Variable importance in Random Forest model of seasonal sediment transport with 1468 observations from 2009 to 2018. by Andrew Kulmatiski (833256)

Patient interest in participating in care tasks. by Chava Kurtz (21519468)

“…</p><p>Results</p><p>Questionnaires from 339 patients in hospital and community-based units showed 89.1% expressed interest in care tasks. Lower education (OR 0.36, 95% CI 0.15–0.9) and being single (OR 0.27, 95% CI 0.12–0.6) decreased interest. …”

The MTT assay and the LDH assay were used to assess the effects of the hydrogel component of MBC-005 on tumor cell number and cell death. by Bryan S. Margulies (21492667)

Supplementary table 1. by Javier A. Flores-Cohaila (16933983)

“…WV had a moderate effect on sleep problems (aPR: 2.06, 95% CI: 1.45 to 2.97) and depressive symptoms (aPR: 1.65, 95% CI: 1.47–1.86). …”

Inhibitor versus the normalized dose response curves. by Bryan S. Margulies (21492667)

Metabolome data of the discovery cohort. by Feng Gao (3548)

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The orthogonal projection to latent structure discriminant analysis (OPLS-DA) analysis of the three groups (OC vs HC, OC vs RC and RC vs HC) of the discovery cohort. by Feng Gao (3548)

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S9 Data - Alterations in the serum metabolome in patients with the COVID-19 Omicron variant and in recovered cases by Feng Gao (3548)

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S3 Data - Alterations in the serum metabolome in patients with the COVID-19 Omicron variant and in recovered cases by Feng Gao (3548)

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Clinical characteristics of COVID-19 cases and healthy controls in the discovery cohort. by Feng Gao (3548)

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S7 Data - Alterations in the serum metabolome in patients with the COVID-19 Omicron variant and in recovered cases by Feng Gao (3548)

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S2 Data - Alterations in the serum metabolome in patients with the COVID-19 Omicron variant and in recovered cases by Feng Gao (3548)

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Relative intensities of differential metabolites that may serve as potential metabolic biomarkers in Omicron variant cases. by Feng Gao (3548)

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S4 Data - Alterations in the serum metabolome in patients with the COVID-19 Omicron variant and in recovered cases by Feng Gao (3548)

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S6 Data - Alterations in the serum metabolome in patients with the COVID-19 Omicron variant and in recovered cases by Feng Gao (3548)

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S5 Data - Alterations in the serum metabolome in patients with the COVID-19 Omicron variant and in recovered cases by Feng Gao (3548)

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ROC curve analysis for the predictive power of biomarkers for distinguishing between patients with Omicron variant and healthy controls. by Feng Gao (3548)

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Analysis of the correlation between pharyngeal microbiomics, metabolomics and clinical indicators between OC and HC. by Feng Gao (3548)

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Metabolome KEGG enrichment analysis of serum in Omicron variant cases and recovered cases. by Feng Gao (3548)

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Untargeted metabolomic profiling of sera from Omicron variant cases of the discovery cohort. by Feng Gao (3548)

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