Table 2_Exploring Histoplasma species seroprevalence and risk factors for seropositivity in The Gambia’s working equid population: Baseline analysis of the Tackling Histoplasmosis... by Tessa Rose Cornell (15460726)

“…In horses, two multivariable models explained the maximum amount of data variability. Model 1 demonstrated increased odds of seropositivity in mares [odds ratio (OR) = 2.90 95% CI 1.70–4.95, p < 0.001] and decreased odds in horses <2.5 years (OR = 0.46 95% CI 0.22–0.95, p = 0.04; reference: ≥4.5 years). …”

Table 10_Exploring Histoplasma species seroprevalence and risk factors for seropositivity in The Gambia’s working equid population: Baseline analysis of the Tackling Histoplasmosis... by Tessa Rose Cornell (15460726)

“…In horses, two multivariable models explained the maximum amount of data variability. Model 1 demonstrated increased odds of seropositivity in mares [odds ratio (OR) = 2.90 95% CI 1.70–4.95, p < 0.001] and decreased odds in horses <2.5 years (OR = 0.46 95% CI 0.22–0.95, p = 0.04; reference: ≥4.5 years). …”

Table 3_Exploring Histoplasma species seroprevalence and risk factors for seropositivity in The Gambia’s working equid population: Baseline analysis of the Tackling Histoplasmosis... by Tessa Rose Cornell (15460726)

“…In horses, two multivariable models explained the maximum amount of data variability. Model 1 demonstrated increased odds of seropositivity in mares [odds ratio (OR) = 2.90 95% CI 1.70–4.95, p < 0.001] and decreased odds in horses <2.5 years (OR = 0.46 95% CI 0.22–0.95, p = 0.04; reference: ≥4.5 years). …”

Table 8_Exploring Histoplasma species seroprevalence and risk factors for seropositivity in The Gambia’s working equid population: Baseline analysis of the Tackling Histoplasmosis... by Tessa Rose Cornell (15460726)

“…In horses, two multivariable models explained the maximum amount of data variability. Model 1 demonstrated increased odds of seropositivity in mares [odds ratio (OR) = 2.90 95% CI 1.70–4.95, p < 0.001] and decreased odds in horses <2.5 years (OR = 0.46 95% CI 0.22–0.95, p = 0.04; reference: ≥4.5 years). …”

Table 6_Exploring Histoplasma species seroprevalence and risk factors for seropositivity in The Gambia’s working equid population: Baseline analysis of the Tackling Histoplasmosis... by Tessa Rose Cornell (15460726)

“…In horses, two multivariable models explained the maximum amount of data variability. Model 1 demonstrated increased odds of seropositivity in mares [odds ratio (OR) = 2.90 95% CI 1.70–4.95, p < 0.001] and decreased odds in horses <2.5 years (OR = 0.46 95% CI 0.22–0.95, p = 0.04; reference: ≥4.5 years). …”

Table 5_Exploring Histoplasma species seroprevalence and risk factors for seropositivity in The Gambia’s working equid population: Baseline analysis of the Tackling Histoplasmosis... by Tessa Rose Cornell (15460726)

“…In horses, two multivariable models explained the maximum amount of data variability. Model 1 demonstrated increased odds of seropositivity in mares [odds ratio (OR) = 2.90 95% CI 1.70–4.95, p < 0.001] and decreased odds in horses <2.5 years (OR = 0.46 95% CI 0.22–0.95, p = 0.04; reference: ≥4.5 years). …”

Table 4_Exploring Histoplasma species seroprevalence and risk factors for seropositivity in The Gambia’s working equid population: Baseline analysis of the Tackling Histoplasmosis... by Tessa Rose Cornell (15460726)

“…In horses, two multivariable models explained the maximum amount of data variability. Model 1 demonstrated increased odds of seropositivity in mares [odds ratio (OR) = 2.90 95% CI 1.70–4.95, p < 0.001] and decreased odds in horses <2.5 years (OR = 0.46 95% CI 0.22–0.95, p = 0.04; reference: ≥4.5 years). …”

