Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer.

To provide a detailed analysis of the molecular components and underlying mechanisms associated with ovarian cancer, we performed a comprehensive mass-spectrometry-based proteomic characterization of 174 ovarian tumors previously analyzed by The Cancer Genome Atlas (TCGA), of which 169 were high-grade serous carcinomas (HGSCs). Integrating our proteomic measurements with the genomic data yielded a number of insights into disease, such as how different copy-number alternations influence the proteome, the proteins associated with chromosomal instability, the sets of signaling pathways that diverse genome rearrangements converge on, and the ones most associated with short overall survival. Specific protein acetylations associated with homologous recombination deficiency suggest a potential means for stratifying patients for therapy. In addition to providing a valuable resource, these findings provide a view of how the somatic genome drives the cancer proteome and associations between protein and post-translational modification levels and clinical outcomes in HGSC. VIDEO ABSTRACT.

Predicting potential microbe-disease associations based on multi-source features and deep learning.

Studies have confirmed that the occurrence of many complex diseases in the human body is closely related to the microbial community, and microbes can affect tumorigenesis and metastasis by regulating the tumor microenvironment. However, there are still large gaps in the clinical observation of the microbiota in disease. Although biological experiments are accurate in identifying disease-associated microbes, they are also time-consuming and expensive. The computational models for effective identification of diseases related microbes can shorten this process, and reduce capital and time costs. Based on this, in the paper, a model named DSAE_RF is presented to predict latent microbe-disease associations by combining multi-source features and deep learning. DSAE_RF calculates four similarities between microbes and diseases, which are then used as feature vectors for the disease-microbe pairs. Later, reliable negative samples are screened by k-means clustering, and a deep sparse autoencoder neural network is further used to extract effective features of the disease-microbe pairs. In this foundation, a random forest classifier is presented to predict the associations between microbes and diseases. To assess the performance of the model in this paper, 10-fold cross-validation is implemented on the same dataset. As a result, the AUC and AUPR of the model are 0.9448 and 0.9431, respectively. Furthermore, we also conduct a variety of experiments, including comparison of negative sample selection methods, comparison with different models and classifiers, Kolmogorov-Smirnov test and t-test, ablation experiments, robustness analysis, and case studies on Covid-19 and colorectal cancer. The results fully demonstrate the reliability and availability of our model.

P-CSN: single-cell RNA sequencing data analysis by partial cell-specific network.

Although many single-cell computational methods proposed use gene expression as input, recent studies show that replacing 'unstable' gene expression with 'stable' gene-gene associations can greatly improve the performance of downstream analysis. To obtain accurate gene-gene associations, conditional cell-specific network method (c-CSN) filters out the indirect associations of cell-specific network method (CSN) based on the conditional independence of statistics. However, when there are strong connections in networks, the c-CSN suffers from false negative problem in network construction. To overcome this problem, a new partial cell-specific network method (p-CSN) based on the partial independence of statistics is proposed in this paper, which eliminates the singularity of the c-CSN by implicitly including direct associations among estimated variables. Based on the p-CSN, single-cell network entropy (scNEntropy) is further proposed to quantify cell state. The superiorities of our method are verified on several datasets. (i) Compared with traditional gene regulatory network construction methods, the p-CSN constructs partial cell-specific networks, namely, one cell to one network. (ii) When there are strong connections in networks, the p-CSN reduces the false negative probability of the c-CSN. (iii) The input of more accurate gene-gene associations further optimizes the performance of downstream analyses. (iv) The scNEntropy effectively quantifies cell state and reconstructs cell pseudo-time.

DDN3.0: determining significant rewiring of biological network structure with differential dependency networks.

