RNA-seq and qPCR analyses of transcription levels of fiber development related genes in Li₁ mutant and WT plants.

<p><b>A-I: qPCR analysis of gene expression levels</b> in 1 DPA, 3 DPA, and 8 DPA ovules and in leaves; J-R: Transcriptome expression levels of these genes.</p

GO enrichment of common DEGs at 1 DPA and 3 DPA in Li₁ mutant and WT tissues.

<p>Scatterplots of enriched GO terms for common down-regulated DEGs (A) and common up-regulated DEGs (B).</p

Association between gene polymorphisms and lung cancer risk in non-smokers.

<p>Association between gene polymorphisms and lung cancer risk in non-smokers.</p

Linkage disequilibrium (LD) patterns of the two SNPs in 15q25.1.

<p>Numbers inside the boxes represent <i>r</i>² values for LD. Colors indicate the strength of LD between pair-wise combinations of SNPs (white, low LD; red, high LD).</p

Association between gene polymorphisms and smoking behaviors among smokers of lung cancer cases and controls.

<p>Data were expressed as mean±standard deviation.</p

Early fiber elongation pathways that are differentially regulated in Li₁ mutant and WT plants.

<p>Early fiber elongation pathways that are differentially regulated in Li₁ mutant and WT plants.</p

DEGs in the ovules and leaves of Li₁ mutant and wild type plants.

<p>A: the expression levels of DEGs were altered in Li₁ mutant compared to wild type; B: distribution of the DEGs at 1 DPA and 3 DPA.</p

Comparison of the phenotypes of WT and Li₁ mutant seed fibers and leaves.

<p>Comparison of the phenotypes of WT and Li₁ mutant seed fibers and leaves.</p

Dynamic progression of common DEGs in leaf and ovule transcriptomes.

<p>(A) Unsupervised hierarchical clustering of the 7492 common DEGs in the Li₁ mutant. Common DEGs were clustered into six groups and the number of genes in each group is listed on the right. Red region, genes up-regulated in the Li₁ mutant; green region, genes down-regulated in the Li₁ mutant. (B) Functional distribution of common DEGs in the Li₁ mutant. (C) Functional categorization of common DEGs in the dominant mutants. ‘Others’ includes 22 minor categories.</p

Adoptive Immunotherapy in Postoperative Non-Small-Cell Lung Cancer: A Systematic Review and Meta-Analysis

<div><p>Background</p><p>Adoptive immunotherapy (AI) has been applied in the treatment of non-small-cell lung cancer (NSCLC) patients, but the value of postoperative AI has been inconclusive largely as a result of the small number of patients included in each study. We performed a systematic review and meta-analysis to address this issue for patients with postoperative NSCLC.</p><p>Methods</p><p>Pubmed, Embase, Cochrane Library were searched for randomized controlled trials comparing adoptive immunotherapy with control therapies in postoperative NSCLC patients. The primary endpoint was overall survival. Hazard ratio (HR) was estimated and 95% confidence intervals (CI) were calculated using a fixed-effect model.</p><p>Results</p><p>Compared with control therapies, analyses of 4 randomized controlled trials (472 patients) showed a significant benefit of adoptive immunotherapy on survival (hazard ratio [HR] 0.61, 95% CI 0.45–0.84, p = 0.002), and a 39% reduction in the relative risk of death (no evidence of a difference between trials; p = 0.16, I² = 42%). In subgroup analyses by treatment cycles and treatment regimen, significant OS benefit was found in combination therapy of AI with chemotherapy, regardless of whether or not the treatment cycles were more than 10 cycles.</p><p>Conclusion</p><p>Adoptive immunotherapy has the potential to improve overall survival in postoperative NSCLC. The findings suggest this is a valid treatment option for these patients. Further randomized clinical trials are urgently needed.</p></div