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International Monetary Fund. "A Simple Dge Model for Inflation Targeting." IMF Working Papers 07, no. 197 (2007): 1. http://dx.doi.org/10.5089/9781451867619.001.
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DeBacker, Jason, Richard W. Evans, and Kerk L. Phillips. "Integrating Microsimulation Models of Tax Policy into a DGE Macroeconomic Model." Public Finance Review 47, no. 2 (February 5, 2019): 207–75. http://dx.doi.org/10.1177/1091142118816744.
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This article proposes a method for integrating individual effective tax rates and marginal tax rates computed from a microsimulation (partial equilibrium) model of tax policy with a dynamic general equilibrium model of tax policy that can provide macroeconomic analysis or dynamic scores of tax reforms. Our approach captures the rich heterogeneity, realistic demographics, and tax-code detail of the microsimulation model and allows this detail to inform a general equilibrium model with a relatively high degree of heterogeneity. In addition, we propose a functional form in which tax rates depend jointly on the levels of both capital income and labor income.
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Schaarschmidt, Stephanie, Axel Fischer, Ellen Zuther, and Dirk K. Hincha. "Evaluation of Seven Different RNA-Seq Alignment Tools Based on Experimental Data from the Model Plant Arabidopsis thaliana." International Journal of Molecular Sciences 21, no. 5 (March 3, 2020): 1720. http://dx.doi.org/10.3390/ijms21051720.
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Quantification of gene expression is crucial to connect genome sequences with phenotypic and physiological data. RNA-Sequencing (RNA-Seq) has taken a prominent role in the study of transcriptomic reactions of plants to various environmental and genetic perturbations. However, comparative tests of different tools for RNA-Seq read mapping and quantification have been mainly performed on data from animals or humans, which necessarily neglect, for example, the large genetic variability among natural accessions within plant species. Here, we compared seven computational tools for their ability to map and quantify Illumina single-end reads from the Arabidopsis thaliana accessions Columbia-0 (Col-0) and N14. Between 92.4% and 99.5% of all reads were mapped to the reference genome or transcriptome and the raw count distributions obtained from the different mappers were highly correlated. Using the software DESeq2 to determine differential gene expression (DGE) between plants exposed to 20 °C or 4 °C from these read counts showed a large pairwise overlap between the mappers. Interestingly, when the commercial CLC software was used with its own DGE module instead of DESeq2, strongly diverging results were obtained. All tested mappers provided highly similar results for mapping Illumina reads of two polymorphic Arabidopsis accessions to the reference genome or transcriptome and for the determination of DGE when the same software was used for processing.
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Angarita, Belcy K., Rodolfo J. C. Cantet, Kaitlin E. Wurtz, Carly I. O’Malley, Janice M. Siegford, Catherine W. Ernst, Simon P. Turner, and Juan P. Steibel. "Estimation of indirect social genetic effects for skin lesion count in group-housed pigs by quantifying behavioral interactions1." Journal of Animal Science 97, no. 9 (September 2019): 3658–68. http://dx.doi.org/10.1093/jas/skz244.
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Abstract Mixing of pigs into new social groups commonly induces aggressive interactions that result in skin lesions on the body of the animals. The relationship between skin lesions and aggressive behavioral interactions in group-housed pigs can be analyzed within the framework of social genetic effects (SGE). This study incorporates the quantification of aggressive interactions between pairs of animals in the modeling of SGE for skin lesions in different regions of the body in growing pigs. The dataset included 792 pigs housed in 59 pens. Skin lesions in the anterior, central, and caudal regions of the body were counted 24 h after pig mixing. Animals were video-recorded for 9 h postmixing and trained observers recorded the type and duration of aggressive interactions between pairs of animals. The number of seconds that pairs of pigs spent engaged in reciprocal fights and unilateral attack behaviors were used to parametrize the intensity of social interactions (ISI). Three types of models were fitted: direct genetic additive model (DGE), traditional social genetic effect model (TSGE) assuming uniform interactions between dyads, and an intensity-based social genetic effect model (ISGE) that used ISI to parameterize SGE. All models included fixed effects of sex, replicate, lesion scorer, weight at mixing, premixing lesion count, and the total time that the animal spent engaged in aggressive interactions (reciprocal fights and unilateral attack behaviors) as a covariate; a random effect of pen; and a random direct genetic effect. The ISGE models recovered more direct genetic variance than DGE and TSGE, and the estimated heritabilities (h^D2) were highest for all traits (P < 0.01) for the ISGE with ISI parametrized with unilateral attack behavior. The TSGE produced estimates that did not differ significantly from DGE (P > 0.5). Incorporating the ISI into ISGE, even in a small dataset, allowed separate estimation of the genetic parameters for direct and SGE, as well as the genetic correlation between direct and SGE (r^ds), which was positive for all lesion traits. The estimates from ISGE suggest that if behavioral observations are available, selection incorporating SGE may reduce the consequences of aggressive behaviors after mixing pigs.
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Lane, Sarah M., Alastair J. Wilson, and Mark Briffa. "Analysis of direct and indirect genetic effects in fighting sea anemones." Behavioral Ecology 31, no. 2 (January 10, 2020): 540–47. http://dx.doi.org/10.1093/beheco/arz217.
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Abstract Theoretical models of animal contests such as the Hawk-Dove game predict that variation in fighting behavior will persist due to mixed evolutionarily stable strategies (ESS) under certain conditions. However, the genetic basis for this variation is poorly understood and a mixed ESS for fighting can be interpreted in more than one way. Specifically, we do not know whether variation in aggression within a population arises from among-individual differences in fixed strategy (determined by an individual’s genotype—direct genetic effects [DGEs]), or from within-individual variation in strategy across contests. Furthermore, as suggested by developments of the original Hawk-Dove model, within-individual variation in strategy may be dependent on the phenotype and thus genotype of the opponent (indirect genetic effects—IGEs). Here we test for the effect of DGEs and IGEs during fights in the beadlet sea anemone Actinia equina. By exploiting the unusual reproductive system of sea anemones, combined with new molecular data, we investigate the role of both additive (DGE + IGE) and non-additive (DGE × IGE) genetic effects on fighting parameters, the latter of which have been hypothesized but never tested for explicitly. We find evidence for heritable variation in fighting ability and that fight duration increases with relatedness. Fighting success is influenced additively by DGEs and IGEs but we found no evidence for non-additive IGEs. These results indicate that variation in fighting behavior is driven by additive indirect genetic effects (DGE + IGE), and support a core assumption of contest theory that strategies are fixed by DGEs.
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Zhou, Sheng, Xin Wang, Jiajun Bu, Martin Ester, Pinggang Yu, Jiawei Chen, Qihao Shi, and Can Wang. "DGE: Deep Generative Network Embedding Based on Commonality and Individuality." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6949–56. http://dx.doi.org/10.1609/aaai.v34i04.6178.
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Network embedding plays a crucial role in network analysis to provide effective representations for a variety of learning tasks. Existing attributed network embedding methods mainly focus on preserving the observed node attributes and network topology in the latent embedding space, with the assumption that nodes connected through edges will share similar attributes. However, our empirical analysis of real-world datasets shows that there exist both commonality and individuality between node attributes and network topology. On the one hand, similar nodes are expected to share similar attributes and have edges connecting them (commonality). On the other hand, each information source may maintain individual differences as well (individuality). Simultaneously capturing commonality and individuality is very challenging due to their exclusive nature and existing work fail to do so. In this paper, we propose a deep generative embedding (DGE) framework which simultaneously captures commonality and individuality between network topology and node attributes in a generative process. Stochastic gradient variational Bayesian (SGVB) optimization is employed to infer model parameters as well as the node embeddings. Extensive experiments on four real-world datasets show the superiority of our proposed DGE framework in various tasks including node classification and link prediction.
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Barajas, Belcy Karine Angarita, Rodolfo Cantet, Kaitlin E. Wurtz, Carly O’Malley, Janice Siegford, Catherine Ernst, and Juan P. Steibel. "62 Improved estimation of indirect social genetic effects in group-housed pigs by quantifying behavioral interactions." Journal of Animal Science 97, Supplement_2 (July 2019): 34. http://dx.doi.org/10.1093/jas/skz122.063.
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Abstract Traditional social genetic effects modeling assumes uniform intensity of interaction between group members. Tree breeders proposed relaxing this assumption by incorporating estimates of intensity of competition between pairs of individuals. Here, we incorporated the quantification of aggressive interactions between pairs of animals in the estimation of indirect social genetic effects on skin lesions in the anterior part of the body in growing pigs. The data consisted of 491 pigs (215 barrows and 276 gilts, mean of 66 ±5 days of age). Animals were housed in 37 pens (11 to 15 pigs by pen) over 7 replicates. Trained scorers counted the number of skin lesions immediately before and 24 hours after mixing pigs. Animals were video-recorded for 9 hours post mixing and trained observers quantified the type and duration of aggressive interactions between pairs of pigs. The number of skin lesions in the frontal part of the body 24 hours post-mixing was the response variable and the number of seconds that pairs of animals spent engaged in reciprocal fights was used to quantify the intensity of interaction. We compared three different models: A direct genetic additive model (DGE), a traditional social genetic effect model (TSGE) assuming uniform interactions, and an improved social genetic effect model (ISGE) that used intensity of interaction to parameterize social genetic effects. All models included fixed effects of sex, replicate, lesion scorer, initial weight and pre-mixing lesion count; a random effect of pen; and a random direct genetic effect. The model ISGE recovered the most variance (smallest σe2) and resulted in the highest estimated h2 (P < 0.005). The model TSGE produced estimates that did not differ significantly from DGE (P = 1). Contrarily, incorporating the intensity of interaction into the modeling of ISGE allowed direct and indirect genetic effects to be estimated separately, even in a small dataset.
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Xiao, Kang-Wen, Zhi-Bo Liu, Zi-Hang Zeng, Fei-Fei Yan, Ling-Fei Xiao, Jia-Li Li, and Lin Cai. "Construction and Validation of a Macrophage-Associated Risk Model for Predicting the Prognosis of Osteosarcoma." Journal of Oncology 2021 (June 2, 2021): 1–18. http://dx.doi.org/10.1155/2021/9967954.