MOTIVATION: Complex diseases are often caused and characterized by misregulation of multiple biological pathways. Differential network analysis aims to detect significant rewiring of biological network structures under different conditions and has become an important tool for understanding the molecular etiology of disease progression and therapeutic response. With few exceptions, most existing differential network analysis tools perform differential tests on separately learned network structures that are computationally expensive and prone to collapse when grouped samples are limited or less consistent. RESULTS: We previously developed an accurate differential network analysis method-differential dependency networks (DDN), that enables joint learning of common and rewired network structures under different conditions. We now introduce the DDN3.0 tool that improves this framework with three new and highly efficient algorithms, namely, unbiased model estimation with a weighted error measure applicable to imbalance sample groups, multiple acceleration strategies to improve learning efficiency, and data-driven determination of proper hyperparameters. The comparative experimental results obtained from both realistic simulations and case studies show that DDN3.0 can help biologists more accurately identify, in a study-specific and often unknown conserved regulatory circuitry, a network of significantly rewired molecular players potentially responsible for phenotypic transitions. AVAILABILITY AND IMPLEMENTATION: The Python package of DDN3.0 is freely available at https://github.com/cbil-vt/DDN3. A user's guide and a vignette are provided at https://ddn-30.readthedocs.io/.

MS-PyCloud: A Cloud Computing-Based Pipeline for Proteomic and Glycoproteomic Data Analyses.

Rapid development and wide adoption of mass spectrometry-based glycoproteomic technologies have empowered scientists to study proteins and protein glycosylation in complex samples on a large scale. This progress has also created unprecedented challenges for individual laboratories to store, manage, and analyze proteomic and glycoproteomic data, both in the cost for proprietary software and high-performance computing and in the long processing time that discourages on-the-fly changes of data processing settings required in explorative and discovery analysis. We developed an open-source, cloud computing-based pipeline, MS-PyCloud, with graphical user interface (GUI), for proteomic and glycoproteomic data analysis. The major components of this pipeline include data file integrity validation, MS/MS database search for spectral assignments to peptide sequences, false discovery rate estimation, protein inference, quantitation of global protein levels, and specific glycan-modified glycopeptides as well as other modification-specific peptides such as phosphorylation, acetylation, and ubiquitination. To ensure the transparency and reproducibility of data analysis, MS-PyCloud includes open-source software tools with comprehensive testing and versioning for spectrum assignments. Leveraging public cloud computing infrastructure via Amazon Web Services (AWS), MS-PyCloud scales seamlessly based on analysis demand to achieve fast and efficient performance. Application of the pipeline to the analysis of large-scale LC-MS/MS data sets demonstrated the effectiveness and high performance of MS-PyCloud. The software can be downloaded at https://github.com/huizhanglab-jhu/ms-pycloud.

Comparison of IMD and ICG videoangiography in combined bypass surgery: a single-center study.

BACKGROUND: Superficial temporal artery-middle cerebral artery (STA-MCA) bypass combined with an encephaloduromyosynangiosis (EDMS) had gained significant role in treating chronic cerebral ischemia. Invasiveness and costs of intraoperative digital subtraction angiography (DSA) limited its application in operations. OBJECTIVE: To find the reliable parameters for determining bypass patency with intraoperative micro-Doppler (IMD) sonography and compare the diagnostic accuracy of indocyanine green (ICG) videoangiography with IMD in combined bypass. METHOD: One hundred fifty bypass procedures were included and divided into patent and non-patent groups according to postoperative computed tomography angiography (CTA) within 72 h. The surgical process was divided into four phases in the following order: preparation phase (phase 1), anastomosis phase (phase 2), the temporalis muscle closure phase (phase 3), and the bone flap closure phase (phase 4). The IMD parameters were compared between patent and non-patent groups, and then compared with the patency on CTA by statistical analyses. IMD with CTA, ICG videoangiography with CTA, IMD with ICG videoangiography were performed to assess bypass patency. The agreement between methods was evaluated using kappa statistics. RESULTS: No significant differences of baseline characteristics were found between patent and non-patent group. Parameters in the STA were different between patent and non-patent groups in phases 2, 3, and 4. In patent group, Vm was apparently higher and PI was lower in phases 2, 3, and 4 compared with phase 1 (P < .001). In non-patent group, no differences of Vm and PI were found within inter-group. The best cutoff value of IMD in the STA to distinguish patent from non-patent bypasses was Vm in phase 4 > 17.5 cm/s (sensitivity 94.2%, specificity 100%). In addition, the agreement for accessing bypass patency was moderate between ICG videoangiography and CTA (kappa = 0.67), IMD and ICG videoangiography (kappa = 0.73), and good between IMD and CTA (kappa = 0.86). CONCLUSION: ICG videoangiography could directly display morphology changes of bypass. IMD could be used for providing half-quantitative parameters to assess bypass patency. Vm in phase 4 > 17.5 cm/s suggesting the patency of bypass on CTA would be good. Also, compared with ICG videoangiography, IMD had more accuracy.

