Regions of significance for the relationship between IRQ disclosure and ICC at various levels of CGQ (Johnson-Neyman plot). by Muhammad Arslan Iqbal (12021908)

Volcano plot on differential expression. by Bingshuo Shi (21485387)

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Demographic data of female participants (n = 30). by Vanessa Wellauer (18408477)

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Raw data used for statistical analysis. by Vanessa Wellauer (18408477)

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CONSORT flowchart of participants. by Vanessa Wellauer (18408477)

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AC-LPN circuit control high temperature induced increase of evening sleep. by Xin Yuan (174619)

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Table 1_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx by Stefanie Wagner (743707)

“…In another experimental setting with tulathromycin treatment, bacterial abundance quantification by flow cytometry and by a spike-in method yielded similar results only on the phylum level. Even though the spike-in method identified the decrease of four genera, analysis by fluorescence-activated cell sorting (FACS) uncovered eight significantly reduced genera, such as Prevotella and Paraprevotella upon antibiotic treatment. …”

Table 3_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx by Stefanie Wagner (743707)

“…In another experimental setting with tulathromycin treatment, bacterial abundance quantification by flow cytometry and by a spike-in method yielded similar results only on the phylum level. Even though the spike-in method identified the decrease of four genera, analysis by fluorescence-activated cell sorting (FACS) uncovered eight significantly reduced genera, such as Prevotella and Paraprevotella upon antibiotic treatment. …”

Table 4_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx by Stefanie Wagner (743707)

“…In another experimental setting with tulathromycin treatment, bacterial abundance quantification by flow cytometry and by a spike-in method yielded similar results only on the phylum level. Even though the spike-in method identified the decrease of four genera, analysis by fluorescence-activated cell sorting (FACS) uncovered eight significantly reduced genera, such as Prevotella and Paraprevotella upon antibiotic treatment. …”

Table 8_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx by Stefanie Wagner (743707)

“…In another experimental setting with tulathromycin treatment, bacterial abundance quantification by flow cytometry and by a spike-in method yielded similar results only on the phylum level. Even though the spike-in method identified the decrease of four genera, analysis by fluorescence-activated cell sorting (FACS) uncovered eight significantly reduced genera, such as Prevotella and Paraprevotella upon antibiotic treatment. …”

Table 2_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx by Stefanie Wagner (743707)

“…In another experimental setting with tulathromycin treatment, bacterial abundance quantification by flow cytometry and by a spike-in method yielded similar results only on the phylum level. Even though the spike-in method identified the decrease of four genera, analysis by fluorescence-activated cell sorting (FACS) uncovered eight significantly reduced genera, such as Prevotella and Paraprevotella upon antibiotic treatment. …”

Table 6_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx by Stefanie Wagner (743707)

“…In another experimental setting with tulathromycin treatment, bacterial abundance quantification by flow cytometry and by a spike-in method yielded similar results only on the phylum level. Even though the spike-in method identified the decrease of four genera, analysis by fluorescence-activated cell sorting (FACS) uncovered eight significantly reduced genera, such as Prevotella and Paraprevotella upon antibiotic treatment. …”

Table 5_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx by Stefanie Wagner (743707)

“…In another experimental setting with tulathromycin treatment, bacterial abundance quantification by flow cytometry and by a spike-in method yielded similar results only on the phylum level. Even though the spike-in method identified the decrease of four genera, analysis by fluorescence-activated cell sorting (FACS) uncovered eight significantly reduced genera, such as Prevotella and Paraprevotella upon antibiotic treatment. …”

Table 7_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx by Stefanie Wagner (743707)

“…In another experimental setting with tulathromycin treatment, bacterial abundance quantification by flow cytometry and by a spike-in method yielded similar results only on the phylum level. Even though the spike-in method identified the decrease of four genera, analysis by fluorescence-activated cell sorting (FACS) uncovered eight significantly reduced genera, such as Prevotella and Paraprevotella upon antibiotic treatment. …”

Table 9_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx by Stefanie Wagner (743707)

“…In another experimental setting with tulathromycin treatment, bacterial abundance quantification by flow cytometry and by a spike-in method yielded similar results only on the phylum level. Even though the spike-in method identified the decrease of four genera, analysis by fluorescence-activated cell sorting (FACS) uncovered eight significantly reduced genera, such as Prevotella and Paraprevotella upon antibiotic treatment. …”

The top 10 putative metabolites with the largest negative fold change between normal and thin cows. by Bhuripit Saraphol (20855573)

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The top 10 putative metabolites with the largest positive fold change between normal and thin cows. by Bhuripit Saraphol (20855573)

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The principal component analysis (PCA) plot utilized in the quality assurance process. by Bhuripit Saraphol (20855573)

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Diversity of the fecal microbiome in normal and thin cows according to 16S rRNA gene sequencing data. by Bhuripit Saraphol (20855573)

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The numbers of normal and thin cows from each farm. by Bhuripit Saraphol (20855573)

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