Graphic abstract of the study. by Donglin Yang (490406)

“…The results showed that the expression of circRNAs in serum exosomes of DN patients was significantly down-regulated, and hsa_circ_0006382 and hsa_circ_0019539 targeted the expression of FGF9 by binding to miR-34a-5p, miR-766-3p, miR-147a and miR-27a-3p. …”

Data Sheet 1_Antibiofilm potential of plant extracts: inhibiting oral microorganisms and Streptococcus mutans.pdf by Nomi Bartels (20997935)

“…P. cretica was able to inhibit and kill S. mutans at a concentration of 0.6 mg/ml, but its effectiveness in biofilm inhibition significantly decreased at 2.5 mg/ml.…”

Data Sheet 1_Therapeutic potential of Cordyceps militaris cultivated with Ginkgo biloba seeds for alleviating western diet-induced type 2 diabetes and diabetic nephropathy.pdf by Shinn-Zong Lin (217003)

“…Key biochemical markers, including blood glucose, triglycerides, cholesterol, blood urea nitrogen (BUN), and creatinine, were significantly improved after treatment. Histopathologic analysis revealed restored renal morphology, reduced fibrosis and decreased amyloid deposition. …”

Raw data. by Donglin Yang (490406)

“…The results showed that the expression of circRNAs in serum exosomes of DN patients was significantly down-regulated, and hsa_circ_0006382 and hsa_circ_0019539 targeted the expression of FGF9 by binding to miR-34a-5p, miR-766-3p, miR-147a and miR-27a-3p. …”

Additional file 2 of Whole genome sequencing of the pulmonary microbiome in interstitial lung disease subtypes by Kristel S. Knudsen (10535406)

“…Every red dot on the plot represents differentially abundant species with increased significance noted towards the top of the plot. …”

Table 2_Prevalence of pathogens from clinical samples associated with porcine respiratory and digestive diseases in South Korea from 2021 to 2023.docx by Hye-young Wang (8786045)

“…The trends in 3-year prevalence showed no significant changes, but in 2023, viral infections (e.g., PRRSV, Rotavirus, porcine epidemic diarrhea virus, etc.) decreased and bacterial infections (e.g., Mycoplasma hyopneumoniae (MH), Pasteurella multocida (PM), Haemophilus parasuis (HP), Salmonella spp., Lawsonia intracellularis, and Brachyspira hyodysenteriae) slightly increased (χ² = 11.36, P < 0.001). …”

Table 1_Prevalence of pathogens from clinical samples associated with porcine respiratory and digestive diseases in South Korea from 2021 to 2023.docx by Hye-young Wang (8786045)

“…The trends in 3-year prevalence showed no significant changes, but in 2023, viral infections (e.g., PRRSV, Rotavirus, porcine epidemic diarrhea virus, etc.) decreased and bacterial infections (e.g., Mycoplasma hyopneumoniae (MH), Pasteurella multocida (PM), Haemophilus parasuis (HP), Salmonella spp., Lawsonia intracellularis, and Brachyspira hyodysenteriae) slightly increased (χ² = 11.36, P < 0.001). …”

Protein and gene expression levels of p62 and LC3B in miR-7974 mimic-transfected MCF-7 cells. by Stralina Eneh (21213312)

“…<b>(B)</b> The fold change of p62 and <b>(C)</b> LC3BI between negative control/cell-only samples and miR-7974-treated samples were statistically significant. GAPDH was used as a reference protein. …”

Data Sheet 1_Impact of SARS-CoV-2 vaccination and of seasonal variations on the innate immune inflammatory response.pdf by Hend Jarras (13138641)

“…</p>Results<p>Our results show that IL-8 production after stimulation decreased after vaccination. In addition, the IL-8 response was significantly different depending on the season when the visit occurred, for both COVID-19 vaccinated and unvaccinated individuals.…”

Figure 3 from Acetalax (Oxyphenisatin Acetate, NSC 59687) and Bisacodyl Cause Oncosis in Triple-Negative Breast Cancer Cell Lines by Poisoning the Ion Exchange Membrane Protein TRP... by Makito Mizunuma (18950775)

“…Percentage of fragmented mitochondria on the <i>y</i>-axis represents the comparison between control and Acetalax-treated groups. <b>A,</b> Significant change in mitochondrial fragmentation is indicated by the brackets. *, <i>P</i> < 0.01; **, <i>P</i> < 0.005; ***, <i>P</i> < 0.0001 (using the Mann–Whitney <i>U</i> test, calculated in Prism 9.0). …”