microRNA-3037 targeting CYP6CY2 confers imidacloprid resistance to Sitobion miscanthi (Takahashi).

The wheat aphid Sitobion miscanthi is a dominant and destructive pest in agricultural production. Insecticides are the main substances used for effective control of wheat aphids. However, their extensive application has caused severe resistance of wheat aphids to some insecticides; therefore, exploring resistance mechanisms is essential for wheat aphid management. In the present study, CYP6CY2, a new P450 gene, was isolated and overexpressed in the imidacloprid-resistant strain (SM-R) compared to the imidacloprid-susceptible strain (SM-S). The increased sensitivity of S. miscanthi to imidacloprid after knockdown of CYP6CY2 indicates that it could be associated with imidacloprid resistance. Subsequently, the posttranscriptional regulation of CYP6CY2 in the 3' UTR by miR-3037 was confirmed, and CYP6CY2 participated in imidacloprid resistance. This finding is critical for determining the role of P450 in relation to the resistance of S. miscanthi to imidacloprid. It is of great significance to understand this regulatory mechanism of P450 expression in the resistance of S. miscanthi to neonicotinoids.

Paraoxonase 1 Ameliorates Renal Lipotoxicity by Activating Lipophagy and Inhibiting Pyroptosis.

Several studies in recent years have shown that lipid overload causes lipotoxic damage to the kidney, and oxidative stress, inflammation, and autophagic arrest are all important mechanisms of renal lipotoxicity. However, effective measures with therapeutic effects on renal lipotoxicity are limited. The present study indicated the protective effect of the paraoxonase 1 (PON1) against renal lipotoxicity in high-fat diet-fed scavenger receptor class B type I-deficient (SR-BI-/-) mice. The results showed that SR-BI-/- mice exhibited significant renal pathologic characteristics, such as oxidative stress, inflammation, and fibrosis, under a normal chow diet, and were accompanied by dyslipidemia and reduced plasma PON1 activity and renal PON1 levels. PON1 overexpression significantly attenuated the above pathologic changes in the kidneys of SR-BI-/- mice fed with a high-fat diet. Mechanistically, PON1 may ameliorate renal oxidative stress by reducing reactive oxygen species production, reduce renal lipid accumulation by inhibiting AKT/mechanistic target of rapamycin kinase pathway to activate lipophagy, and reduce the occurrence of inflammation and cell death by inhibiting Nod-like receptor family protein 3 inflammasome-mediated pyroptosis. The present study is the first to show that PON1 overexpression can effectively alleviate renal lipotoxicity injury, and PON1 may be a promising therapeutic strategy for the treatment of renal lipotoxicity-related diseases.

Molecular cloning and functional analysis of polymeric immunoglobulin receptor, pIgR, gene in mandarin fish Siniperca chuatsi.

Polymeric immunoglobulin receptor (pIgR) can bind and transport immunoglobulins (Igs), thus playing a role in mucosal immunity. In this study, pIgR gene was cloned in mandarin fish, Siniperca chuatsi, with the open reading frame (ORF) of 1011 bp, encoding 336 amino acids. The pIgR protein consists of a signal peptide, an extracellular domain, a transmembrane domain and an intracellular region, with the presence of two Ig-like domains (ILDs) in the extracellular domain, as reported in other species of fish. The pIgR gene was expressed in all organs/tissues of healthy mandarin fish, with higher level observed in liver and spleen. Following the immersion infection of Flavobacterium columnare, pIgR transcripts were detected in immune related, especially mucosal tissues, with significantly increased transcription during the first two days of infection. Through transfection of plasmids expressing pIgR, IgT and IgM, pIgR was found to be interacted with IgT and IgM as revealed by co-immunoprecipitation and immunofluorescence.

