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  • 1
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    Landslide susceptibility mapping using machine learning for Wenchuan County, Sichuan province, China
    EDP Sciences ; 2020
    In:  E3S Web of Conferences Vol. 198 ( 2020), p. 03023-
    Details
    In: E3S Web of Conferences, EDP Sciences, Vol. 198 ( 2020), p. 03023-
    Abstract: Landslide susceptibility mapping is a method used to assess the probability and spatial distribution of landslide occurrences. Machine learning methods have been widely used in landslide susceptibility in recent years. In this paper, six popular machine learning algorithms namely logistic regression, multi-layer perceptron, random forests, support vector machine, Adaboost, and gradient boosted decision tree were leveraged to construct landslide susceptibility models with a total of 1365 landslide points and 14 predisposing factors. Subsequently, the landslide susceptibility maps (LSM) were generated by the trained models. LSM shows the main landslide zone is concentrated in the southeastern area of Wenchuan County. The result of ROC curve analysis shows that all models fitted the training datasets and achieved satisfactory results on validation datasets. The results of this paper reveal that machine learning methods are feasible to build robust landslide susceptibility models.
    Type of Medium: Online Resource
    ISSN: 2267-1242
    URL: Article
    DOI: 10.1051/e3sconf/202019803023
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2020
    detail.hit.zdb_id: 2755680-3
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  • 2
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    Spatial prediction of landslide susceptibility based on the neighborhood rough set
    IOP Publishing ; 2020
    In:  IOP Conference Series: Materials Science and Engineering Vol. 780, No. 7 ( 2020-03-01), p. 072052-
    Details
    In: IOP Conference Series: Materials Science and Engineering, IOP Publishing, Vol. 780, No. 7 ( 2020-03-01), p. 072052-
    Abstract: This paper discusses the feasibility of reducing the landslide inducing factors by the neighborhood rough set algorithm in data processing section, which could improve the accuracy and timeliness of landslides susceptibility prediction models effectively. 15 predisposing factors for a continuous value that has not been graded were reduced by nighborhood rough set, a granularity calculation method, based on the importance degree of each factor. Then the combination of factors before and after optimization was put into random forest (RF) and support vector machine (SVM) for modelling. ROC curve and statistical indicators show that: the average performance of the reduced factors combination is superior to that before optimization. In addition, we used the RF which has a better performs in evaluation to map the landslides susceptibility in Jiuzhaigou area, discuss the timeliness of the assessment of landslides prediction and the weight of the predisposing factors.
    Type of Medium: Online Resource
    ISSN: 1757-8981 , 1757-899X
    URL: Article
    DOI: 10.1088/1757-899X/780/7/072052
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2020
    detail.hit.zdb_id: 2506501-4
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  • 3
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    Neonatal hair profiling reveals a metabolic phenotype of monochorionic twins with selective intrauterine growth restriction and abnormal umbilical artery flow
    Springer Science and Business Media LLC ; 2020
    In:  Molecular Medicine Vol. 26, No. 1 ( 2020-12)
    Details
    In: Molecular Medicine, Springer Science and Business Media LLC, Vol. 26, No. 1 ( 2020-12)
    Abstract: Selective intrauterine fetal growth restriction (sIUGR) in monochorionic diamniotic twins, especially types 2 & 3 with abnormal umbilical artery Doppler, results in increased risk of fetal/perinatal mortality and postnatal disability. We investigate whether the hair metabolome profiles of neonates were associated with the pathophysiological differences across the different clinical forms of sIUGR in twins. Methods Hair samples were collected at delivery from 10 pairs of type 1 sIUGR twins, 8 pairs of types 2 & 3 sIUGR twins, and 11 pairs of twins without sIUGR. The hair metabolome was characterized using gas chromatography-mass spectrometry. Results Our results demonstrated that the hair metabolite profiles of the different sIUGR subclinical forms were associated with the averaged fetal growth rate after 28 weeks of gestation but not with birthweight. The hair profiles were capable of discriminating type2 & 3 sIUGR twins from twins without sIUGR. In particular, the metabolites 2-aminobutyric acid, cysteine, alanine, and tyrosine all displayed areas under the receiver operating characteristic curve were above 0.9. The metabolic pathway analysis highlighted the associations of sIUGR twins with abnormal umbilical artery flow with increased metabolites from a nutrient depletion pathway, glutathione metabolism, and nerve development. Conclusion This study offers novel insight into the severity of intrauterine ischemia and hypoxia for T2 & 3 sIUGR twins, through evaluation of the neonatal hair metabolome.
