The treatment with anti-CXCR3 decreases the number of CD8⁺ T cells in the heart. by Camila Pontes Ferreira (6194006)

Loss of fenestrations and decreased VEGF production in <i>Cyp1b1-/-</i> LSEC. by Juliana Falero-Perez (5905103)

“…A significant increase in the level of caveolin-1 α-isoform and a decrease in the caveolin-1 β-isoform were noted (**P< 0.01; n = 3). …”

The gradual loss of the IFN-γ antiviral effect is accompanied by decreased STAT1 phosphorylation in BMMs. by Yong Shen (284972)

Mice exposed to neonatal hyperoxia have persistent RVH and decreased vessel density at 21d. by Marta Perez (526067)

Fig 3 - by Dennis Ochola (11626912)

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Untargeted metabolomic analysis of delayed death-parasites indicates isoprenoid defect and decreased haemoglobin turnover. by Kit Kennedy (4915510)

Sampled locations with banana in 2016. by Dennis Ochola (11626912)

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Classification and regression tree (CART) showing the biophysical factors associated with geographic shift in banana at national level. by Dennis Ochola (11626912)

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Scanned map of historical locations with banana in 1958. by Dennis Ochola (11626912)

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Average nearest neighbour analysis before and after filtering of data points. by Dennis Ochola (11626912)

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List of 12 covariates selected subjectively and their underlying reasons for their selection. by Dennis Ochola (11626912)

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Fig 6 - by Dennis Ochola (11626912)

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Fig 9 - by Dennis Ochola (11626912)

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Fig 7 - by Dennis Ochola (11626912)

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K-means clustering was performed to cluster the genes according to their expression kinetics. by Seon-Pil Jin (17364626)

Comparison between logistic regression models of different complexity and structure derived from the 12 covariates chosen using subjective feature selection. by Dennis Ochola (11626912)

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Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 12 covariates chosen using subjective feature selection. by Dennis Ochola (11626912)

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Fig 4 - by Dennis Ochola (11626912)

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Fig 5 - by Dennis Ochola (11626912)

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Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 17 covariates selected after recursive feature selection. by Dennis Ochola (11626912)

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