Image_2_North American Propolis Extracts From Upstate New York Decrease Nosema ceranae (Microsporidia) Spore Levels in Honey Bees (Apis mellifera).jpeg by Andre J. Burnham (9149522)

“…Beekeepers have used dicyclohexylammonium fumagillin to control Nosema apis, although it may be ineffective against N. ceranae. We investigated the ability of various propolis extracts collected from Upstate New York (United States) to decrease in vivo N. ceranae infection levels when fed ad libitum to N. ceranae-infected honey bees. …”

Image_1_North American Propolis Extracts From Upstate New York Decrease Nosema ceranae (Microsporidia) Spore Levels in Honey Bees (Apis mellifera).jpeg by Andre J. Burnham (9149522)

“…Beekeepers have used dicyclohexylammonium fumagillin to control Nosema apis, although it may be ineffective against N. ceranae. We investigated the ability of various propolis extracts collected from Upstate New York (United States) to decrease in vivo N. ceranae infection levels when fed ad libitum to N. ceranae-infected honey bees. …”

Percentage of homology at metabolite composition level based on the number of different significant chemical features within each cluster and between the most distant clusters. by Laura Perez-Fons (8056685)

“…<p>Percentage of homology at metabolite composition level based on the number of different significant chemical features within each cluster and between the most distant clusters.…”

Summary of significant clusters composition from the seed-based connectivity analysis of the brainstem (covering ≥ 10% of the regions). by Sadeq Mohammadi (22622219)

“…<p>Summary of significant clusters composition from the seed-based connectivity analysis of the brainstem (covering ≥ 10% of the regions).…”

Significant spatial clusters of newborn care in Ethiopia, EDHS 2016. by Melaku Hunie Asratie (9312013)

Distribution distances between Cluster 1 and Cluster 2 based on Kullback-Leibler divergence. by Duy Nguyen (1831585)

Subjects:

Identification of specific cluster DEGs based on two disulfidptosis-related molecular clusters. by Jie Yuan (208425)

Subjects:

County-level geographical septile distribution for the first 12 statistically significant factors with at least one statistically significant coefficient ranked by decreasing ΔIC. by Yanan Long (11784717)

Detection of three clusters of the patients based on the height (cluster distances) in dendrogram. by Mehrdad Davoudi (9704675)

Clusters of significant Gene Ontology terms for pudendal block treatment. by Charles J. Tran (11482404)

Clusters of significant Gene Ontology terms for laughing gas treatment. by Charles J. Tran (11482404)

Persistence based clustering and an overview of PrestoCell. by Yue Wu (1262184)

Subjects:

Cluster analysis based on taxonomic dissimilarity and Ward’s clustering method. by Benjamín Quiroz-Martínez (276876)

SLE sample clustering based on GRGs and differential analysis between clusters. by Yinghao Ren (17915291)

Table_1_Decrease in the number of new cancer diagnoses during the first year of the COVID-19 pandemic – cohort study of 3.5 million individuals in western Poland.docx by Maciej Trojanowski (17690721)

“…In females the observed incidence was higher than expected for cancer of an unspecified site (SIR 1·19, 95% CI 1·01 to 1·38). In our study, the decrease in new cancer cases was greater in males than in females.…”

Significant clusters for gray matter volume loss per timepoint comparison. by Jesse D. de Groot (15401476)

Analysis of significant differences in ARG abundance for the geographical clusters in figure 3S. by Markus H. K. Johansson (17241650)

Analysis of significant differences in MGE abundance for the geographical clusters in figure 2S. by Markus H. K. Johansson (17241650)

Significant clusters for white matter volume loss per timepoint comparison. by Jesse D. de Groot (15401476)

Univariate LISA (Cluster and significance) maps depicting spatial clustering and spatial outliers of District Composite Health Profile (DCHP 5), based on NFHS-5. by Bindhy Wasini Pandey (18794176)