Association between post-stroke smoking and stroke recurrence in first-ever ischemic stroke survivors: based on a 10-year prospective cohort.

BACKGROUND: Whether smoking is a risk factor for ischemic stroke (IS) recurrence in IS survivors is still uncovered, and evidences are sparse. Meanwhile, an add-on effect of clopidogrel was observed in myocardial infarction patients who smoked, but whether the paradox exists in IS patients is still unsolved. The objectives of this study are to explore the association between smoking behavior after index stroke and IS recurrence and to explore whether the paradox exists. METHODS: A prospective cohort of first-ever IS patients was conducted between 2010 and 2019. The prognosis and smoking features of enrolled patients were obtained via telephone follow-up every 3 months. Fine-gray model with interaction terms was applied to measure the relationships between stroke recurrence and smoking behaviors after index stroke and to explore the add-on effect of clopidogrel in smoking patients. RESULTS: There were 171 (24.26%) recurrences and 129 (18.30%) deaths during follow-up in 705 enrolled IS patients. One hundred forty-six (20.71%) patients smoked after index stroke. The hazard ratios (HRs) and 95% confidence intervals (CIs) of interaction terms between antiplatelet drug and follow-up smoking (smoking status and daily smoking amount) were 1.092 (95% CI: 0.524, 2.276) and 0.985 (95% CI: 0.941, 1.031), respectively. A significantly higher risk of recurrence was observed in patients with a higher daily smoking amount during follow-up (per cigarette), with HR being 1.027 (95% CI: 1.003, 1.052). CONCLUSIONS: Smoking could elevate the risk of IS recurrence, and IS survivor should be advised to quit or smoke less. Add-on effect of clopidogrel may not exist in smoking strokers taking clopidogrel.

Adhesion to the Brain Endothelium Selects Breast Cancer Cells with Brain Metastasis Potential.

Tumor cells metastasize from a primary lesion to distant organs mainly through hematogenous dissemination, in which tumor cell re-adhesion to the endothelium is essential before extravasating into the target site. We thus hypothesize that tumor cells with the ability to adhere to the endothelium of a specific organ exhibit enhanced metastatic tropism to this target organ. This study tested this hypothesis and developed an in vitro model to mimic the adhesion between tumor cells and brain endothelium under fluid shear stress, which selected a subpopulation of tumor cells with enhanced adhesion strength. The selected cells up-regulated the genes related to brain metastasis and exhibited an enhanced ability to transmigrate through the blood-brain barrier. In the soft microenvironments that mimicked brain tissue, these cells had elevated adhesion and survival ability. Further, tumor cells selected by brain endothelium adhesion expressed higher levels of MUC1, VCAM1, and VLA-4, which were relevant to breast cancer brain metastasis. In summary, this study provides the first piece of evidence to support that the adhesion of circulating tumor cells to the brain endothelium selects the cells with enhanced brain metastasis potential.

Silencing of CYP6AS160 in Solenopsis invicta Buren by RNA interference enhances worker susceptibility to fipronil.

Cytochrome P450 monooxygenases play a key role in pest resistance to insecticides by detoxification. Four new P450 genes, CYP6AS160, CYP6AS161, CYP4AB73 and CYP4G232 were identified from Solenopsis invicta. CYP6AS160 was highly expressed in the abdomen and its expression could be induced significantly with exposure to fipronil, whereas CYP4AB73 was not highly expressed in the abdomen and its expression could not be significantly induced following exposure to fipronil. Expression levels of CYP6AS160 and CYP4AB73 in workers were significantly higher than that in queens. RNA interference-mediated gene silencing by feeding on double-stranded RNA (dsRNA) found that the levels of this transcript decreased (by maximum to 64.6%) when they fed on CYP6AS160-specific dsRNA. Workers fed dsCYP6AS160 had significantly higher mortality after 24 h of exposure to fipronil compared to controls. Workers fed dsCYP6AS160 had reduced total P450 activity of microsomal preparations toward model substrates p-nitroanisole. However, the knockdown of a non-overexpressed P450 gene, CYP4AB73 did not lead to an increase of mortality or a decrease of total P450 activity. The knockdown effects of CYP6AS160 on worker susceptibility to fipronil, combined with our other findings, indicate that CYP6AS160 is responsible for detoxification of fipronil. Feeding insects dsRNA may be a general strategy to trigger RNA interference and may find applications in entomological research and in the control of insect pests in the field.

