.