Supplementary file 1_Comparative analysis of accuracy and completeness in standardized database generation for complex multilingual lung cancer pathological reports: large language... by Hao Hang (7037264)

“…Background<p>This study evaluates how AI enhances EHR efficiency by comparing a lung cancer-specific LLM with general-purpose models (DeepSeek, GPT-3.5) and clinicians across expertise levels, assessing accuracy and completeness in complex lung cancer pathology documentation and task load changes pre−/post-AI implementation.…”

Lick latency across trial types. by Alice Berners-Lee (15354255)

Supplementary Material for: A Novel Mutation in Insulin-Like Growth Factor 1 Receptor (c.641-2A>G) Is Associated with Impaired Growth, Hypoglycemia, and Modified Immune Phenotypes by Shapiro M.R. (9572729)

“…Flow cytometric immunophenotyping demonstrated lower IGF1R on peripheral blood mononuclear cells from <i>IGF1R</i> c.641-2A>G subjects. This alteration was associated with reduced levels of T-helper 17 cells and a higher percentage of T-helper 1 cells compared to controls, suggesting decreased IGF1R expression may affect CD4⁺ Th-cell lineage commitment. …”

LEfSe analysis between CCO and HC. by Guangying Cui (459719)

LEfSe analysis between CCO and CCOS. by Guangying Cui (459719)

Table2_Enhanced Transgene Expression by Optimization of Poly A in Transfected CHO Cells.DOCX by Xiao-yin Wang (11992034)

“…Importantly, the SV40 and Synt poly A elements decreased the variation of eGFP transgene expression. …”

Table1_Enhanced Transgene Expression by Optimization of Poly A in Transfected CHO Cells.DOC by Xiao-yin Wang (11992034)

“…Importantly, the SV40 and Synt poly A elements decreased the variation of eGFP transgene expression. …”

Tomato gene ontology clustering based on expression values for each GO term. by Michael Schneider (1806265)

Barley gene ontology clustering based on expression values for each GO term. by Michael Schneider (1806265)

AS-IV modified the composition of fecal microflora in rats with LPS-induced ALI. by Cheng Luo (48047)

Schematic diagram of the molecular mechanism by which TRIM37 improves MS by stabilizing PEX5 through monoubiquitination. by Lai Jiang (2401513)

DataSheet_1_Sulforaphane Exerts Beneficial Immunomodulatory Effects on Liver Tissue via a Nrf2 Pathway-Related Mechanism in a Murine Model of Hemorrhagic Shock and Resuscitation.pd... by Weiqiang Liang (772055)

“…<p>Our research explores the immunomodulatory effects of sulforaphane (SFN), a well-known nuclear factor erythroid 2-related factor 2 (Nrf2) pathway agonist, on the sterile inflammation of and ischemia-reperfusion injuries to the liver after hemorrhagic shock (HS) followed by resuscitation (R). …”

COG annotation of differentially abundant proteins of three genotypes of <i>Lolium perenne</i> (fold increase>1.5, fold decrease<0.5, <i>P</i> < 0.05). by Fatemeh Raeisi Vanani (8991491)

Interaction plot with 95% confidence intervals generated from the GAM regression model 1 in Table 2 examining initial ED SBP and management group interactions. by Randeep S. Jawa (20489181)

Tomato gene expression of normalized expression value. by Michael Schneider (1806265)

Barley gene expression of normalized expression value. by Michael Schneider (1806265)

Expression dynamics and hormone regulation of <i>AaERR</i> in the adult female <i>Ae</i>. <i>aegypti</i>. by Dan-Qian Geng (18137370)

Genes associated with androgen-induced decrease in H3K27me3 mark in the gene body and overlapping with promoters and distal enhancers involving long-range regulation of gene expres... by Sambit Roy (5463899)

“…<p>A: Heat maps showing the read density change along the peak regions for the 16345 control peaks and the 3975 treatment peaks. …”

Change in final number of adults for impacted populations compared to baseline abundances (%, colors) over a range of sizes of constructed side-channels (y-axis), annual chronic an... by Pascale Gibeau (9866702)

Benchmark regression results. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”