GSEA results. by Wan-Jing Zhen (20427813)

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GO enrichment analysis. by Wan-Jing Zhen (20427813)

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37%, 63%, and 100% amplitude (mm) and latency (ms). by Tomoe Hayakawa (20978784)

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Impact of group 1 and group 2 drugs on hyperglycemia based on HbA1c levels before and after 3 months of administration. by Nadia Gul (249538)

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The complex interplay between SGLT-2is, RAAS, and glucose metabolism in type 2 diabetes mellitus patients. by Ningning Wang (560944)

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Experimental design. by Amy J. Schuh (8520354)

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Effects of SGLT-2is during the time course. by Ningning Wang (560944)

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Changes of physical and biochemical indicators from baseline and difference between DKD and non-DKD patients. by Ningning Wang (560944)

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Baseline characteristics between DKD and non-DKD patients. by Ningning Wang (560944)

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Flow diagram of patient recruitment. by Ningning Wang (560944)

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Data used to generate Figs 2–7 and S1 Fig. by Amy J. Schuh (8520354)

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Spearman correlation analysis of the RAAS and glucose metabolism indicators before and after treatment in DKD and non-DKD patients. by Ningning Wang (560944)

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PRISMA flowchart of the included studies. by Gaelle Salame (21077899)

“…On the other hand, patients in the immunotherapy group had significantly decreased HbA1c levels (MD = -0.63; 95% CI: [-1.18, -0.07]; p = 0.03), indicating that immunotherapy had a positive impact on glycemic management. …”

Characteristics of Included Studies. by Gaelle Salame (21077899)

“…On the other hand, patients in the immunotherapy group had significantly decreased HbA1c levels (MD = -0.63; 95% CI: [-1.18, -0.07]; p = 0.03), indicating that immunotherapy had a positive impact on glycemic management. …”

Fig 6 - by Samuel Hylander (331771)

Relative expression level of GCN2 in the resistant and susceptible strains of <i>H. armigera.</i> by Caihong Zhang (1633294)

Fig 1 - by Samuel Hylander (331771)

Fig 3 - by Samuel Hylander (331771)

Fig 4 - by Samuel Hylander (331771)

Online travelogues information from Ctrip. by Weiya Zhang (346410)

“…Findings indicate that: (1) Locations mentioned in Tang and Song poetry show significant spatial differentiation, with urban areas displaying a clustered distribution and suburbs showing scattered hotspots. (2) The number of locations referenced in Song poetry increased significantly compared to Tang poetry, suggesting that Nanjing’s economic growth heightened the city’s appeal and inspired more literary output. (3) Song Dynasty poetry reflects a shift toward more neutral and negative emotions, with a marked decrease in positive expressions. …”