    Type of Medium: Online Resource
    ISSN: 1076-1551 , 1528-3658
    URL: Article
    DOI: 10.1186/s10020-020-00160-8
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 1475577-4
    detail.hit.zdb_id: 1283676-X
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  • 4
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    Selection of landslide affecting factors based on strong association analysis
    IOP Publishing ; 2020
    In:  IOP Conference Series: Materials Science and Engineering Vol. 780, No. 7 ( 2020-03-01), p. 072051-
    Details
    In: IOP Conference Series: Materials Science and Engineering, IOP Publishing, Vol. 780, No. 7 ( 2020-03-01), p. 072051-
    Abstract: The performance of models in landslide susceptibility mapping largely depends on the selection and combination of affecting factors. The Apriori algorithm proposed in this paper is a factor selection method of strong association analysis, which can select the factors that are most likely to induce landslides from 15 affecting factors. Then combine the origin and optimized factors to build the prediction model of landslide susceptibility by support vector machine (SVM) in machine learning. Afterwards, we verifying the landslide points in the dataset to measure the accuracy of the model. Ultimately, ROC curve was adopted to evaluate the prediction results of the two models. The result reveals that the model based on the combination of optimized factors (AUC 1=0.930) is superior to that based on 15 affecting factors (AUC 2=0.898).
    Type of Medium: Online Resource
    ISSN: 1757-8981 , 1757-899X
    URL: Article
    DOI: 10.1088/1757-899X/780/7/072051
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2020
    detail.hit.zdb_id: 2506501-4
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  • 5
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    Table9.XLSX
    Frontiers Media SA ; 2023
    In:  Frontiers in Pharmacology Vol. 14 ( 2023-5-25)
    Details
    In: Frontiers in Pharmacology, Frontiers Media SA, Vol. 14 ( 2023-5-25)
    Abstract: Introduction: IgA nephropathy (IgAN) is the most common disease leading to end-stage renal disease, and tubular fibrosis represents an important risk factor for disease progression. However, research on early molecular diagnostic indicators of tubular fibrosis and the mechanisms underlying disease progression is still lacking. Methods: The GSE93798 dataset was downloaded from the GEO database. DEGs were screened and analyzed for GO and KEGG enrichment in IgAN. The least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) algorithms were applied to screen for hub secretory genes. The expression and diagnostic efficacy of hub genes were confirmed by the GSE35487 dataset. ELISA was applied to detect the expression of APOC1 in serum. The expression and localization of hub genes in IgAN were verified by the expression of IHC and IF in human kidney tissues, and the correlation of expression with clinical data was verified in the Nephroseq database. Finally, cellular experiments clarified the role of hub genes in the signaling pathway. Results: A total of 339 DEGs were identified in IgAN, of which 237 were upregulated and 102 downregulated. The KEGG signaling pathway is enriched in the ECM–receptor interaction and AGE-RAGE signaling pathway. APOC1, ALB, CCL8, CXCL2, SRPX2, and TGFBI identified six hub secretory genes using the LASSO and SVM-RFE algorithms. In vivo and in vitro experiments demonstrated that APOC1 expression was elevated in IgAN. The serum concentration of APOC1 was 1.232 ± 0.1812 μg/ml in IgAN patients, whereas it was 0.3956 ± 0.1233 μg/ml in healthy individuals. APOC1 exhibited high diagnostic efficacy for IgAN (AUC of 99.091%, specificity of 95.455%, and sensitivity of 99.141%) in the GSE93798 dataset. APOC1 expression negatively correlated with eGFR ( R 2 = 0.2285, p = 0.0385) and positively correlated with serum creatinine ( R 2 = 0.41, p = 0.000567) in IgAN. APOC1 exacerbated renal fibrosis, possibly in part by activating the NF-κB pathway in IgAN. Conclusion: APOC1 was identified as the core secretory gene of IgAN, which was closely associated with blood creatinine and eGFR and had significant efficacy in the diagnosis of IgAN. Mechanistic studies revealed that the knockdown of APOC1 could improve IgAN renal fibrosis by inhibiting the NF pathway, which may be a potential therapeutic target for improving renal fibrosis in IgAN.