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Background. Osteosarcoma is one of the most common bone tumors among children. Tumor-associated macrophages have been found to interact with tumor cells, secreting a variety of cytokines about tumor growth, metastasis, and prognosis. This study aimed to identify macrophage-associated genes (MAGs) signatures to predict the prognosis of osteosarcoma. Methods. Totally 384 MAGs were collected from GSEA software C7: immunologic signature gene sets. Differential gene expression (DGE) analysis was performed between normal bone samples and osteosarcoma samples in GSE99671. Kaplan–Meier survival analysis was performed to identify prognostic MAGs in TARGET-OS. Decision curve analysis (DCA), nomogram, receiver operating characteristic (ROC), and survival curve analysis were further used to assess our risk model. All genes from TARGET-OS were used for gene set enrichment analysis (GSEA). Immune infiltration of osteosarcoma sample was calculated using CIBERSORT and ESTIMATE packages. The independent test data set GSE21257 from gene expression omnibus (GEO) was used to validate our risk model. Results. 5 MAGs (MAP3K5, PML, WDR1, BAMBI, and GNPDA2) were screened based on protein-protein interaction (PPI), DGE, and survival analysis. A novel macrophage-associated risk model was constructed to predict a risk score based on multivariate Cox regression analysis. The high-risk group showed a worse prognosis of osteosarcoma ( p < 0.001) while the low-risk group had higher immune and stromal scores. The risk score was identified as an independent prognostic factor for osteosarcoma. MAGs model for diagnosis of osteosarcoma had a better net clinical benefit based on DCA. The nomogram and ROC curve also effectively predicted the prognosis of osteosarcoma. Besides, the validation result was consistent with the result of TARGET-OS. Conclusions. A novel macrophage-associated risk score to differentiate low- and high-risk groups of osteosarcoma was constructed based on integrative bioinformatics analysis. Macrophages might affect the prognosis of osteosarcoma through macrophage differentiation pathways and bring novel sights for the progression and prognosis of osteosarcoma.
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Kong, Lingkai, and Yunxin Chang. "THE IMPULSE RESPONSES OF CAPITAL, CONSUMPTION, AND PRICES IN THE STOCHASTIC RAMSEY MODEL WITH AN INFINITE TIME HORIZON EMPLOYING VALUE FUNCTION ITERATION AND LINEAR INTERPOLATION." JOURNAL OF QUANTITATIVE FINANCE AND ECONOMICS 4, no. 2 (2022): 161–78. http://dx.doi.org/10.47509/jqfe.2022.v04i02.01.
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In this paper, we use value function iteration and linear interpolation to solve an example of a stochastic, infinite-horizon Ramsey model, which is one kind of dynamic general equilibrium (DGE) model. To obtain an approximation of the policy function’s solution, we pick a grid of capital investments for each period, set the starting value of the value function, build an iterative loop to compute the new value using interpolation, and establish the selection criteria and stop conditions. We model transient shocks to total factor productivity (TFP) and capture the impulsive reactions of consumption, capital, and factor pricing, with the algorithm anticipated to converge in “x” iterations. This concept is helpful and inspiring for assessing financial risk avoidance and dealing with and better comprehending potential shocks.
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Johri, Alok, and Md Mahbubur Rahman. "The Rise and Fall of India’s Relative Investment Price: A Tale of Policy Error and Reform." American Economic Journal: Macroeconomics 14, no. 1 (January 1, 2022): 146–78. http://dx.doi.org/10.1257/mac.20180411.
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India’s relative price of investment rose 44 percent from 1981 to 1991 and fell 26 percent from 1991 to 2006. We build a simple DGE model, calibrated to Indian data, in order to explore the impact of capital import substitution policies and their reform post-1991 in accounting for this rise and fall. Our model delivers a 23 percent rise before reform and a 31 percent fall thereafter. GDP per effective labor was 3 percent lower in 1991 compared to 1981 due to import restrictions on capital goods. Their removal, and a 71 percentage point reduction in tariff rates, raised GDP per effective labor permanently by 20 percent. (JEL E22, E23, F13, O11, O16, O19)
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Bortoluzzi, Mirian, Marcelo Furlan, Simone Geitenes Colombo, Tatiele Martins Amaral, Celso Correia de Souza, José Francisco dos Reis Neto, and Josimar Fernandes de França. "Combining Value-Focused Thinking and PROMETHEE Techniques for Selecting a Portfolio of Distributed Energy Generation Projects in the Brazilian Electricity Sector." Sustainability 13, no. 19 (October 7, 2021): 11091. http://dx.doi.org/10.3390/su131911091.
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This article aims to propose a multi-criteria model to support decision-making from a portfolio in selecting technologies for Distributed Generation of Energy (DGE) projects based on the characteristics of the geographic space in Brazil. The decision model involves using multi-criteria to support the evaluation, prioritization, and selection of projects under a multistage decision-making process that fits into a strategic management cycle within the energy sector of Mato Grosso do Sul (Brazil). The over-classification techniques Preference Ranking Organization Technique for Enrichment Evaluations (PROMETHEE) II and V were applied under the Value-Focused Thinking (VFT) approach, reflecting the decision-maker or manager preferences among several conflicting criteria in the investment context of sustainable distributed energy generation projects. Based on real data, a numerical application is employed to view the steps of this decision model and illustrate the adequacy and effectiveness in practical issues of portfolio management.
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Zhang, Zhao, Caoyuan Ma, and Aiping Wang. "Environmental Governance, Public Health Expenditure, and Economic Growth: Analysis in an OLG Model." International Journal of Environmental Research and Public Health 20, no. 4 (February 9, 2023): 3033. http://dx.doi.org/10.3390/ijerph20043033.
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This article studies the relationship between environmental governance, public health expenditure, and economic growth by introducing human health status into a three-period overlapping generation dynamic general equilibrium (OLG-DGE) model and conducting a policy simulation analysis in a Chinese scenario. The main findings are generalized as follows: (i) The increase in pollution emissions per unit of output will not only lead to the deterioration of public health but also hinder long-term economic growth, while the efficiency of pollution control will improve health and output per labor unit; (ii) Although levying environmental tax will improve health status and life expectancy, it has a non-linear impact on pollution emissions and output per labor unit, which means that there are trade-offs among environmental governance, public health improvement, and economic output; and (iii) Although the increase in the proportion of public health expenditure will improve health status, its impact on life expectancy and economic output is affected by the level of environmental tax. Only when the environmental tax rate is relatively low, will increasing the proportion of public health expenditure extend life expectancy and output per labor unit.
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Wang, Ye, and Xindong Zhao. "Grandparental Childcare and Second Birth in China: Evidence from a Dynamic Model and Empirical Study." Complexity 2021 (June 1, 2021): 1–15. http://dx.doi.org/10.1155/2021/6693853.
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The availability of nonparental childcare may be an important factor that influences reproductive decisions. While there is still a shortage of formal childcare service in China, grandparents are one primary source of childcare for their grandchildren. However, impact evaluations regarding the contribution of grandparenting on fertility level in China are still limited; the established evaluation results are not conclusive, especially for the birth of the second child. In this paper, we provide a theoretical justification and an empirical study of the influence of grandparental childcare on the second birth. By introducing a dynamic general equilibrium (DGE) model, this study proves that intergenerational childcare plays a critical role in both boosting the fertility level and maintaining its positive tendency. Drawing on the nationally representative data from the China Migrants Dynamic Survey in 2016, we estimate the treatment effects of grandparental childcare for the first child on the second birth with the Propensity Score Matching method. After controlling the self-selection bias, the results show that intergenerational childcare can positively affect the second birth. Sensitivity analysis results show the relative robustness of our empirical estimates to potential hidden bias attributed to unobserved variables. We also draw policy implications from the analysis, calling for government policies not only to promote sustainable and healthy development of the childcare industry but also to support family life, especially grandparental childcare.
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Renz, Bernhard W., Christine Adrion, Carsten Klinger, Matthias Ilmer, Jan G. D’Haese, Heinz-J. Buhr, Ulrich Mansmann, and Jens Werner. "Pylorus resection versus pylorus preservation in pancreatoduodenectomy (PyloResPres): study protocol and statistical analysis plan for a German multicentre, single-blind, surgical, registry-based randomised controlled trial." BMJ Open 11, no. 11 (November 2021): e056191. http://dx.doi.org/10.1136/bmjopen-2021-056191.
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IntroductionPartial pancreatoduodenectomy (PD) is the treatment of choice for various benign and malignant tumours of the pancreatic head or the periampullary region. For reconstruction of the gastrointestinal passage, two stomach-preserving PD variants exist: pylorus preservation PD (ppPD) or pylorus resection PD (prPD) with preservation of the stomach. In pancreatic surgery, delayed gastric emptying (DGE) remains a serious complication after PD with an incidence varying between 4.5% and 45%, potentially delaying hospital discharge or further treatment, for example, adjuvant chemotherapy. Evidence is lacking to assess, which variant of PD entails fewer postoperative DGE.Methods and analysisThe protocol of a large-scale, multicentre, pragmatic, two-arm parallel-group, registry-based randomised controlled trial (rRCT) using a two-stage group-sequential design is presented. This patient-blind rRCT aims to demonstrate the superiority of prPD over ppPD with respect to the overall incidence of DGE within 30 days after index surgery in a German real-world setting. A total of 984 adults undergoing elective PD for any indication will be randomised in a 1:1 ratio. Patients will be recruited at about 30 hospitals being members of the StuDoQ|Pancreas registry established by the German Society of General and Visceral Surgery. The postoperative follow-up for each patient will be 30 days. The primary analysis will follow an intention-to-treat approach and applies a binary logistic random intercepts model. Secondary perioperative outcomes include overall severe morbidity (Clavien-Dindo classification), blood loss, 30-day all-cause mortality, postoperative hospital stay and operation time. Complication rates and adverse events will be closely monitored.Ethics and disseminationThis protocol was approved by the leading ethics committee of the Medical Faculty of the Ludwig-Maximilians-Universität, Munich (reference number 19-221). The results will be published in a peer-reviewed journal and presented at international conferences. Study findings will also be disseminated via the website (http://www.dgav.de/studoq/pylorespres/).Trial registration numberDRKS-ID: DRKS00018842.