Table 7_Exploring Histoplasma species seroprevalence and risk factors for seropositivity in The Gambia’s working equid population: Baseline analysis of the Tackling Histoplasmosis... by Tessa Rose Cornell (15460726)

“…In horses, two multivariable models explained the maximum amount of data variability. Model 1 demonstrated increased odds of seropositivity in mares [odds ratio (OR) = 2.90 95% CI 1.70–4.95, p < 0.001] and decreased odds in horses <2.5 years (OR = 0.46 95% CI 0.22–0.95, p = 0.04; reference: ≥4.5 years). …”

Image2_GABA Type A receptors expressed in triple negative breast cancer cells mediate chloride ion flux.TIF by J Bundy (19843944)

“…GABA_A β3 subunit knockdown causes cell cycle arrest in TNBC cell lines via decreased cyclin D1 and increased p21 expression. However, it is not known if the upregulated GABA_AR express at the cell-surface in TNBC and mediate Cl⁻ flux. …”

Image 9_Genomic, transcriptomic, and T cell receptor profiling in stratifying response to first-line chemoradiotherapy or radiotherapy for esophageal squamous cell carcinoma.jpeg by Xiaqin Zhang (10211396)

“…Richness was significantly decreased from pre-treat to post-treat.…”

Image 8_Genomic, transcriptomic, and T cell receptor profiling in stratifying response to first-line chemoradiotherapy or radiotherapy for esophageal squamous cell carcinoma.jpeg by Xiaqin Zhang (10211396)

“…Richness was significantly decreased from pre-treat to post-treat.…”

Image 5_Genomic, transcriptomic, and T cell receptor profiling in stratifying response to first-line chemoradiotherapy or radiotherapy for esophageal squamous cell carcinoma.jpeg by Xiaqin Zhang (10211396)

“…Richness was significantly decreased from pre-treat to post-treat.…”

Image 2_Genomic, transcriptomic, and T cell receptor profiling in stratifying response to first-line chemoradiotherapy or radiotherapy for esophageal squamous cell carcinoma.jpeg by Xiaqin Zhang (10211396)

“…Richness was significantly decreased from pre-treat to post-treat.…”

Image 3_Genomic, transcriptomic, and T cell receptor profiling in stratifying response to first-line chemoradiotherapy or radiotherapy for esophageal squamous cell carcinoma.jpeg by Xiaqin Zhang (10211396)

“…Richness was significantly decreased from pre-treat to post-treat.…”

Image 4_Genomic, transcriptomic, and T cell receptor profiling in stratifying response to first-line chemoradiotherapy or radiotherapy for esophageal squamous cell carcinoma.jpeg by Xiaqin Zhang (10211396)

“…Richness was significantly decreased from pre-treat to post-treat.…”

Image 11_Genomic, transcriptomic, and T cell receptor profiling in stratifying response to first-line chemoradiotherapy or radiotherapy for esophageal squamous cell carcinoma.jpeg by Xiaqin Zhang (10211396)

“…Richness was significantly decreased from pre-treat to post-treat.…”

Image 10_Genomic, transcriptomic, and T cell receptor profiling in stratifying response to first-line chemoradiotherapy or radiotherapy for esophageal squamous cell carcinoma.jpeg by Xiaqin Zhang (10211396)

“…Richness was significantly decreased from pre-treat to post-treat.…”

Image 7_Genomic, transcriptomic, and T cell receptor profiling in stratifying response to first-line chemoradiotherapy or radiotherapy for esophageal squamous cell carcinoma.jpeg by Xiaqin Zhang (10211396)

“…Richness was significantly decreased from pre-treat to post-treat.…”

Image 6_Genomic, transcriptomic, and T cell receptor profiling in stratifying response to first-line chemoradiotherapy or radiotherapy for esophageal squamous cell carcinoma.jpeg by Xiaqin Zhang (10211396)

“…Richness was significantly decreased from pre-treat to post-treat.…”

Correlation analyses between studied genes. by Marwa A. Ali (11973086)

“…</p><p>Conclusions</p><p>Our study is the first to detect decreased <i>NEAT-1</i> and <i>miR374b-5p</i> expression in COVID-19 patients’ serum. …”