Population structure impacts the relationship between the amount of environmental DNA particles and organism abundance by Toshiaki S. Jo (15869182)

“…On the other hand, under the allometric eDNA production, the <i>R</i>^<em>2</em> values decreased for the populations with broader population size range and broader/heterogeneous mass distribution by using biomass, which was not statistically significant by using ASM.…”

Data Sheet 1_PitNET tissue deconvolution: tracing normal tissue residues and immune dynamics.pdf by Mattia Dalle Nogare (22696022)

“…However, its limited ability to resolve cellular heterogeneity – particularly in samples containing residual non-tumor pituitary cells – remains a significant challenge.</p>Objective<p>We developed and validated a tissue deconvolution framework using a reference dataset derived from single-nucleus RNA sequencing (snRNA-seq) of normal pituitary tissue, aimed at estimating cellular composition in PitNETs from bulk RNA-seq data and characterizing the tumor microenvironment (TME).…”

Data Sheet 2_Uncovering the heterogeneity of NK cells on the prognosis of HCC by integrating bulk and single-cell RNA-seq data.csv by Jiashuo Li (7865036)

“…Background<p>The tumor microenvironment (TME) plays a critical role in the development, progression, and clinical outcomes of hepatocellular carcinoma (HCC). …”

Image 2_Uncovering the heterogeneity of NK cells on the prognosis of HCC by integrating bulk and single-cell RNA-seq data.jpeg by Jiashuo Li (7865036)

“…Background<p>The tumor microenvironment (TME) plays a critical role in the development, progression, and clinical outcomes of hepatocellular carcinoma (HCC). …”

Image 4_Uncovering the heterogeneity of NK cells on the prognosis of HCC by integrating bulk and single-cell RNA-seq data.jpeg by Jiashuo Li (7865036)

“…Background<p>The tumor microenvironment (TME) plays a critical role in the development, progression, and clinical outcomes of hepatocellular carcinoma (HCC). …”

Image 3_Uncovering the heterogeneity of NK cells on the prognosis of HCC by integrating bulk and single-cell RNA-seq data.jpeg by Jiashuo Li (7865036)

“…Background<p>The tumor microenvironment (TME) plays a critical role in the development, progression, and clinical outcomes of hepatocellular carcinoma (HCC). …”

Image 5_Uncovering the heterogeneity of NK cells on the prognosis of HCC by integrating bulk and single-cell RNA-seq data.jpeg by Jiashuo Li (7865036)

“…Background<p>The tumor microenvironment (TME) plays a critical role in the development, progression, and clinical outcomes of hepatocellular carcinoma (HCC). …”

Data Sheet 2_PitNET tissue deconvolution: tracing normal tissue residues and immune dynamics.pdf by Mattia Dalle Nogare (22696022)

“…However, its limited ability to resolve cellular heterogeneity – particularly in samples containing residual non-tumor pituitary cells – remains a significant challenge.</p>Objective<p>We developed and validated a tissue deconvolution framework using a reference dataset derived from single-nucleus RNA sequencing (snRNA-seq) of normal pituitary tissue, aimed at estimating cellular composition in PitNETs from bulk RNA-seq data and characterizing the tumor microenvironment (TME).…”

Table 2_PitNET tissue deconvolution: tracing normal tissue residues and immune dynamics.xlsx by Mattia Dalle Nogare (22696022)

“…However, its limited ability to resolve cellular heterogeneity – particularly in samples containing residual non-tumor pituitary cells – remains a significant challenge.</p>Objective<p>We developed and validated a tissue deconvolution framework using a reference dataset derived from single-nucleus RNA sequencing (snRNA-seq) of normal pituitary tissue, aimed at estimating cellular composition in PitNETs from bulk RNA-seq data and characterizing the tumor microenvironment (TME).…”

Table 1_PitNET tissue deconvolution: tracing normal tissue residues and immune dynamics.xlsx by Mattia Dalle Nogare (22696022)

“…However, its limited ability to resolve cellular heterogeneity – particularly in samples containing residual non-tumor pituitary cells – remains a significant challenge.</p>Objective<p>We developed and validated a tissue deconvolution framework using a reference dataset derived from single-nucleus RNA sequencing (snRNA-seq) of normal pituitary tissue, aimed at estimating cellular composition in PitNETs from bulk RNA-seq data and characterizing the tumor microenvironment (TME).…”