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Bell, Erica, Amy Webb, Joseph Stanek, Megan Blue, Parth Patel, Diana Thomas, Christopher Pierson, et al. "BIOM-49. A PILOT STUDY OF CEREBROSPINAL FLUID EXOSOMAL SMALL RNA-SEQUENCING IN PEDIATRIC MEDULLOBLASTOMA PATIENTS ON THE NEXT CONSORTIUM “HEAD START” 4 PROTOCOL." Neuro-Oncology 24, Supplement_7 (November 1, 2022): vii15—vii16. http://dx.doi.org/10.1093/neuonc/noac209.059.
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Abstract BACKGROUND Head Start 4 is a randomized clinical trial to determine whether dose-intensive tandem consolidation, compared with a single cycle, with autologous hematopoietic progenitor cell rescue provides a survival benefit in pediatric patients with medulloblastoma or other embryonal tumors. The trial incorporates upfront molecular subgrouping and non-mandatory, prospective blood and cerebrospinal fluid (CSF) collection. This pilot study aimed to identify exosomal non-coding RNAs (exo-ncRNAs) that might serve as novel diagnostic and/or treatment response biomarkers. METHODS CSF(1-2mLs) from 11 controls (non-tumor) and 27 medulloblastoma participants including 23 obtained at baseline, 22 at the end of induction, 3 post-consolidation, and 4 relapse time points, were profiled. Exosome isolation and small RNA-sequencing were performed by System Biosciences. Differential gene expression (DGE) was performed in R (DESeq2). Variations in gene expression profiles between samples were visualized using principal component analysis. RESULTS After limiting to ncRNAs with expression of 2 counts per million in 50% or more of the samples in each comparison, ~9,500 ncRNAs were detected. DGE analyses revealed 118 ncRNAs with log2 fold change(FC) >2 and 1 ncRNA with log2FC< -2 in baseline CSF samples compared to controls. In contrast, 11 ncRNAs(log2FC >2) and 1 ncRNA(log2FC< -2) were detected in end of induction CSF samples compared to controls. Comparing end of induction to baseline CSF samples accounting for paired samples, 0 ncRNAs(log2FC >2) and 52 ncRNAs(log2FC< -2) were detected. CONCLUSIONS Overall, our data indicate that exosomal small RNA-sequencing of limited CSF volumes is feasible. Differential expression and distinct clustering between tumor baseline samples compared to non-tumor controls was observed. CSF-derived exo-ncRNAs at end of induction also demonstrated “normalization” of ncRNA profiles, signifying CSF biomarkers may serve a role in diagnosis and molecular response assessment. A comprehensive analysis including multi-marker predictive model development and molecular subgrouping will be undertaken at completion of study enrollment.
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Tkáčiková, Soňa, Ivan Talian, Marián Petrovič, and Ján Sabo. "Using 2-D electrophoresis followed by nano HPLC in nuclear protein analysis of MCF-7 breast cancer cell line by MALDI-TOF/TOF." Open Chemistry 10, no. 2 (April 1, 2012): 407–12. http://dx.doi.org/10.2478/s11532-011-0156-x.
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AbstractThe biomarker identification is an important tool in early cancer detection. The MCF-7 breast cancer cell line was chosen as a model system. The nuclear proteins were extracted utilizing a commercially manufactured kit and separated on two dimensional (2-D) sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS PAGE). The first dimension was performed on isoelectric focusing strips with pH range 4–7. Afterwards the proteins were tryptic digested and identification was performed by matrix assisted laser desorption technique with time of flight mass analyzer (MALDI-TOF/TOF). For unambiguous identification proteins with too low concentration or spots contains protein mixture the nano high performance liquid chromatography (HPLC) was used. The 2-D gel electrophoresis (2-DGE) seems to be a good tool to separate large amount of proteins using relatively simple procedure and its hyphenation with HPLC can create the perfect analytical solution for proteome identification. About 150 nuclei protein spots were visualized and the most abundant of them were identified.
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Sun, Yi-Sheng, Zhang-Nv Yang, Fang Xu, Chen Chen, Hang-Jing Lu, Jian-Min Jiang, Yan-Jun Zhang, Han-Ping Zhu, and Ping-Ping Yao. "Global Gene Expression Analysis of the Brainstem in EV71- and CVA16-Infected Gerbils." Viruses 12, no. 1 (December 30, 2019): 46. http://dx.doi.org/10.3390/v12010046.
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Enterovirus 71 (EV71) and coxsackievirus A16 (CVA16) are the two most important pathogens of hand, foot, and mouth disease (HFMD). However, the neuropathogenesis of EV71 and CVA16 has not been elucidated. In our previous study, we established gerbils as a useful model for both EV71 and CVA16 infection. In this work, we used RNA-seq technology to analyze the global gene expression of the brainstem of EV71- and CVA16-infected gerbils. We found that 3434 genes were upregulated while 916 genes were downregulated in EV71-infected gerbils. In CVA16-infected gerbils, 1039 genes were upregulated, and 299 genes were downregulated. We also found significant dysregulation of cytokines, such as IP-10 and CXCL9, in the brainstem of gerbils. The expression levels of 10 of the most upregulated genes were confirmed by real-time RT-PCR, and the upregulated tendency of most genes was in accordance with the differential gene expression (DGE) results. Our work provided global gene expression analysis of virus-infected gerbils and laid a solid foundation for elucidating the neuropathogenesis mechanisms of EV71 and CVA16.
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Cao, Song, Yun Liu, Wenting Sun, Li Zhao, Lin Zhang, Xinkui Liu, and Tian Yu. "Genome-Wide Expression Profiling of Anoxia/Reoxygenation in Rat Cardiomyocytes Uncovers the Role of MitoKATPin Energy Homeostasis." Oxidative Medicine and Cellular Longevity 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/756576.
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Mitochondrial ATP-sensitive potassium channel (mitoKATP) is a common end effector of many protective stimuli in myocardial ischemia-reperfusion injury (MIRI). However, the specific molecular mechanism underlying its myocardial protective effect is not well elucidated. We characterized an anoxia/reoxygenation (A/R) model using freshly isolated adult rat cardiomyocytes. MitoKATPstatus was interfered with its specific opener diazoxide (DZ) or blocker 5-hydroxydecanote (5-HD). Digital gene expression (DGE) and bioinformatic analysis were deployed. Three energy metabolism related genes (MT-ND6, Idh2,andAcadl) were upregulated when mitoKATPopened. In addition, as many as 20 differentially expressed genes (DEGs) were significantly enriched in five energy homeostasis correlated pathways (PPAR, TCA cycle, fatty acid metabolism, and peroxisome). These findings indicated that mitoKATPopening in MIRI resulted in energy mobilization, which was confirmed by measuring ATP content in cardiomyocytes. These causal outcomes could be a molecular mechanism of myocardial protection of mitoKATPand suggested that the mitoKATPopening plays a physiologic role in triggering cardiomyocytes’ energy homeostasis during MIRI. Strategies of modulating energy expenditure during myocardial ischemia-reperfusion may be promising approaches to reduce MIRI.
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Agase, D. M., K. K. Gupta, A. Wasnik, M. S. Markam, S. B. Zade, P. M. Mohurle, and T. S. Kothe. "Differential gene expression and co-regulated expression of genes in leukemia: an in-silico approach to identify potent biomarker." Journal of Applied and Natural Science 13, no. 2 (June 2, 2021): 585–92. http://dx.doi.org/10.31018/jans.v13i2.2650.
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A biomarker can be measured, used to diagnose or classify disease, and measure progress as well as the therapeutic response of the disease. Early diagnosis and selection of appropriate treatment can be critical for the successful treatment of diseases. Identification and characterization of potent diagnostic biomarkers, and therapeutic targets rely heavily on traditional in vitro screens which require extensive resources and time. Integration of in silico screens prior to experimental validation can improve the efficiency and potency of biomarkers as well as reduce the cost and time of biomarker discovery. Considering the need, present work was undertaken to identify biomarkers for different classes of leukemia. Differential Gene Expression (DGE) analysis and co-regulated expression analysis were used for in silico identification and characterise a potent biomarker for leukemia. On the basis of in silico screening, the present study proposed seven protein-coding (CD38, TSC22D3, TNFRSF25, AGL, LARGE1, ARHGAP32, and PARM1) genes for the diagnosis of leukemia. The study also proposed a novel three-step lineage-specific model for the diagnosis of leukemia. In the three-step diagnosis model, the first group of biomarkers with an association of clinical and hematological parameters diagnose leukemia. The second group of biomarkers diagnoses acute and chronic form of leukemia. The third group of biomarkers identifies whether it belongs to myeloid lineage or lymphoid lineage.
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Yang, Huilin, Yuande Peng, Yixue Shi, Jianxiang Tian, Juan Wang, Xianjin Peng, Chunliang Xie, et al. "Transcriptome assembly and expression profiling of the molecular responses to cadmium toxicity in cerebral ganglia of wolf spider Pardosa pseudoannulata (Araneae: Lycosidae)." Ecotoxicology 27, no. 2 (January 3, 2018): 198–208. http://dx.doi.org/10.1007/s10646-017-1885-1.
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AbstractCadmium (Cd) is a heavy metal that can cause irreversible toxicity to animals, and is an environmental pollutant in farmlands. Spiders are considered to be an excellent model for investigating the impacts of heavy metals on the environment. To date, the changes at the molecular level in the cerebral ganglia of spiders are poorly understood. Cd exposure leads to strong damage in the nervous system, such as apoptosis and necrosis of nerve cells, therefore we conducted a transcriptomic analysis of Pardosa pseudoannulata cerebral ganglia under Cd stress to profile differential gene expression (DGE). We obtained a total of 123,328 assembled unigenes, and 1441 Cd stress-associated DEGs between the Cd-treated and control groups. Expression profile analysis demonstrated that many genes involved in calcium signaling, cGMP—PKG signaling, tyrosine metabolism, phototransduction–fly, melanogenesis and isoquinoline alkaloid biosynthesis were up-regulated under Cd stress, whereas oxidative phosphorylation-related, nervous disease-associated, non-alcoholic fatty liver disease-associated, and ribosomal-associated genes were down-regulated. Here, we provide a comprehensive set of DEGs influenced by Cd stress, and heavy metal stress, and provide new information for elucidating the neurotoxic mechanisms of Cd stress in spiders.