CYP4CJ6-mediated resistance to two neonicotinoid insecticides in Sitobion miscanthi (Takahashi).

The wheat aphid Sitobion miscanthi (CWA) is an important harmful pest in wheat fields. Insecticide application is the main method to effectively control wheat aphids. However, CWA has developed resistance to some insecticides due to its extensive application, and understanding resistance mechanisms is crucial for the management of CWA. In our study, a new P450 gene, CYP4CJ6, was identified from CWA and showed a positive response to imidacloprid and thiamethoxam. Transcription of CYP4CJ6 was significantly induced by both imidacloprid and thiamethoxam, and overexpression of CYP4CJ6 in the imidacloprid-resistant strain was also observed. The sensitivity of CWA to these two insecticides was increased after the knockdown of CYP4CJ6. These results indicated that CYP4CJ6 could be associated with CWA resistance to imidacloprid and thiamethoxam. Subsequently, the posttranscriptional regulatory mechanism was assessed, and miR-316 was confirmed to participate in the posttranscriptional regulation of CYP4CJ6. These results are crucial for clarifying the roles of P450 in the resistance of CWA to insecticides.

MicroRNA-190-5p confers chlorantraniliprole resistance by regulating CYP6K2 in Spodoptera frugiperda (Smith).

The fall armyworm Spodoptera frugiperda (Smith) (FAA) is responsible for considerable losses in grain production, and chemical control is the most effective strategy. However, frequent insecticide application can lead to the development of resistance. In insects, cytochrome P450 plays a crucial role in insecticide metabolism. CYP6K2 is related to FAA resistance to chlorantraniliprole. However, the regulatory mechanism of CYP6K2 expression is poorly understood. In this study, a conserved target of isolated miRNA-190-5p was located in the 3' UTR of CYP6K2 in FAA. A luciferase reporter analysis showed that in FAA, miRNA-190-5p can combine with the 3'UTR of CYP6K2 to suppress its expression. Injected miRNA-190-5p agomir significantly reduced CYP6K2 abundance by 54.6% and reduced tolerance to chlorantraniliprole in FAA larvae, whereas injected miRNA-190-5p antagomir significantly increased CYP6K2 abundance by 1.77-fold and thus improved chlorantraniliprole tolerance in FAA larvae. These results provide a basis for further research on the posttranscriptional regulatory mechanism of CYP6K2 and will facilitate further study on the function of miRNAs in regulating tolerance to chlorantraniliprole in FAA.

MicroRNA-263b confers imidacloprid resistance in Sitobion miscanthi (Takahashi) by regulating the expression of the nAChRß1 subunit.

The Chinese wheat aphid Sitobion miscanthi (CWA) is an important harmful pest in wheat fields. Imidacloprid plays a critical role in controlling pests with sucking mouthparts. However, imidacloprid-resistant pests have been observed after insecticide overuse. Point mutations and low expression levels of the nicotinic acetylcholine receptor ß1 (nAchRß1) subunit are the main imidacloprid-resistant mechanisms. However, the regulatory mechanism underlying nAChRß1 subunit expression is poorly understood. In this study, a target of miR-263b was isolated from the 5'UTR of the nAchRß1 subunit in the CWA. Low expression levels were found in the imidacloprid-resistant strain CWA. Luciferase reporter assays showed that miR-263b could combine with the 5'UTR of the nAChRß1 subunit and suppress its expression by binding to a site in the CWA. Aphids treated with the miR-263b agomir exhibited a significantly reduced abundance of the nAchRß1 subunit and increased imidacloprid resistance. In contrast, aphids treated with the miR-263b antagomir exhibited significantly increased nAchRß1 subunit abundance and decreased imidacloprid resistance. These results provide a basis for an improved understanding of the posttranscriptional regulatory mechanism of the nAChRß1 subunit and further elucidate the function of miRNAs in regulating susceptibility to imidacloprid in the CWA. These results provide a better understanding of the mechanisms of posttranscriptional regulation of nAChRß1 and will be helpful for further studies on the role of miRNAs in the regulation of nAChRß1 subunit resistance in homopteran pests.