    Type of Medium: Online Resource
    ISSN: 1663-9812
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    DOI: 10.3389/fphar.2023.1181435
    DOI: 10.3389/fphar.2023.1181435.s001
    DOI: 10.3389/fphar.2023.1181435.s002
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    DOI: 10.3389/fphar.2023.1181435.s021
    DOI: 10.3389/fphar.2023.1181435.s022
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2587355-6
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  • 6
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    DataSheet_1.zip
    Frontiers Media SA ; 2023
    In:  Frontiers in Endocrinology Vol. 14 ( 2023-2-20)
    Details
    In: Frontiers in Endocrinology, Frontiers Media SA, Vol. 14 ( 2023-2-20)
    Abstract: Diabetic nephropathy is the leading cause of end-stage renal disease, which imposes a huge economic burden on individuals and society, but effective and reliable diagnostic markers are still not available. Methods Differentially expressed genes (DEGs) were characterized and functional enrichment analysis was performed in DN patients. Meanwhile, a weighted gene co-expression network (WGCNA) was also constructed. For further, algorithms Lasso and SVM-RFE were applied to screening the DN core secreted genes. Lastly, WB, IHC, IF, and Elias experiments were applied to demonstrate the hub gene expression in DN, and the research results were confirmed in mouse models and clinical specimens. Results 17 hub secretion genes were identified in this research by analyzing the DEGs, the important module genes in WGCNA, and the secretion genes. 6 hub secretory genes (APOC1, CCL21, INHBA, RNASE6, TGFBI, VEGFC) were obtained by Lasso and SVM-RFE algorithms. APOC1 was discovered to exhibit elevated expression in renal tissue of a DN mouse model, and APOC1 is probably a core secretory gene in DN. Clinical data demonstrate that APOC1 expression is associated significantly with proteinuria and GFR in DN patients. APOC1 expression in the serum of DN patients was 1.358±0.1292μg/ml, compared to 0.3683±0.08119μg/ml in the healthy population. APOC1 was significantly elevated in the sera of DN patients and the difference was statistical significant (P & gt; 0.001). The ROC curve of APOC1 in DN gave an AUC = 92.5%, sensitivity = 95%, and specificity = 97% (P & lt; 0.001). Conclusions Our research indicates that APOC1 might be a novel diagnostic biomarker for diabetic nephropathy for the first time and suggest that APOC1 may be available as a candidate intervention target for DN.