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Perivoliotis, Konstantinos, Eleni Sioka, Athina Tatsioni, Ioannis Stefanidis, Elias Zintzaras, and Dimitrios Zacharoulis. "Pancreatogastrostomy versus Pancreatojejunostomy: An Up-to-Date Meta-Analysis of RCTs." International Journal of Surgical Oncology 2017 (2017): 1–18. http://dx.doi.org/10.1155/2017/7526494.
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Background. A meta-analysis was conducted in order to provide an up-to-date comparison of pancreatogastrostomy (PG) and pancreatojejunostomy (PJ), after pancreatoduodenectomy (PD), in terms of clinically significant postoperative pancreatic fistula (POPF) and other postoperative complications. Methods. This meta-analysis was conducted according to the PRISMA guidelines and the Cochrane Handbook for Systematic Reviews of Interventions. A systematic literature search in MEDLINE and Cochrane Central Register of Controlled Clinical Trials was performed. Fixed Effects or Random Effects model was used, based on the Cochran Q test. Results. In total, 10 studies (1629 patients) were included. There was no statistical significance between PG and PJ regarding the rate of clinically significant POPF (OR: 0.70, 95%CI: 0.46–1.06). PG was associated with a higher rate of postpancreatoduodenectomy haemorrhage (PPH) (OR: 1.52, 95%CI: 1.08–2.14). There was no difference between the two techniques in terms of clinically significant PPH (OR: 1.35, 95%CI: 0.95–1.93) and clinically significant postoperative delayed gastric emptying (DGE) (OR: 0.98, 95%CI: 0.59–1.63). Discussion. There is no difference between the two anastomotic techniques regarding the rate of clinically significant POPF. Given several limitations, more large scale high quality RCTs are required.
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Rahi, Md Lifat, Shorash Amin, Peter B. Mather, and David A. Hurwood. "Candidate genes that have facilitated freshwater adaptation by palaemonid prawns in the genusMacrobrachium: identification and expression validation in a model species (M. koombooloomba)." PeerJ 5 (February 8, 2017): e2977. http://dx.doi.org/10.7717/peerj.2977.
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BackgroundThe endemic Australian freshwater prawn,Macrobrachium koombooloomba, provides a model for exploring genes involved with freshwater adaptation because it is one of the relatively fewMacrobrachiumspecies that can complete its entire life cycle in freshwater.MethodsThe present study was conducted to identify potential candidate genes that are likely to contribute to effective freshwater adaptation byM. koombooloombausing a transcriptomics approach.De novoassembly of 75 bp paired end 227,564,643 high quality Illumina raw reads from 6 different cDNA libraries revealed 125,917 contigs of variable lengths (200–18,050 bp) with an N50 value of 1597.ResultsIn total, 31,272 (24.83%) of the assembled contigs received significant blast hits, of which 27,686 and 22,560 contigs were mapped and functionally annotated, respectively. CEGMA (Core Eukaryotic Genes Mapping Approach) based transcriptome quality assessment revealed 96.37% completeness. We identified 43 different potential genes that are likely to be involved with freshwater adaptation inM. koombooloomba. Identified candidate genes included: 25 genes for osmoregulation, five for cell volume regulation, seven for stress tolerance, three for body fluid (haemolymph) maintenance, eight for epithelial permeability and water channel regulation, nine for egg size control and three for larval development. RSEM (RNA-Seq Expectation Maximization) based abundance estimation revealed that 6,253, 5,753 and 3,795 transcripts were expressed (at TPM value ≥10) in post larvae, juveniles and adults, respectively. Differential gene expression (DGE) analysis showed that 15 genes were expressed differentially in different individuals but these genes apparently were not involved with freshwater adaptation but rather were involved in growth, development and reproductive maturation.DiscussionThe genomic resources developed here will be useful for better understanding the molecular basis of freshwater adaptation inMacrobrachiumprawns and other crustaceans more broadly.
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Collins, J. E., P. K. Legan, T. P. Kenny, J. MacGarvie, J. L. Holton, and D. R. Garrod. "Cloning and sequence analysis of desmosomal glycoproteins 2 and 3 (desmocollins): cadherin-like desmosomal adhesion molecules with heterogeneous cytoplasmic domains." Journal of Cell Biology 113, no. 2 (April 15, 1991): 381–91. http://dx.doi.org/10.1083/jcb.113.2.381.
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Desmosomal glycoproteins 2 and 3 (dg2 and 3) or desmocollins have been implicated in desmosome adhesion. We have obtained a 5.0-kb-long clone for dg3 from a bovine nasal epidermal lambda gt11 cDNA library. Sequence analysis of this clone reveals an open reading frame of 2,517 bases encoding a polypeptide of 839 amino acids. The sequence consists of a signal peptide of 28 amino acids, a precursor sequence of 104 amino acids, and a mature protein of 707 amino acids. The latter has the characteristics of a transmembrane glycoprotein with an extracellular domain of 550 amino acids and a cytoplasmic domain of 122 amino acids. The sequence of a partial clone from the same library shows that dg2 has an alternative COOH terminus that is extended by 54 amino acids. Genomic DNA sequence data show that this arises by splicing out of a 46-bp exon that encodes the COOH-terminal 11 amino acids of dg3 and contains an in-frame stop codon. The extracellular domain of dg3 shows 39.4% protein sequence identity with bovine N-cadherin and 28.4% identity with the other major desmosomal glycoprotein, dg1, or desmoglein. The cytoplasmic domain of dg3 and the partial cytoplasmic domain of dg2 show 23 and 24% identity with bovine N-cadherin, respectively. The results support our previous model for the transmembrane organization of dg2 and 3 (Parrish, E.P., J.E. Marston, D.L. Mattey, H.R. Measures, R. Venning, and D.R. Garrod. 1990. J. Cell Sci. 96:239-248; Holton, J.L., T.P. Kenny, P.K. Legan, J.E. Collins, J.N. Keen, R. Sharma, and D.R. Garrod. 1990. J. Cell Sci. 97:239-246). They suggest that these glycoproteins are specialized for calcium-dependent adhesion in their extracellular domains and, cytoplasmically, for the molecular interactions involved in desmosome plaque formation. Moreover this represents the first example of alternative splicing within the cadherin family of cell adhesion molecules.
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Li, Nie, Tian, Zhao, and Zhang. "The Impact of Equilibrium Gas Pressure and Coal Particle Size on Gas Dynamic Diffusion in Coal." Processes 7, no. 9 (August 28, 2019): 571. http://dx.doi.org/10.3390/pr7090571.
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The diffusion coefficient of gases in coal varies with time. This study aims to develop an unsteady dynamic diffusion (UDD) model based on the decay of diffusion coefficient with time and the change of integral. This study conducted a series of gas desorption and diffusion experiments with three different combinations of particle sizes and gas pressures and compared the diffusion coefficients of the three models. The UDD model exhibited good fitting results, and both the UDD and bidisperse models fitted the experimental data better than the unipore model. In addition, the dynamic diffusion coefficient (DDe) decreased rapidly in the initial stage but gradually decreased to a stable level in the later stage. All the effective diffusion coefficients of the three models negatively correlated with the particle size. In the unipore model, the diffusion coefficient of coal samples with three particle sizes increased with gas pressure. In the bidisperse and UDD models, the diffusion coefficients (Dae, Die, and DDe) of 0.25–0.5 mm and 0.5–1.0 mm coal samples increased with gas pressure. However, DDe and Dae of 1.0–1.25 mm coal samples increased first and then decreased. Furthermore, Die decreased first and then increased, with no sign of significant pressure dependence. Finally, the correlation and significance between the constant and diffusion coefficient in the UDD model was investigated.
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Sojoodi, Mozhdeh, Stephen C. Barrett, Derek J. Erstad, Shadi Salloum, Shijia Zhu, Tongqi Qian, Selene Colon, et al. "Abstract 255: Peroxidasin deficiency recruits pro-healing macrophages into the liver and inhibits NAFLD progression to HCC." Cancer Research 82, no. 12_Supplement (June 15, 2022): 255. http://dx.doi.org/10.1158/1538-7445.am2022-255.
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Abstract Introduction: During liver fibrosis, tissue repair mechanisms replace necrotic tissue with highly stabilized extracellular matrix (ECM) proteins. ECM stabilization influences the speed of tissue recovery. Here, we used a mouse model of nonalcoholic fatty liver disease (NAFLD) to study the function of peroxidasin (PXDN), a peroxidase that uses H2O2 to cross-link collagen IV, during liver fibrosis progression to hepatocellular carcinoma (HCC). Method: Pxdn-/- and Pxdn+/+ mice were fed with a choline-deficient L-amino acid-defined high-fat diet (CDAHFD) for 16 weeks to create a NAFLD-HCC preclinical model. Liver histology, collagen content, flow cytometry, immunostaining of immune cells, RNA-seq, and liver function tests were analyzed. In vivo imaging of liver reactive oxygen species (ROS) was performed using a redox-active iron complex, Fe-PyC3A. Results: Using Fe-PyC3A as an MRI contrast agent, we detected a higher content of ROS in Pxdn-/- livers (healthy) that was not necessarily directly toxic but could activate hypoxia-related molecular pathways. Genome-wide expression analysis of liver tissue and differential gene expression (DGE) combined with Gene Ontology (GO) analysis identified significant upregulation of genes associated with hypoxia and TNFα signaling pathways already in Pxdn-/- sham livers (without injury). In addition, we observed an upregulation of genes involved in the innate immune response, leukocyte activation, and chemotaxis. After 16 weeks of CDAHFD, gross analysis of collected liver showed no HCC nodule formation in Pxdn-/- mice while 60% of the WT mice had HCC tumors. Collagen deposition showed less collagen accumulation in Pxdn-/- mice. Flow cytometry of macrophages showed Pxdn-/- mice had increased pro-healing M2 macrophages recruitment in early- and mid-stage NAFLD (4 weeks and 8 weeks on CDAHFD) compared to WT controls. In addition, we observed a significant decrease in the number of CD3+ T cells and CD8+ cytotoxic T cells in the late-stage of NAFLD in Pxdn KO mice. DGE analysis revealed that IL-12 is highly expressed in Pxdn-/- injured livers. Additionally, multiple other T cell-related molecules such as IL-10, IL-6, CCL2, IL-7, and CD4 were elevated in Pxdn-/- injured liver. Elevation of these cytokines is an indicator for higher recruitment of pro-healing and anti-HCC macrophage to the site of injury. Conclusion: Our findings demonstrate that PXDN deficiency is associated with the induction of the hypoxia and TNFα signaling pathways and the recruitment of pro-healing and anti-HCC macrophages to the liver. This results in significantly decreased collagen stabilization during liver fibrosis and accelerates fibrosis reversal. In addition, recruited macrophages-controlled T cell response and inhibited HCC formation in Pxdn-/- mice. Citation Format: Mozhdeh Sojoodi, Stephen C. Barrett, Derek J. Erstad, Shadi Salloum, Shijia Zhu, Tongqi Qian, Selene Colon, Eric Gale, Veronica Clavijo Jordan, Yongtao Wang, Shen Li, Michael Lanuti, Lawrence Zukerberg, Peter Caravan, Yujin Hoshida, Raymond T. Chung, Gautam Bhave, Georg M. Lauer, Bryan C. Fuchs, Kenneth K. Tanabe. Peroxidasin deficiency recruits pro-healing macrophages into the liver and inhibits NAFLD progression to HCC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 255.