Regulators of calcineurin 1 deficiency attenuates tubulointerstitial fibrosis through improving mitochondrial fitness.

Renal fibrosis is the common pathological process of various chronic kidney diseases (CKD). Recent studies indicate that mitochondrial fragmentation is closely associated with renal fibrosis in CKD. However, the molecular mechanisms leading to mitochondrial fragmentation remain to be elucidated. The present study investigated the role of regulators of calcineurin 1 (RCAN1) in mitochondrial fission and renal interstitial fibrosis using conditional knockout mice in which RCAN1 was genetically deleted in tubular epithelial cells (TECs). TEC-specific deletion of RCAN1 attenuated tubulointerstitial fibrosis and epithelial to mesenchymal transition (EMT)-like phenotype change after unilateral ureteral obstruction (UUO) and ischemia reperfusion injury (IRI) through suppressing TGF-ß1/Smad3 signaling pathway. TEC-specific deletion of RCAN1 also reduced the tubular apoptosis after UUO by inhibiting cytochrome c/caspase-9 pathway. Ultrastructure analysis revealed a marked decrease in mitochondrial fragmentation in TECs of RCAN1-deficient mice in experimental CKD models. The expression of mitochondrial profission proteins dynamin-related protein 1 (Drp1) and mitochondrial fission factor (Mff) was also downregulated in obstructed kidney of TEC-specific RCAN1-deficient mice. Furthermore, TEC-specific deletion of RCAN1 attenuated the dysfunctional tubular autophagy by regulating PINK1/Parkin-induced mitophagy in CKD. RCAN1 knockdown and knockout similarly improved the mitochondrial quality control in HK-2 cells and primary cultured mouse tubular cells stimulated by TGF-ß1. Put together, our data indicated that RCAN1 plays an important role in the progression of tubulointerstitial fibrosis through regulating the mitochondrial quality. Therefore, targeting RCAN1 may provide a potential therapeutic approach in CKD.

Variations in the light absorption coefficients of phytoplankton, non-algal particles and dissolved organic matter in reservoirs across China.

Reservoirs were critical sources of drinking water for many large cities around the world, but progress in the development of large-scale monitoring protocols to obtain timely information about water quality had been hampered by the complex nature of inland waters and the various optical conditions exhibited by these aquatic ecosystems. In this study, we systematically investigated the absorption coefficient of different optically-active constituents (OACs) in 120 reservoirs of different trophic states across five eco-regions in China. The relationships were found between phytoplankton absorption coefficient at 675 nm (aph (675)) and Chlorophyll a (Chla) concentration in different regions (R2:0.60-0.82). The non-algal particle (NAP) absorption coefficient (aNAP) showed an increasing trend for reservoirs with trophic states. Significant correlation (p < 0.05) was observed between chromophoric dissolved organic matter (CDOM) absorption and water chemical parameters. The influencing factors for contributing the relative proportion of OACs absorption including the hydrological factors and water quality factors were analyzed. The non-water absorption budget from our data showed the variations of the dominant absorption types which underscored the need to develop and parameterize region-specific bio-optical models for large-scale assessment in water reservoirs.

Proteome-wide Tyrosine Phosphorylation Analysis Reveals Dysregulated Signaling Pathways in Ovarian Tumors.