    Type of Medium: Online Resource
    ISSN: 1664-2392
    URL: Article
    URL: Article
    DOI: 10.3389/fendo.2023.1102634
    DOI: 10.3389/fendo.2023.1102634.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2592084-4
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  • 7
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    Interspecies/Intergroup Complementation of Orthotospovirus Replication and Movement through Reverse Genetics Systems
    American Society for Microbiology ; 2023
    In:  Journal of Virology Vol. 97, No. 4 ( 2023-04-27)
    Details
    In: Journal of Virology, American Society for Microbiology, Vol. 97, No. 4 ( 2023-04-27)
    Abstract: Orthotospoviruses, the plant-infecting bunyaviruses, cause serious diseases in agronomic crops and pose major threats to global food security. The family of Tospoviridae contains more than 30 members that are classified into two geographic groups, American-type and Euro/Asian-type orthotospovirus. However, the genetic interaction between different species and the possibility, during mixed infections, for transcomplementation of gene functions by orthotospoviruses from different geographic groups remains underexplored. In this study, minireplicon-based reverse genetics (RG) systems have been established for Impatiens necrotic spot virus (INSV) (an American-type orthotospovirus) and for Calla lily chlorotic spot virus and Tomato zonate spot virus (CCSV and TZSV) (two representative Euro/Asian orthotospoviruses). Together with the earlier established RG system for Tomato spotted wilt virus (TSWV), a type species of the Orthotospovirus American-clade, viral replicase/movement proteins were exchanged and analyzed on interspecies transcomplementation. Whereas the homologous RNA-dependent RNA polymerase (RdRp) and nucleocapsid (N) protein supported the replication of orthotospoviruses from both geographic groups, heterologous combinations of RdRp from one group and N from the other group were unable to support the replication of viruses from both groups. Furthermore, the NSm movement protein (MP), from both geographic groups of orthotospoviruses, was able to transcomplement heterologous orthotospoviruses or a positive-strand Cucumber mosaic virus (CMV) in their movement, albeit with varying efficiency. MP from Rice stripe tenuivirus (RSV), a plant-infecting bunyavirus that is distinct from orthotospoviruses, or MP from CMV also moves orthotospoviruses. Our findings gain insights into the genetic interaction/reassortant potentials for the segmented plant orthotospoviruses. IMPORTANCE Orthotospoviruses are agriculturally important negative-strand RNA viruses and cause severe yield-losses on many crops worldwide. Whereas the emergence of new animal-infecting bunyaviruses is frequently associated with genetic reassortants, this issue remains underexposed with the plant-infecting orthotospovirus. With the development of reverse genetics systems for orthotospoviruses from different geographic regions, the interspecies/intergroup replication/movement complementation between American- and Euro/Asian-type orthotospoviruses were investigated. Genomic RNAs from American orthotospoviruses can be replicated by the RdRp and N from those of Euro/Asia-group orthotospoviruses, and vice versa. However, their genomic RNAs cannot be replicated by a heterologous combination of RdRp from one geographic group and N from another geographic group. Cell-to-cell movement of viral entity is supported by NSm from both geographic groups, with highest efficiency by NSm from viruses belonging to the same group. Our findings provide important insights into the genetic interaction and exchange ability of viral gene functions between different species of orthotospovirus.
    Type of Medium: Online Resource
    ISSN: 0022-538X , 1098-5514
    URL: Article
    DOI: 10.1128/jvi.01809-22
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2023
    detail.hit.zdb_id: 1495529-5
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  • 8
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    Comparison of three statistical methods for earthquake-induced landslides susceptibility in Lushan region China
    EDP Sciences ; 2020
    In:  E3S Web of Conferences Vol. 198 ( 2020), p. 02024-
    Details
    In: E3S Web of Conferences, EDP Sciences, Vol. 198 ( 2020), p. 02024-
    Abstract: This paper adopts three models including the logistic regression (LR), support vector machine (SVM), and random forest (RF) to study the susceptibility distribution rule of susceptibility distribution of earthquakes induced landslides. The Area Under the Receiver Operating Characteristic (ROC) curve (AUC) and Ratio were used for evaluating the model’s accuracy and mapping availability susceptibility assessment. The result shows that RF has the best performance in the susceptibility assessment of earthquake-induced landslides in the Lushan region of China.