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Chan, Mandy M., Sabine Daemen, Li He, Anastasiia Gainullina, Maxim N. Artyomov, Babak Razani, and Joel D. Schilling. "Enhancing lysosomal lipid metabolism prevents the loss of Kupffer cells in non-alcoholic steatohepatitis and attenuates liver pathology." Journal of Immunology 208, no. 1_Supplement (May 1, 2022): 165.03. http://dx.doi.org/10.4049/jimmunol.208.supp.165.03.
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Abstract During the development of non-alcoholic steatohepatitis (NASH), liver resident Kupffer cells (KCs) are progressively lost and replaced by monocyte-derived macrophages (MdMs). The impact of KC loss on NASH pathology is not currently known. Given the important role of KCs in maintaining tissue homeostasis and clearing blood-borne antigens, we hypothesized that KC depletion contributes to NASH pathogenesis. Thus, we aimed to elucidate the mechanism(s) of KC loss and to devise a strategy to enhance KC survival during NASH. We had previously shown that lipids can cause lysosomal cell death in macrophages. Using a mouse model of NASH, we discovered that KCs also develop phagolysosomal pathology. Transcription factor EB (TFEB) is a master regulator of lysosomal biogenesis and lipid metabolism that has been shown to rescue lysosomal dysfunction in other metabolic diseases. To test whether TFEB activation could protect against KC death in NASH, we generated a mouse model in which a KC-specific Cre induces expression of a TFEB overexpression construct (KCTFEB). Despite having similar body and liver weight as WT mice fed a NASH-inducing diet, KCTFEB mice had a striking preservation of KC number. Moreover, KCTFEB mice had reduced recruitment of pro-inflammatory MdMs and this was associated with lower liver triglyceride and injury. RNA sequencing of KCs from transgenic and WT mice revealed that TFEB induced the expression of several lysosomal and lipid metabolic genes. Together these findings provide important proof-of-concept evidence that KC loss contributes to disease pathology in NASH and suggest that targeting macrophage lysosomal/lipid metabolic function could be a useful strategy to enhance resident macrophage survival. Supported by grants from ADA-118IBS280, DDRCC-P30DK052574, NIH T32-AI007163, and NSF GRFP-DGE-1745038
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Chen, Guanlan, Rui Zeng, Xin Wang, Hongying Cai, Jiajia Chen, Yingxiong Zhong, Saiyi Zhong, and Xuejing Jia. "Antithrombotic Activity of Heparinoid G2 and Its Derivatives from the Clam Coelomactra antiquata." Marine Drugs 20, no. 1 (January 5, 2022): 50. http://dx.doi.org/10.3390/md20010050.
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Clam heparinoid G2 (60.25 kDa) and its depolymerized derivatives DG1 (24.48 kDa) and DG2 (6.75 kDa) prepared from Coelomactra antiquata have been documented to have excellent fibrinolytic and anticoagulant activity. In this study, to further explore the antithrombotic activity of G2, DG1 and DG2, azure A, sheep plasma, and clot lytic rate assays were used to determine their anticoagulant and thrombolytic activity in vitro. The results indicated that the anticoagulant titer of G2 was approximately 70% that of heparin and the thrombolytic activity of DG2 was greater than G2, DG1, and heparin activities. Moreover, in a carrageenan-induced venous thrombosis model, oral administration of G2 and DG1 each at 20 mg/kg and 40 mg/kg for 7 days significantly reduced blacktail thrombus formation, increased tissue-type plasminogen activator, fibrin degradation products, and D-dimer levels, decreased von Willebrand factor and thromboxane B2 levels, and restored phylum and genus abundance changes of intestinal bacteria. DG2 had no antithrombotic effect. At 20 mg/kg, G2, DG1, and heparin had comparable antithrombotic activities, and DG1 at 40 mg/kg had more muscular antithrombotic activity than G2. Thus, DG1 could be an antithrombotic oral agent owing to its more robust antithrombotic activity and lower molecular weight.
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Dawson, Rebekah I., Ruth A. Murray-Clay, and John Asher Johnson. "Constraining Planetary Migration Mechanisms in Systems of Giant Planets." Proceedings of the International Astronomical Union 8, S299 (June 2013): 386–90. http://dx.doi.org/10.1017/s1743921313009046.
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AbstractIt was once widely believed that planets formed peacefully in situ in their proto-planetary disks and subsequently remain in place. Instead, growing evidence suggests that many giant planets undergo dynamical rearrangement that results in planets migrating inward in the disk, far from their birthplaces. However, it remains debated whether this migration is caused by smooth planet-disk interactions or violent multi-body interactions. Both classes of model can produce Jupiter-mass planets orbiting within 0.1 AU of their host stars, also known as hot Jupiters. In the latter class of model, another planet or star in the system perturbs the Jupiter onto a highly eccentric orbit, which tidal dissipation subsequently shrinks and circularizes during close passages to the star. We assess the prevalence of smooth vs. violent migration through two studies. First, motivated by the predictions of Socrates et al. (2012), we search for super-eccentric hot Jupiter progenitors by using the “photoeccentric effect” to measure the eccentricities of Kepler giant planet candidates from their transit light curves. We find a significant lack of super- eccentric proto-hot Jupiters compared to the number expected, allowing us to place an upper limit on the fraction of hot Jupiters created by stellar binaries. Second, if both planet-disk and multi-body interactions commonly cause giant planet migration, physical properties of the proto-planetary environment may determine which is triggered. We identify three trends in which giant planets orbiting metal rich stars show signatures of planet-planet interactions: (1) gas giants orbiting within 1 AU of metal-rich stars have a range of eccentricities, whereas those orbiting metal- poor stars are restricted to lower eccentricities; (2) metal-rich stars host most eccentric proto-hot Jupiters undergoing tidal circularization; and (3) the pile-up of short-period giant planets, missing in the Kepler sample, is a feature of metal-rich stars and is largely recovered for giants orbiting metal-rich Kepler host stars. These two studies suggest that both disk migration and planet-planet interactions may be widespread, with the latter occurring primarily in metal-rich planetary systems where multiple giant planets can form. Funded by NSF-GRFP DGE-1144152.
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Veneziani, Federica, Antonio Rampino, Aleksandra Marakhovskaia, Clementine Quintana, Giuseppe Blasi, Marco Zezza, Alessandro Bertolino, and Jean Martin Beaulieu. "M207. REVEALING HYPOTHALAMIC PATHWAYS CONTRIBUTION TO OLANZAPINE- INDUCED METABOLIC SYNDROME: FROM MURINE MODEL TO HUMAN TRANSLATION." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S215. http://dx.doi.org/10.1093/schbul/sbaa030.519.
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Abstract Background Olanzapine (OL) represents one of the main choices for the treatment of psychotic symptoms. However, OL increase the risk of metabolic syndrome (MS). The mechanism of Olanzapine induced MS remains still unclear but hypothalamic pathways seem to be involved. The purpose of our study is to validate an innovative approach for translational studies to investigate the hypothalamic pathways contribution to OL induced MS. Methods To establish a murine model of Olanzapine induced MS, OL compounded in chow (54mg/Kg of HFD food) has been administered for 30 days to C57BL/6J female mice of 10 weeks old (20 mice/group). Food intake and weight gain are tested. After the 4 weeks of treatment, mice are sacrificed by rapid cervical dislocation. Blood is collected for Glucose, Insulin and Leptin evaluation. Hypothalamus and Liver are rapidly dissected and analyzed with qPCR. Fatty liver is histologically tested with Red Oil-O- staining. The identification of mice hypothalamic coexpression network with a Genome-wide Weighted Genes Co-expression Network Analysis (WGCNA) is performed using a publicly available mice hypothalamic RNASeq a dataset. From the RNASeq data obtained from Perez-Gomez et al. study (PMID: 30532051) a differential gene expression (DGE) analysis is performed to identify the gene impacted by Olanzapine and verified with qPCR on our sample. The segregation of differentially expressed genes in specific modules of the mice hypothalamic network is tested. Human hypothalamic network identification is performed using the publicly available GTEx dataset of Hypothalamic RNASeq data for a WGCNA. The segregation of differentially expressed genes of mice model in human network has been studied. An eigengene network approach is used to study the relationship between the human affected modules. Results From the 2nd week of treatment, the weight gain shows a significant increase (p= 0.02) in OL group compared to Control. The difference in weight gain remains unchanged until the 30th day. Likewise Blood glucose, Insuline and Leptine levels appear increased in Olanzapine group compared to control (p= 0,0089, p= 0,01, p= 0,0012 respectively). The percentage of liver parenchyma occupied by lipid droplets shows a statistically significant increase in OL treated group (p=0,0001). 14 of the 29 identified hypothalamic differentially expressed genes between OL- treated mice compared to control clusters in a single module of the WGCNA. The pathway analysis of this module reveals that Wnt signaling pathway reaches the statistical significance (FDR= 0,02 p value = 0,00006). The co-occurrence of OL-induced hypothalamic differentially expressed genes, previously identified in mice, is analyzed on human WGCNA on hypothalamic RNASeq data. The impacted module in humans seems to be three with no identifiable pathways involved. From the eigengene analysis results that two of the three impacted modules cluster in a single hierarchical module. The pathway analysis performed on the whole eigengine module reveals that Wnt signaling pathway reaches the statistical significance (FDR= 0,01 p value = 0,00003). Discussion Our study firstly demonstrates the full MS-phenotype induced by Olanzapine avoiding the use of weight gain as a proxy of OL-MS as shown in previous literature. The high comparability shows by hypothalamic network analysis in mice and humans underlines the highly interspecies conservation of hypothalamic functional pathways. So the present study represents an innovative approach for translational studies on hypothalamic pathway contribution to MS induced by OL. Combining a murine model, network analysis and human translation it proposes a reliable method for translation of pre-clinical studies.