The recent accomplishment of comprehensive proteogenomic analysis of high-grade serous ovarian carcinoma (HGSOC) tissues reveals cancer associated molecular alterations were not limited to variations among DNA, and mRNA/protein expression, but are a result of complex reprogramming of signaling pathways/networks mediated by the protein and post-translational modification (PTM) interactomes. A systematic, multiplexed approach interrogating enzyme-substrate relationships in the context of PTMs is fundamental in understanding the dynamics of these pathways, regulation of cellular processes, and their roles in disease processes. Here, as part of Clinical Proteomic Tumor Analysis Consortium (CPTAC) project, we established a multiplexed PTM assay (tyrosine phosphorylation, and lysine acetylation, ubiquitylation and SUMOylation) method to identify protein probes' PTMs on the human proteome array. Further, we focused on the tyrosine phosphorylation and identified 19 kinases are potentially responsible for the dysregulated signaling pathways observed in HGSOC. Additionally, elevated kinase activity was observed when 14 ovarian cancer cell lines or tumor tissues were subjected to test the autophosphorylation status of PTK2 (pY397) and PTK2B (pY402) as a proxy for kinase activity. Taken together, this report demonstrates that PTM signatures based on lysate reactions on human proteome array is a powerful, unbiased approach to identify dysregulated PTM pathways in tumors.

Identification of differentially expressed microRNAs under imidacloprid exposure in Sitobion miscanthi.

Imidacloprid is a neonicotinoid that targets sucking pests, such as aphids and the green leaf bug and has been widely applied in wheat fields to control wheat aphids in China. To investigate the involvement of miRNAs in imidacloprid resistance, we sequenced small RNA libraries of Sitobion miscanthi Fabricius, across two different treatments using Illumina short-read sequencing technology. As a result, 265 microRNAs (miRNAs), of which 242 were known and 23 were novel, were identified. Quantitative analysis of miRNA levels showed that 23 miRNAs were significantly up-regulated, and 54 miRNAs were significantly down-regulated in the nymphs of S. miscanthi treated with imidacloprid in comparison with those of the control. Modulation of the abundances of differentially expressed miRNAs, smi-miR-316, smi-miR-1000, and smi-miR-iab-4 by the addition of the corresponding antagomir/inhibitor to the artificial diet significantly changed the susceptibility of S. miscanthi to imidacloprid. Subsequently, the post-transcriptional regulatory mechanism was conducted, smi-miR-278 and smi-miR-316 were confirmed to be participated in the post-transcriptional regulation of nAChRα1A and CYP4CJ6, respectively. The results suggested that miRNAs differentially expressed in response to imidacloprid could play a critical regulatory role in the metabolism of S. miscanthi to imidacloprid.

Remote estimates of CDOM using Sentinel-2 remote sensing data in reservoirs with different trophic states across China.

Chromophoric dissolved organic matter (DOM) is called as CDOM which could affect the optical properties of surface waters, and is a useful parameter for monitoring complex inland aquatic systems. Large-scale monitoring of CDOM using remote-sensing has been a challenge due to the poor transferability of CDOM retrieval models across regions. To overcome these difficulties, a study is conducted using Sentinel-2 images, in situ reflectance spectral data, and water chemical parameters at 93 water reservoirs across China classified by trophic state. Empirical algorithms are established between CDOM absorption coefficient aCDOM(355) and reflectance band ratio (B5/B2,vegetation Red Edge/Blue) acquired in situ and via Sentinel-2 MSI sensors. Relationships are stronger (r2 > 0.7, p < 0.05) when analysis is conducted separately by trophic states. Validation models show that, by accounting for trophic state of reservoirs and using B5/B2 band ratios, it is possible to expand the geographical range of remote sensing-based models to determine CDOM. However, the accuracy of model validation decreased from oligotrophic (r2: 0.86) to eutrophic reservoirs (r2: 0.82), likely due to increased complexity of CDOM sources in nutrient-rich systems. This study provides a strategy for using local and remote-sensing data to monitor the spatial variations of CDOM in reservoirs based on different trophic states, and will contribute to water resources management.