Table 2_Impact of fasting and refeeding on immune markers, hepatic gene expression, and gut microbiota in geese: insights into metabolic regulation and gut-liver interactions.xlsx by Yi Liu (36759)

“…In this study, biochemical, transcriptome and 16S rRNA sequencing techniques were used to investigate the physiological effects of fasting and refeeding on immune responses, liver gene expression, and gut microbiota composition in geese. Fasting led to a significant reduction in circulating levels of IgA and IFN-γ, while IgG, TNF-α, IL-6, and IL-10 levels remained stable. …”

Image 2_Can Chinese patients restore normal knee function 1 year after total knee arthroplasty?.jpeg by YiShun Guo (22629887)

“…Based on expert and patient focus group discussions, a set of evaluation items was established, followed by designing a self-administered questionnaire assessing importance, frequency, and difficulty. …”

Data Sheet 1_In vivo quantification of superficial cortical veins on susceptibility-weighted imaging with artificial intelligence image segmentation and the potential mechanism of... by Qi Xie (230608)

“…The curvature of SCVs in the right cerebral hemisphere had a significant impact on cognitive decline, with a strong positive correlation. …”

Percent of recording electrodes excited or inhibited by stimulation at different frequencies, amplitudes, and types of electrodes. by Uma R. Mohan (19950039)

“…<p>(<b>a</b>) Percent of recording electrodes showing significant high frequency activity increases and decreases for each stimulation frequency for depth and surface stimulation sites. …”

Optimizing Irradiation Dose for <i>Drosophila melanogaster</i> Males to Enhance Heterospecific Sterile Insect Technique Against <i>Drosophila suzukii</i> by Flavia Cerasti (21075827)

“…<p dir="ltr">The spotted-wing drosophila (<i>Drosophila suzukii</i>), a highly invasive agricultural pest, poses significant challenges to fruit production worldwide. …”

Image 1_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 8_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 6_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 2_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 7_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 5_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 4_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 3_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

PTEN KD increases chromatin accessibility. by Ahmed H. Ghobashi (12705573)

“…<p><b>(A)</b> Barplot of normalized enrichment scores for genesets with significant enrichment by GSEA using the epigenetic geneset dataset and genes significantly upregulated in PTEN knockdown (KD) relative to empty vector (EV) from the RNA-seq data in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0313769#pone.0313769.g002" target="_blank">Fig 2</a> (|log 2FC|>1; p < 0.05). …”

Data Sheet 1_Comparative analysis of proteomics and transcriptomics reveals novel mechanism underlying the antibacterial activity and immune-enhancing properties of horse milk.zip by Xueshan Chen (17477633)

“…KEGG analysis showed that horse milk contained abundant antimicrobial associated proteins relevant to pathogenic bacterial resistance, leading to the decreased risk of pathogenic diseases. A higher accumulation of proteins associated with caffeine metabolism, amino acid biosynthesis, and glycolysis/gluconeogenesis in horse milk contributes to its distinctive flavor. …”

Table2_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…Background<p>Polycystic ovary syndrome (PCOS) is a complex endocrine disorder with various contributing factors. …”

Table13_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…Background<p>Polycystic ovary syndrome (PCOS) is a complex endocrine disorder with various contributing factors. …”

Table12_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…Background<p>Polycystic ovary syndrome (PCOS) is a complex endocrine disorder with various contributing factors. …”

Table3_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…Background<p>Polycystic ovary syndrome (PCOS) is a complex endocrine disorder with various contributing factors. …”

Table9_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…Background<p>Polycystic ovary syndrome (PCOS) is a complex endocrine disorder with various contributing factors. …”