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Bovee, Katherine, and Giorgio Rizzoni. "Model-Based Torque Shaping for Smooth Acceleration Response in Hybrid Electric Vehicles * *Financial support provided by the National Science Foundation Graduate Research Fellowship Program under grant no. DGE-1343012 and the Department of Energy Graduate Automotive Technology Education (GATE) Fellowship Program." IFAC-PapersOnLine 49, no. 11 (2016): 525–32. http://dx.doi.org/10.1016/j.ifacol.2016.08.077.
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Elânio Bezerra, Francisco, Fernando André Zemuner Garcia, Silvio Ikuyo Nabeta, Gilberto Francisco Martha de Souza, Ivan Eduardo Chabu, Josemir Coelho Santos, Shigueru Nagao Junior, and Fabio Henrique Pereira. "Wavelet-Like Transform to Optimize the Order of an Autoregressive Neural Network Model to Predict the Dissolved Gas Concentration in Power Transformer Oil from Sensor Data." Sensors 20, no. 9 (May 11, 2020): 2730. http://dx.doi.org/10.3390/s20092730.
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Dissolved gas analysis (DGA) is one of the most important methods to analyze fault in power transformers. In general, DGA is applied in monitoring systems based upon an autoregressive model; the current value of a time series is regressed on past values of the same series, as well as present and past values of some exogenous variables. The main difficulty is to decide the order of the autoregressive model; this means determining the number of past values to be used. This study proposes a wavelet-like transform to optimize the order of the variables in a nonlinear autoregressive neural network to predict the in oil dissolved gas concentration (DGC) from sensor data. Daubechies wavelets of different lengths are used to create representations with different time delays of ten DGC, which are then subjected to a procedure based on principal components analysis (PCA) and Pearson’s correlation to find out the order of an autoregressive model. The representations with optimal time delays for each DGC are applied as input in a multi-layer perceptron (MLP) network with backpropagation algorithm to predict the gas at the present and future times. This approach produces better results than choosing the same time delay for all inputs, as usual. The forecasts reached an average mean absolute percentage error (MAPE) of 5.763%, 1.525%, 1.831%, 2.869%, and 5.069% for C2H2, C2H6, C2H4, CH4, and H2, respectively.
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Berman, Daniel S. "DGA CapsNet: 1D Application of Capsule Networks to DGA Detection." Information 10, no. 5 (April 27, 2019): 157. http://dx.doi.org/10.3390/info10050157.
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Domain generation algorithms (DGAs) represent a class of malware used to generate large numbers of new domain names to achieve command-and-control (C2) communication between the malware program and its C2 server to avoid detection by cybersecurity measures. Deep learning has proven successful in serving as a mechanism to implement real-time DGA detection, specifically through the use of recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This paper compares several state-of-the-art deep-learning implementations of DGA detection found in the literature with two novel models: a deeper CNN model and a one-dimensional (1D) Capsule Networks (CapsNet) model. The comparison shows that the 1D CapsNet model performs as well as the best-performing model from the literature.
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Jamil, Khansa, Sahir Hameed Khattak, Anum Farrukh, Sania Begum, Muhammad Naeem Riaz, Aish Muhammad, Tahira Kamal, et al. "Biogenic Synthesis of Silver Nanoparticles Using Catharanthus roseus and Its Cytotoxicity Effect on Vero Cell Lines." Molecules 27, no. 19 (September 21, 2022): 6191. http://dx.doi.org/10.3390/molecules27196191.
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Background: Type 2 diabetes mellitus (DM2) is a chronic and sometimes fatal condition which affects people all over the world. Nanotherapeutics have shown tremendous potential to combat chronic diseases—including DM2—as they enhance the overall impact of drugs on biological systems. Greenly synthesized silver nanoparticles (AgNPs) from Catharanthus roseus methanolic extract (C. AgNPs) were examined primarily for their cytotoxic and antidiabetic effects. Methods: Characterization of C. AgNPs was performed by UV–vis spectroscopy, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and atomic force microscopy (AFM). The C. AgNPs were trialed on Vero cell line and afterwards on an animal model (rats). Results: The C. AgNPs showed standard structural and functional characterization as revealed by FTIR and XRD analyses. The zetapotential analysis indicated stability while EDX analysis confirmed the formation of composite capping with Ag metal. The cytotoxic effect (IC50) of C. AgNPs on Vero cell lines was found to be 568 g/mL. The animal model analyses further revealed a significant difference in water intake, food intake, body weight, urine volume, and urine sugar of tested rats after treatment with aqueous extract of C. AgNPs. Moreover, five groups of rats including control and diabetic groups (NC1, PC2, DG1, DG2, and DG3) were investigated for their blood glucose and glycemic control analysis. Conclusions: The C. AgNPs exhibited positive potential on the Vero cell line as well as on experimental rats. The lipid profile in all the diabetic groups (DG1-3) were significantly increased compared with both of the control groups (p < 0.05). The present study revealed the significance of C. AgNPs in nanotherapeutics.
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Beliveau, Yvan J., Daniel A. Snyder, and Michael C. Vorster. "DBE Programs—New Model." Journal of Construction Engineering and Management 117, no. 1 (March 1991): 176–92. http://dx.doi.org/10.1061/(asce)0733-9364(1991)117:1(176).
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Santos, Maria Susana Newton De Almeida, Didier Mugniéry, Maria José Moreno Da Cunha, Isabel Maria De Oliveira Abrantes, and Michel Bossis. "Protein variability among Portuguese and other populations of Globodera rostochiensis revealed by two-dimensional gel electrophoresis with computed image analysis." Nematology 2, no. 4 (2000): 461–71. http://dx.doi.org/10.1163/156854100509222.
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AbstractSilver-stained two dimensional gel electrophoresis (2-DGE) was used to characterize 46 populations of G. rostochiensis and, as an outgroup, one population of G. pallida. Protein patterns of white females were compared with the aid of computer assisted image analysis using Kepler software. A synthetic master pattern of G. rostochiensis, built with spots present in all populations and detected in at least two of three gels of each population, revealed the presence of 379 protein spots. The populations were compared taking into account the main spots present in each isolate (spots present in two of three gels, amplitude greater than 7, volume greater than 500 and with values fitting the Gaussian model). Comparison allowed the identification of 200 polymorphic spots. Similarity indices (F) and genetic distances (D = 1 F) between populations were calculated on the basis of homologous polymorphic spots, and a dendrogram was constructed according to the UPGMA method. Bootstrap analysis was used to assess the significance of the results from the phenetic study. The presence or absence of specific spots in some G. rostochiensis populations is discussed. Further biochemical and biological studies are necessary to determine if specific proteins are linked to virulence. Variabilité protéique de populations portugaises et d'origines diverses de Globodera rostochiensis détectée par électrophorèse bidimensionnelle et analysée par informatique - L'électrophorèse bidimensionnelle (E2D) est utilisée pour caractériser 46 populations européennes de G. rostochiensis et une population de G. pallida, prise comme groupe extérieur. Les protéinogrammes obtenus à partir de femelles blanches sont comparés par analyse informatisée d'images à l'aide du logiciel Kepler. Une image de référence est constituée au vu des taches protéiques détectées dans l'ensemble des populations étudiées par transfert vers cette image synthétique de chaque protéine détectée au moins deux fois sur trois dans une population. Celle-ci permet de répertorier et de localiser 379 protéines. Les populations ont été comparées avec les taches pröteiques les plus importantes (taches présentes dans au moins deux gels sur trois, amplitude plus grande que 7, volume plus grand que 500 et valeurs dans le model Gaussien). La comparaison des populations a permis de détecter 200 protéines. Les indices de similarité (F) et les distances génétiques (D = 1 F) ont été étudiés à partir des taches polymorphes homologues présentes dans chaque population. Le dendrogramme a été construit selon la méthode UPGMA. Une analyse des valeurs de bootstraps a été utilisée pour estimer la signification des résultats phénétiques. La présence ou l'absence de protéines spécifiques de certaines populations de G. rostochiensis est discutée. D'autres études biochimiques et biologiques sont en cours pour déterminer si les protéines spécifiques sont ou non liées à la virulence.
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da Costa Cantos Jerônimo, Gabriel, Luiz Felipe Ramos Turci, Paulo Augusto Zaitune Pamplin, and Patrícia Neves Mendes. "Modelagem otimizada de indicadores biológicos de qualidade da água." Revista DAE 221, no. 68 (December 10, 2019): 131–41. http://dx.doi.org/10.36659/dae.2020.011.
