Table 1_Insights into the association of Nicotiana tabacum health with eukaryotic microbial community and environmental factors.docx by Longxin Chai (20991224)

“…Compared with soil associated with healthy Nicotiana tabacum, the alpha and beta diversity of the eukaryotic microbial community decreased in soil with diseased Nicotiana tabacum, indicating a decline in microbial abundance and composition. …”

Long-term divergence of nitrogen and phosphorus dynamics in small lakes across China by Shaojuan Du (22465949)

Comparative analysis of four distinct microstructures: S1G0, S1G1, S1G2, and S2G0. by Camilo A. S. Afanador (22232423)

“…The porosity of <b>S1G0</b> and <b>S2G0</b> () aligns with <i>μ</i>CT measurements from the literature. Note the increase in porosity in <b>S1G1</b> and <b>S1G2</b> due to the morphological filter. …”

RNA levels of selected CMGC kinases in dHepaRG, PHHs and liver biopsies. by Florentin Pastor (19852287)

Fig 6 - by Francesco Poli (19995426)

Image 1_Heterogeneous appetite patterns in depression: computational modeling of nutritional interoception, reward processing, and decision-making.jpeg by Yuuki Uchida (12564583)

“…This study aimed to explore the potential of computational psychiatry in addressing these issues. Using a homeostatic reinforcement learning model formalizing the link between internal states and behavioral control, we investigated the mechanisms by which altered interoception affects homeostatic behavior and reward system activity via simulation experiments. …”

Table 2_Heterogeneous appetite patterns in depression: computational modeling of nutritional interoception, reward processing, and decision-making.docx by Yuuki Uchida (12564583)

“…This study aimed to explore the potential of computational psychiatry in addressing these issues. Using a homeostatic reinforcement learning model formalizing the link between internal states and behavioral control, we investigated the mechanisms by which altered interoception affects homeostatic behavior and reward system activity via simulation experiments. …”

Table 1_Heterogeneous appetite patterns in depression: computational modeling of nutritional interoception, reward processing, and decision-making.docx by Yuuki Uchida (12564583)

“…This study aimed to explore the potential of computational psychiatry in addressing these issues. Using a homeostatic reinforcement learning model formalizing the link between internal states and behavioral control, we investigated the mechanisms by which altered interoception affects homeostatic behavior and reward system activity via simulation experiments. …”

Data Sheet 1_Immunometabolic alterations in type 2 diabetes mellitus revealed by single-cell RNA sequencing: insights into subtypes and therapeutic targets.csv by Huahua Li (6896339)

“…</p>Results<p>In patients with T2DM, a marked increase in monocytes and a decrease in CD4+ T cells were observed, indicating immune dysregulation. …”

Data Sheet 4_Immunometabolic alterations in type 2 diabetes mellitus revealed by single-cell RNA sequencing: insights into subtypes and therapeutic targets.csv by Huahua Li (6896339)

“…</p>Results<p>In patients with T2DM, a marked increase in monocytes and a decrease in CD4+ T cells were observed, indicating immune dysregulation. …”

Data Sheet 2_Immunometabolic alterations in type 2 diabetes mellitus revealed by single-cell RNA sequencing: insights into subtypes and therapeutic targets.csv by Huahua Li (6896339)

“…</p>Results<p>In patients with T2DM, a marked increase in monocytes and a decrease in CD4+ T cells were observed, indicating immune dysregulation. …”

Data Sheet 3_Immunometabolic alterations in type 2 diabetes mellitus revealed by single-cell RNA sequencing: insights into subtypes and therapeutic targets.csv by Huahua Li (6896339)

“…</p>Results<p>In patients with T2DM, a marked increase in monocytes and a decrease in CD4+ T cells were observed, indicating immune dysregulation. …”

Data Sheet 1_Patient-centered modeling of the breast biopsy experience.pdf by Isabel Nieto-Alvarez (22425466)

“…</p>Results<p>We (1) provide a visual model of the patient pathway, (2) predict, with linear mixed models and machine learning, anxiety based on psychological pre-assessments as well as procedural events, and (3) analyze communication between caregiver and patient to understand moderators of the patient experience. …”

Table 1_CAMDA 2023: Finding patterns in urban microbiomes.csv by Haydeé Contreras-Peruyero (20320404)

Image 1_CAMDA 2023: Finding patterns in urban microbiomes.tiff by Haydeé Contreras-Peruyero (20320404)

Data Sheet 1_CAMDA 2023: Finding patterns in urban microbiomes.pdf by Haydeé Contreras-Peruyero (20320404)

Table 1_Near-infrared prediction of total phosphorus in leaves content in korla fragrant pear with growth period specificity via spectral modeling.docx by Mingyang Yu (7456358)

Table 1_WGCNA-ML-MR integration: uncovering immune-related genes in prostate cancer.docx by Jing Lv (128179)

“…The intersection of differentially expressed genes and driver genes was taken, and Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed. Furthermore, a machine learning algorithm was used to screen for core genes and construct a diagnostic model, which was then validated in an external validation dataset. …”

Image 1_WGCNA-ML-MR integration: uncovering immune-related genes in prostate cancer.tif by Jing Lv (128179)

“…The intersection of differentially expressed genes and driver genes was taken, and Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed. Furthermore, a machine learning algorithm was used to screen for core genes and construct a diagnostic model, which was then validated in an external validation dataset. …”

Maps illustrating the absolute change in probabilistic landslide susceptibility values following the impact of (a) Storm Podul and (b) Typhoon Molave in comparison to the post-Kets... by Raja Das (1841107)