Data Sheet 1_The impact of climate risks on green technology innovation: an empirical study based on panel data of 269 cities in China.zip by Yangyulong Wu (19867245)

“…First, the two components of climate risks—physical risks and transition risks—significantly hinder green technology innovation. Second, physical risks suppress green technology innovation by reducing market potential, while transition risks do so by decreasing foreign direct investment. …”

Figure 2 from mTORC1-Driven Protein Translation Correlates with Clinical Benefit of Capivasertib within a Genetically Preselected Cohort of <i>PIK3CA</i>-Altered Tumors by Constance A. Sobsey (19373550)

“…Node size increases as the <i>P</i>-value decreases. <b>B,</b> Top 20 canonical pathways that are significantly differentially activated between clinical benefit (CB) and no clinical benefit (NCB) groups, based on assessment with Fisher’s exact test in Qiagen IPA. …”

Table 1_Analysis of the microstates of prolonged disorders of consciousness.docx by Yuzhang Wu (143824)

“…At the same time, the brain connectivity of pDOC patients in the four MS decreased significantly compared to the HG.</p>…”

Data Sheet 1_Immune monitoring of trabectedin therapy in refractory soft tissue sarcoma patients - the IMMUNYON study.pdf by Paulo Rodrigues-Santos (3424613)

“…Gene expression analysis identified changes in BTRC (decreased), IFNA1 (increased), and IL9 (increased) in PD versus SD patients (p<0.05). …”

Data Sheet 1_Global, regional, and national burden of hyperglycemia-associated colorectal cancer, 1990-2021: a systemic analysis for the Global Burden of Disease study.zip by Yijuan Liu (5195747)

“…Notably, while mortality-related burdens slightly decreased in high-SDI areas, YLDs continued to rise, indicating unmitigated disability burdens. …”

Proteomics analysis comparing dsProsβ1- and dsmGFP-fed cabbage stem flea beetle adults. by Doga CEDDEN (12675286)

“…Proteins with fewer than three peptide counts were discarded. Statistical significance was set at adjusted P < 0.05, with significantly altered proteins defined by LogFold2 > 1 (increased) or LogFold2 < -1 (decreased). …”

Presentation 1_A framework for modeling county-level COVID-19 transmission.pdf by Yida Bao (15255682)

“…We then use Moran's I to evaluate spatial clustering, prompting Spatial Autoregressive and Spatial Error Models when autocorrelation is significant. …”

Differential mRNA expression of key metabolic and stress response genes in the <i>MYH7</i> Q315R mice. by Shinya Takarada (8655066)

“…Clustering maps show significant changes in RNA expression (p < 0.05) greater than twofold or less than −2.0-fold (A and C). …”

Image 1_Assessment of microstructural abnormalities in gray and white matter of minimal hepatic encephalopathy patients using diffusion kurtosis imaging and their associations with... by Qing Sun (492552)

“…</p>Results<p>The TBSS analysis results showed that MHE patients had significantly decreased fractional anisotropy (FA) in the temporal part of the left superior longitudinal fasciculus and decreased kurtosis fractional anisotropy (KFA) in the left corticospinal tract and anterior thalamic radiation (p < 0.05, threshold-free cluster enhancement corrected). …”

Table 1_Novel integrated approach modeling proanthocyanidins and bacteriophages to combat multidrug Salmonella Typhimurium in challenged broilers.docx by Hanan S. Al-Khalaifah (12864938)

“…GSOPs+BP fortified group exhibited higher cecal beneficial bacteria counts (Bacteroides, Firmicutes, Lactobacillus, and Bifidobacterium species), lower cecal harmful bacteria loads (Escherichia, Enterobacteriaceae, and Clostridium clusters I and IV), decreased serum oxidative markers [H₂O₂, reactive oxygen species (ROS), and malondialdehyde (MDA)], and increased serum antioxidant enzymes [superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px)]. …”

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

“…</p>Results<p>CIBERSORTx demonstrated the highest sensitivity (r > 0.85) for detecting pituitary cell types, although accuracy decreased for TME components. Application to ten GH-secreting PitNETs with known histological contamination and to public datasets consistently revealed residual normal tissue across hormone-secreting subtypes, excluding silent tumors. …”

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)

“…HCC subtypes from the TCGA dataset were classified through consensus clustering based on differentially expressed genes (DEGs). …”

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)

“…HCC subtypes from the TCGA dataset were classified through consensus clustering based on differentially expressed genes (DEGs). …”

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)

“…HCC subtypes from the TCGA dataset were classified through consensus clustering based on differentially expressed genes (DEGs). …”

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)

“…HCC subtypes from the TCGA dataset were classified through consensus clustering based on differentially expressed genes (DEGs). …”

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)

“…HCC subtypes from the TCGA dataset were classified through consensus clustering based on differentially expressed genes (DEGs). …”

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

“…</p>Results<p>CIBERSORTx demonstrated the highest sensitivity (r > 0.85) for detecting pituitary cell types, although accuracy decreased for TME components. Application to ten GH-secreting PitNETs with known histological contamination and to public datasets consistently revealed residual normal tissue across hormone-secreting subtypes, excluding silent tumors. …”

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

“…</p>Results<p>CIBERSORTx demonstrated the highest sensitivity (r > 0.85) for detecting pituitary cell types, although accuracy decreased for TME components. Application to ten GH-secreting PitNETs with known histological contamination and to public datasets consistently revealed residual normal tissue across hormone-secreting subtypes, excluding silent tumors. …”

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

“…</p>Results<p>CIBERSORTx demonstrated the highest sensitivity (r > 0.85) for detecting pituitary cell types, although accuracy decreased for TME components. Application to ten GH-secreting PitNETs with known histological contamination and to public datasets consistently revealed residual normal tissue across hormone-secreting subtypes, excluding silent tumors. …”

Table 3_PitNET tissue deconvolution: tracing normal tissue residues and immune dynamics.xlsx by Mattia Dalle Nogare (22696022)

“…</p>Results<p>CIBERSORTx demonstrated the highest sensitivity (r > 0.85) for detecting pituitary cell types, although accuracy decreased for TME components. Application to ten GH-secreting PitNETs with known histological contamination and to public datasets consistently revealed residual normal tissue across hormone-secreting subtypes, excluding silent tumors. …”