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Resumo 27/06/2018 DOI: https://doi.org/10.36659 /dae.2020.011 Turci, L. F. R Pamplin, P. A. Z https://orcid.org/0000-0001-7516-0963 https://orcid.org/0000-0001-7318-9121 O estudo de plantas aquáticas (macrófitas) é importante, uma vez que essas plantas apresentam potencial de utilização em estudos de ecotoxicologia, como bioindicadores no tratamento de águas residuárias. A mode- lagem criteriosa do crescimento dessas plantas, especificamente a Lemna minor, é útil na determinação das condições de otimização dessas aplicações; assim, deseja-se sempre obter o modelo que melhor represente a dinâmica de crescimento populacional da planta em estudo. Neste trabalho, apresenta-se uma metodologia de ajuste e seleção de modelos de crescimento não lineares com base em indicadores estatísticos que servem como avaliadores de qualidade dos modelos. Para ilustrar o uso da metodologia, foi feito o cultivo de Lemna minor em meio Steinberg e foram ajustados três modelos aos dados médios de crescimento de suas frondes, selecionando o modelo Logístico como o melhor. Palavras-chave: Modelo de crescimento populacional. Avaliadores de qualidade. Lemna minor. Abstract The study of aquatic plants (macrophytes) is important since such plants present a potential utilization in ecotoxi- cology as bioindicators, as well in wastewater treatment. The criterious growth modelling of such plants, specifically Lemna minor, is useful for the determination of the optimal conditions of mentionedin applications - so one always looks for the best model that represents the dynamic of population growth of the plant in study. This work presents a methodology of adjustment and selection of nonlinear growth models based on statistical indicators, which work as quality evaluators for the models. To illustrate this methodology, Lemna minor was grown in Steinberg environ- ment, and three models were fitted to the fronds growth data, the Logistic model was selected as the best model. Keywords: Population growth model. Quality evaluators. Lemna minor.
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Johri, Alok, and Marc-André Letendre. "What do ‘residuals’ from first-order conditions reveal about DGE models?" Journal of Economic Dynamics and Control 31, no. 8 (August 2007): 2744–73. http://dx.doi.org/10.1016/j.jedc.2006.09.008.
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El Alami laaroussi, Adil, Mohamed El Hia, Mostafa Rachik, and Rachid Ghazzali. "Analysis of a Multiple Delays Model for Treatment of Cancer with Oncolytic Virotherapy." Computational and Mathematical Methods in Medicine 2019 (September 30, 2019): 1–12. http://dx.doi.org/10.1155/2019/1732815.
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Despite advanced discoveries in cancerology, conventional treatments by surgery, chemotherapy, or radiotherapy remain ineffective in some situations. Oncolytic virotherapy, i.e., the involvement of replicative viruses targeting specific tumor cells, opens new perspectives for better management of this disease. Certain viruses naturally have a preferential tropism for the tumor cells; others are genetically modifiable to present such properties, as the lytic cycle virus, which is a process that represents a vital role in oncolytic virotherapy. In the present paper, we present a mathematical model for the dynamics of oncolytic virotherapy that incorporates multiple time delays representing the multiple time periods of a lytic cycle. We compute the basic reproductive ratio R0, and we show that there exist a disease-free equilibrium point (DFE) and an endemic equilibrium point (DEE). By formulating suitable Lyapunov function, we prove that the disease-free equilibrium (DFE) is globally asymptotically stable if R0<1 and unstable otherwise. We also demonstrate that under additional conditions, the endemic equilibrium is stable. Also, a Hopf bifurcation analysis of our dynamic system is used to understand how solutions and their stability change as system parameters change in the case of a positive delay. To illustrate the effectiveness of our theoretical results, we give numerical simulations for several scenarios.
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Kwon, Joseph Sangil, Michael Nayhouse, and Dong Ni Panagiotis D. Christofides. "Handling Parametric Drift in Batch Crystallization Using Predictive Control with R2R Model Parameter Estimation∗∗Financial support from the Extreme Science and Engineering Discovery Environment (TG-CCR120003), the National Science Foundation (CBET-0967291), and the NSF Graduate Research Fellowship (DGE-1144087) given to Michael Nayhouse is gratefully acknowledged." IFAC-PapersOnLine 48, no. 8 (2015): 912–17. http://dx.doi.org/10.1016/j.ifacol.2015.09.086.
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Hutla, P., B. Petráčková, and J. Kára. "Experimental model of ammonia elimination by ozone in the air." Research in Agricultural Engineering 59, No. 2 (May 31, 2013): 39–45. http://dx.doi.org/10.17221/54/2012-rae.
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Experimental device was created to model stable atmosphere. The device consists of the glass vessel filled with air. Volume of the vessel is 30 litres. The ammonia concentration is similar to stable air. Amount of ozone in 2.4 mg was added and subsequently weight loss of ammonia was measured. Measurements were performed at different temperatures (20°C, 45°C) and different air humidity. The observed ratio of reacting ozone and ammonia is 5.2:1. It was also found, that this ratio is practically independent of temperature and relative humidity that occur in a stable environment. The results are the basis for the design of ozone air purification technology.
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Waudby-Smith, Ian, A. Simon Pickard, Feng Xie, and Eleanor M. Pullenayegum. "Using Both Time Tradeoff and Discrete Choice Experiments in Valuing the EQ-5D: Impact of Model Misspecification on Value Sets." Medical Decision Making 40, no. 4 (May 2020): 483–97. http://dx.doi.org/10.1177/0272989x20924019.
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Introduction. The EQ-5D-5L valuation protocol contains both time tradeoff (TTO) tasks and discrete choice experiments (DCE), raising the question of how to best use these in creating a value set. The hybrid model, which combines TTO and DCE data, has emerged as a commonly used approach. However, this model assumes independence among responses from the same individual, a linear relationship between TTO and DCE utilities, and, in many implementations, homoscedastic residuals. The aims of this study are to examine alternatives to these assumptions and determine the impact of misspecification on value sets. Methods. We performed a simulation study, parameterized using the US EQ-5D-5L valuation study, to assess the impact of model misspecification. We simulated TTO and DCE data with nonlinear relationships between TTO and DCE utilities, heteroscedastic errors, and correlated responses. Simulated data were analyzed using hybrid models with and without heteroscedasticity, Tobit models with and without heteroscedasticity, a latent class model, and a mixed model. Results. Mean absolute errors (MAEs) for correctly specified models were <0.05, whereas models that incorrectly assumed a linear relationship between TTO and DCE utilities or homoscedasticity of TTO responses featured states with an MAE >0.1. When a linear relationship between TTO and DCE utilities held, using both TTO and DCE data under correct specification yielded smaller MAEs compared with using TTO data alone but yielded larger MAEs when a linear relationship did not hold. Mistakenly assuming homoscedasticity led to increased MAEs, whereas ignoring dependence did not. Conclusions. Because heteroscedasticity in TTO utilities and nonlinear associations between DCE and TTO utilities have been noted, we recommend careful assessment of scedasticity and linearity to ascertain the suitability of a hybrid model.
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Maan, Normah, Izaz Ullah Khan, and Nor Atirah Izzah Zulkefli. "The Notion of Stability of a Differential Equation and Delay Differential Equation Model of HIV Infection of CD4+ T-Cells." International Journal of Mathematics and Computers in Simulation 15 (March 29, 2021): 20–23. http://dx.doi.org/10.46300/9102.2021.15.4.
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This research presents a deep insight to address the notion of stability of an epidemical model of the HIV infection of CD4+ T-Cells. Initially, the stability of an ordinary differential equation (ODE) model is studied. This is followed by studying a delay differential equation (DDE) model the HIV infection of CD4+ T-Cells. The available literature on the stability analysis of the ODE model and the DDE model of the CD4+ T-Cells shows that the stability of the models depends on the basic reproduction number “R0”. Accordingly, for the basic reproduction number R0 <1, the model is asymptotically stable, whereas, for R0 >1, the models are globally stable. This research further studies the stability of the models and address the lower possible stability limits for the infection rate of CD4+ T-Cells with virus and the reproduction rate of infectious CD4+ T-Cells, respectively. Accordingly, the results shows that the lower possible limits for the infection rate of CD4+ T-Cells with virus are 0.0000027 mm-3 and 0.000066 mm-3 for the ODE and DDE models, respectively. Again, the lower stability limits for the reproduction rate of infectious CD4+ T-Cells with virus are 12 mm3day-1 and 273.4 mm3day-1 for the ODE and DDE models, respectively. The research minutely studies the stability of the models and gives a deep insight of the stability of the ODE and DDE models of the HIV infection of CD4+ T-Cells with virus.
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Ito, Akinori, Ying Ye, Akitomo Yamamoto, Michio Watanabe, and Maki N. Aita. "Responses of ocean biogeochemistry to atmospheric supply of lithogenic and pyrogenic iron-containing aerosols." Geological Magazine 157, no. 5 (November 15, 2019): 741–56. http://dx.doi.org/10.1017/s0016756819001080.
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AbstractAtmospheric supply of iron (Fe) to the ocean has been suggested to regulate marine productivity in large parts of the world’s ocean. However, there are still large uncertainties regarding how the atmospheric inputs of dissolved Fe (DFe) influence the seawater DFe concentrations and thus net primary production (NPP). Here, we use an atmospheric chemistry model and two ocean biogeochemistry models with high (Model H) and low (Model L) sensitivities to atmospheric sources of DFe to explore the responses of ocean biogeochemistry to different types of atmospheric inputs of DFe: mineral dust and combustion aerosols. When both Fe content in mineral dust of 3.5% and Fe solubility of 2% are prescribed in sensitivity simulations, the ocean models overestimate DFe concentration in the surface ocean downwind from the North African and East Asian dust plumes. Considering different degrees of atmospheric Fe processing reduces the overestimates of DFe concentration in the North Atlantic and North Pacific. The two ocean biogeochemistry models show substantially different magnitudes of responses to the atmospheric input of DFe. The more detailed Model H shows a much higher sensitivity of NPP to the change in combustion aerosols than to mineral dust, regardless of relative inputs of the sedimentary sources. This finding suggests that pyrogenic Fe-containing aerosols are more important sources of atmospheric bioavailable Fe for marine productivity than would be expected from the small amount of DFe deposition, especially in the Pacific and Southern oceans.