    Type of Medium: Online Resource
    ISSN: 2267-1242
    URL: Article
    DOI: 10.1051/e3sconf/202019802024
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2020
    detail.hit.zdb_id: 2755680-3
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  • 9
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    The Resonance and Adaptation of Neurospora crassa Circadian and Conidiation Rhyth ms to Short Light-Dark Cycles
    MDPI AG ; 2021
    In:  Journal of Fungi Vol. 8, No. 1 ( 2021-12-29), p. 27-
    Details
    In: Journal of Fungi, MDPI AG, Vol. 8, No. 1 ( 2021-12-29), p. 27-
    Abstract: Circadian clocks control the physiological and behavioral rhythms to adapt to the environment with a period of ~24 h. However, the influences and mechanisms of the extreme light/dark cycles on the circadian clock remain unclear. We showed that, in Neurospora crassa, both the growth and the microconidia production contribute to adaptation in LD12:12 (12 h light/12 h dark, periodically). Mathematical modeling and experiments demonstrate that in short LD cycles, the expression of the core clock protein FREQUENCY was entrained to the LD cycles when LD 〉 3:3 while it free ran when T ≤ LD3:3. The conidial rhythmicity can resonate with a series of different LD conditions. Moreover, we demonstrate that the existence of unknown blue light photoreceptor(s) and the circadian clock might promote the conidiation rhythms that resonate with the environment. The ubiquitin E3 ligase FWD-1 and the previously described CRY-dependent oscillator system were implicated in regulating conidiation under short LD conditions. These findings shed new light on the resonance of Neurospora circadian clock and conidiation rhythms to short LD cycles, which may benefit the understandings of both the basic regulatory aspects of circadian clock and the adaptation of physiological rhythms to the extreme conditions.
    Type of Medium: Online Resource
    ISSN: 2309-608X
    URL: Article
    DOI: 10.3390/jof8010027
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2784229-0
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  • 10
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    Distribution of antibiotic-resistant bacteria in aerobic composting of swine manure with different antibiotics
    Springer Science and Business Media LLC ; 2021
    In:  Environmental Sciences Europe Vol. 33, No. 1 ( 2021-12)
    Details
    In: Environmental Sciences Europe, Springer Science and Business Media LLC, Vol. 33, No. 1 ( 2021-12)
    Abstract: Livestock manure is an important reservoir of antibiotic-resistant bacteria (ARB) and antibiotic-resistance genes (ARGs). The bacterial community structure and diversity are usually studied using high-throughput sequencing that cannot provide direct evidence for ARB changes. Thus, little is known about the distribution of ARB, especially in the presence of different antibiotics in composting process. In this study, the fate of ARB was investigated in aerobic composting of swine manure, using chlortetracycline, sulfamethoxazole, lincomycin, and ciprofloxacin as typical antibiotics. The abundance and species of ARB were analyzed systematically to evaluate their ecological risk at different stages of composting. Results The absolute abundance of total ARB decreased, while the relative abundance increased on day 2. The relative abundance of lincomycin-resistant bacteria was higher than other ARBs during the whole composting process. The absolute abundance of four ARBs was 9.42 × 10 6 –2.51 × 10 2  CFU/g (lincomycin-  〉  chlortetracycline-  〉  sulfamethoxazole-  〉  ciprofloxacin-  〉  multiple antibiotic-resistant bacteria), and they were not completely inactivated at the end of composting. Antibiotics led to a partial proliferation of ARBs including Corynebacterium , Sporosarcina , Solibacillus , and Acinetobacter . Especially, Corynebacterium , a pathogenic genus, was observed in chlortetracycline and lincomycin treatments. Conclusion Among the antibiotics studied, lincomycin showed the highest ecological risk, due to it expanded the range of lincomycin-resistant bacteria at the phyla level (Firmicutes, Actinobacteria, and Proteobacteria). The principal co-ordinates analysis indicated that the bacterial community structure was primarily associated with the composting stages rather than antibiotic types. Possible potential hosts and the related to the decrease of ARGs abundance were indicated based on the network analysis. The decrease of culturable Proteobacteria and the increase of culturable Firmicutes ( Solibacillus , Bacillus ) partially explained the high degradation rate of various ARGs with the progress of composting in this study. These results provided important information for the control of antibiotic resistance in composting.
    Type of Medium: Online Resource
    ISSN: 2190-4707 , 2190-4715
    URL: Article
    DOI: 10.1186/s12302-021-00535-6
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2593962-2
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