Table 2_Hyper-fractionated radiotherapy as a bridging strategy to enhance CAR-T efficacy by regulating T-cell co-stimulatory molecules in relapsed/refractory diffuse large B-cell l... by Jing Ruan (5117951)

“…After hyper-fractionated radiotherapy, peripheral PD1+CD8+T/T ratio significantly decreased while quantitative serum proteomics profiling showed a decrease in sCD28.…”

Table 1_Hyper-fractionated radiotherapy as a bridging strategy to enhance CAR-T efficacy by regulating T-cell co-stimulatory molecules in relapsed/refractory diffuse large B-cell l... by Jing Ruan (5117951)

“…After hyper-fractionated radiotherapy, peripheral PD1+CD8+T/T ratio significantly decreased while quantitative serum proteomics profiling showed a decrease in sCD28.…”

Table 3_Hyper-fractionated radiotherapy as a bridging strategy to enhance CAR-T efficacy by regulating T-cell co-stimulatory molecules in relapsed/refractory diffuse large B-cell l... by Jing Ruan (5117951)

“…After hyper-fractionated radiotherapy, peripheral PD1+CD8+T/T ratio significantly decreased while quantitative serum proteomics profiling showed a decrease in sCD28.…”

Mst1 knockout skewed macrophage polarization toward a proinflammatory and profibrotic phenotype with concomitant down-regulation of CD36. by Jianyang Li (461703)

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Downregulation of CD36 impaired phagocytic capacity and is associated with a proinflammatory phenotype of <i>Mst1</i> deficiency macrophages. by Jianyang Li (461703)

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Comparison of demographic estimates from GI-1d-a and GS-1. by Isabell Schmidt (6331013)

Serum concentrations of malondialdehyde (a) and super oxide dismutase (b) and NOx (nitrate +nitrite) (c) in different experimental groups on day 2 and 10. by Omid Mehrpour (9385929)

Appendix figures. by Alexandra Dunnum VandeLoo (22209218)

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Structure of the Segment Anything Model (SAM) from the original paper [5]. by Alexandra Dunnum VandeLoo (22209218)

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Qualitative comparison of zero-shot, cross-dataset performance. by Alexandra Dunnum VandeLoo (22209218)

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Feasibility of AI-powered assessment scoring: Can large language models replace human raters? by Michael Jaworski III (22156096)

“…<p><b>Objective:</b> To assess the feasibility, accuracy, and reliability of using ChatGPT-4.5 (early-access), a large language model (LLM), for automated scoring of Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) protocols. …”

The expression of the corresponding genes of Fig 5A in PEMs from uninfected Mst1^+/+ and Mst1^ΔM/ΔM mice. by Jianyang Li (461703)

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Factor associated with body fat mass loss^b'*' in both periods of inpatient treatment. by Domingos L. S. Rios (20496173)

(A) Auxiliary marking points to ensure complete and accurate seating of the prosthesis. by Long Li (6555)

The concentration of inflammatory parameters (TNF-α and IL-10) in serum (a and b) and burned skin samples (c) of different experimental groups on day 2 and 10. by Omid Mehrpour (9385929)

The concentrations of malondialdehyde (a), super oxide dismutase (b), and NOx (nitrate +nitrite)(c) in the burned skin samples of different experimental groups on day 2 and 10. by Omid Mehrpour (9385929)

Source data of S3 Fig, the list of corresponding genes in Fig 5A of PEMs from control Mst1^+/+ and Mst1^ΔM/ΔM mice. by Jianyang Li (461703)

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Pie charts showing the different patterns of risk factors associated with total colony losses. by Beatrice T. Nganso (4114768)

Sample characteristics: Countries, cities and city innovation. by Saul Estrin (8629173)

Bar graphs showing the total loss rates and 95% confidence intervals for each region in Ethiopia, Kenya, and Benin. by Beatrice T. Nganso (4114768)