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Alves Henriques, Juscelino, Marcelo Libânio, Veber Afonso Figueiredo Costa, and Mariângela Dutra de Oliveira. "Modelo de predição de desempenho de estações de tratamento de água de pequeno porte usando redes neurais artificiais." Revista DAE 221, no. 68 (December 10, 2019): 87–100. http://dx.doi.org/10.36659/dae.2020.008.
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As estações de tratamento de água (ETAs) têm um papel fundamental e estratégico no controle de doenças transmitidas pela água por meio da potabilização da água, para atender às necessidades da população que é abastecida por ela. Nesse contexto, a avaliação do desempenho dessas estações é primordial, particularmente para as entidades responsáveis pelo estágio de controle da qualidade da água, uma vez que a ETA deve apre- sentar e operar com condições mínimas necessárias para alcançar seu objetivo. Para o desenvolvimento dos modelos (Modelo 1 - com base na turbidez da água tratada e Modelo 2 - com base na cor aparente da água tratada) foram utilizados dados referentes à qualidade da água bruta e tratada, fatores operacionais e parâme- tros hidráulicos de 3 ETAs, com taxas de fluxo de 50 L.s-1 ou menos. Os modelos foram desenvolvidos usando a caixa de ferramentas do Matlab®, a partir da rede neural do tipo de camadas recorrentes, com função de ativação tansig e purelin. Como resultados, os modelos apresentaram coeficientes de determinação de 0,928 e 0,823 para turbidez e cor aparente da água tratada, respectivamente. Os resultados corroboram a aplicação da Inteligência Artificial em estações de tratamento de água, com o objetivo de otimizar processos e garantir uma maior operabilidade da ETAs, gerando um produto cada vez mais confiável. Palavras-chave: Desempenho da planta de tratamento de água. Processos de otimização. Rede neural artificial. Abstract The water treatment plants (WTP) have a fundamental and strategic role in the control of waterborne diseases through the potabilization of water, to meet the needs of the population that is supplied by it. In this context, evaluating the performance of these stations is paramount, particularly for the entities responsible for the water quality control stage, since WTP must present and operate with minimum conditions necessary to achieve its ob- jective. For the development of the models (Model 1 - based on turbidity of treated water and Model 2 - based on the apparent color of the treated water) data were used referring to raw and treated water quality, operational factors and hydraulic parameters of 3 WTPs, with flow rates of 50 L.s-1 or less. The models were developed usingthe Matlab® toolbox, from the neural network of the recurrent layers type, with activation function tansig and purelin. As results, the models presented regression coefficients of 0.928 and 0.823 for turbidity and apparent color of treated water, respectively. The results corroborate for the application of Artificial Intelligence in water treatment plants, with a view to optimizing processes and guaranteeing greater WTPs operability, generating an increasingly reliable product. Keywords: Water treatment plant performance. Optimization processes. Artificial Neural Network.
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Namgung, Juhong, Siwoon Son, and Yang-Sae Moon. "Efficient Deep Learning Models for DGA Domain Detection." Security and Communication Networks 2021 (January 18, 2021): 1–15. http://dx.doi.org/10.1155/2021/8887881.
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In recent years, cyberattacks using command and control (C&C) servers have significantly increased. To hide their C&C servers, attackers often use a domain generation algorithm (DGA), which automatically generates domain names for the C&C servers. Accordingly, extensive research on DGA domain detection has been conducted. However, existing methods cannot accurately detect continuously generated DGA domains and can easily be evaded by an attacker. Recently, long short-term memory- (LSTM-) based deep learning models have been introduced to detect DGA domains in real time using only domain names without feature extraction or additional information. In this paper, we propose an efficient DGA domain detection method based on bidirectional LSTM (BiLSTM), which learns bidirectional information as opposed to unidirectional information learned by LSTM. We further maximize the detection performance with a convolutional neural network (CNN) + BiLSTM ensemble model using Attention mechanism, which allows the model to learn both local and global information in a domain sequence. Experimental results show that existing CNN and LSTM models achieved F1-scores of 0.9384 and 0.9597, respectively, while the proposed BiLSTM and ensemble models achieved higher F1-scores of 0.9618 and 0.9666, respectively. In addition, the ensemble model achieved the best performance for most DGA domain classes, enabling more accurate DGA domain detection than existing models.
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Kusumiyati, Kusumiyati, Ine Elisa Putri, and Agus Arip Munawar. "Model Prediksi Kadar Air Buah Cabai Rawit Domba (Capsicum frutescens L.) Menggunakan Spektroskopi Ultraviolet Visible Near Infrared." Agro Bali: Agricultural Journal 4, no. 1 (March 15, 2021): 15–22. http://dx.doi.org/10.37637/ab.v0i0.615.
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Penelitian ini bertujuan untuk menduga kadar air buah cabai rawit domba (Capsicum frutescens L.) menggunakan spektroskopi UV-Vis-NIR. Total sampel yang digunakan yaitu 45 buah. Analisis dilakukan di Laboratorium Hortikultura, Fakultas Pertanian, Universitas Padjadjaran. Akuisisi data spektra dengan rentang panjang gelombang 300 – 1050 nm (Nirvana AG410). Spektra diperbaiki dengan metode multiplicative scatter correction (MSC), standard normal variate transformation (SNV), orthogonal signal correction (OSC), first derivative (dg1) dan second derivative (dg2). Analisis data dilakukan dengan menggunakan partial least squares regression (PLSR). Berdasarkan penelitian ini menunjukkan bahwa metode koreksi OSC menghasilkan model kalibrasi tertinggi dengan Rkal, RMSEC, Rval, RMSECV, RPD dan faktornya masing-masing yaitu 0.99, 0.31, 0.98, 0.68, 6.62 dan 4. Hal ini menunjukkan bahwa spektroskopi UV-Vis-NIR dapat digunakan untuk memprediksi kadar air pada buah cabai rawit domba.
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Krulikovská, T., E. Jarošová, and P. Patáková. "Evaluation of Rhodotorula growth on solid substrate via a linear mixed effects model." Czech Journal of Food Sciences 29, No. 4 (August 10, 2011): 400–410. http://dx.doi.org/10.17221/327/2009-cjfs.
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The growth of Rhodotorula glutinis and Rhodotorula mucilaginosa was studied under optimal and stress cultivation conditions at 10°C and 20°C for 14 days. The method of image analysis was used to determine the size of colonies. The linear mixed effects model implemented in the statistical program S-PLUS was applied to analyse the repeated measurements. Two-phase kinetics was confirmed and the mean growth rates in the second linear phase under various stress conditions were estimated. The results indicated a higher growth rate of R. mucilaginosa than was that of R. glutinis under all cultivation conditions. The highest growth rate of was observed during the cultivation of R. mucilaginosa in media with 2% of NaCl at 20°C. The impact of neglecting the fact that repeated data are not independent and using the classical regression model instead of the mixed effects model was demonstrated through the comparison of the confidence intervals for the parameters based on both approaches. While the point estimates of the corresponding parameters were similar, the width of the confidence intervals differed substantially.
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Lazárková, Z., F. Buňka, L. Buňková, P. Valášek, S. Kráčmar, and J. Hrabě. "Application of different sterilising modes and the effects on processed cheese quality." Czech Journal of Food Sciences 28, No. 3 (July 1, 2010): 168–76. http://dx.doi.org/10.17221/44/2008-cjfs.
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The aim of the present work is to evaluate the impacts of four different sterilising modes (110°C 100 min, 115°C 32 min, 120°C 10 min, and 125°C 3.2 min – with a constant lethal effect on microorganisms) on some chemical (pH, total and bio-available lysine, and ammonia content), microbiological, and sensory (shade and acceptability) properties of processed cheese depending on the lactose additions (0.0–2.0% w/w). All sterilising modes used were sufficient to inactivate the microorganism groups observed (total number of microorganisms, colony forming units of yeasts and/or moulds, number of spore-forming microorganisms). The falling sterilisation temperature kept for an adequately prolonged period of time caused darkening of the processed cheese and a decline of their acceptability. Consequently, greater losses of lysine and ammonia content increase occurred when the sterilisation temperature decreased. Compared to non-sterilised products, the smallest changes were detected in the cheese treated with temperatures 125°C for 3.2 min, and 120°C for 10 minutes. The decrease of the processed cheese quality was more apparent with the growing lactose concentration.
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Hedengren, John D., and Thomas F. Edgar. "ORDER REDUCTION OF DAE MODELS." IFAC Proceedings Volumes 38, no. 1 (2005): 106–11. http://dx.doi.org/10.3182/20050703-6-cz-1902.01558.
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Feilke, M., B. Bischl, J. Gertheiss, and V. J. Schmid. "Boosting in Nonlinear Regression Models with an Application to DCE-MRI Data." Methods of Information in Medicine 55, no. 01 (2016): 31–41. http://dx.doi.org/10.3414/me14-01-0131.
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SummaryBackground: For the statistical analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data, compartment models are a commonly used tool. By these models, the observed uptake of contrast agent in some tissue over time is linked to physiologic properties like capillary permeability and blood flow. Up to now, models of different complexity have been used, and it is still unclear which model should be used in which situation. In previous studies, it has been found that for DCE-MRI data, the number of compartments differs for different types of tissue, and that in cancerous tissue, it might actually differ over a region of voxels of one DCE-MR image. Objectives: To find the appropriate number of compartments and estimate the parameters of a regression model for each voxel in an DCE-MR image. With that, tumors in an DCE-MR image can be located, and for example therapy success can be assessed. Methods: The observed uptake of contrast agent in a voxel of an image of some tissue is described by a concentration time curve. This curve can be modeled using a nonlinear regression model. We present a boosting approach with nonlinear regression as base procedure, which allows us to estimate the number of compartments and the related parameters for each voxel of an DCE-MR image. In addition, a spatially regularized version of this approach is proposed. Results: With the proposed approach, the number of compartments – and with that the complexity of the model – per voxel is not fixed but data-driven, which allows us to fit models of adequate complexity to the concentration time curves of all voxels. The parameters of the model remain nevertheless interpretable because of the underlying compartment model. Conclusions: The proposed boosting approaches outperform all competing methods considered in this paper regarding the correct localization of tumors in DCE-MR images as well as the spatial homogeneity of the estimated number of compartments across the image, and the definition of the tumor edge.