Construction of a nomogram model for deep vein thrombosis in patients with tibial plateau fracture based on the Systemic Inflammatory Response Index.

BACKGROUND: In recent years, the incidence of tibial plateau fracture has been on the rise, predominantly affecting the elderly population. Deep vein thrombosis may lead to poor prognosis in patients. the Systemic Inflammatory Response Index are novel biomarkers of inflammation, and this study aims to verify their predictive effect and construct the nomogram model. METHOD: This study used binary logistic regression analysis to predict the predictive effect of SIRI on the occurrence of DVT in tibial plateau fracture patients. And use R studio to construct nomogram model. RESULT: The results showed that NC (7.036 [3.516, 14.080], p < 0.001), LYM (0.507 [0.265, 0.969], p = 0.04), and SIRI (2.090 [1.044, 4.182], p = 0.037) were independent predictive factors for DVT. The nomogram demonstrated good predictive performance with small errors in both the training and validation groups, and most clinical patients could benefit from them. CONCLUSION: The nomogram constructed based on SIRI can assist clinicians in early assessment of the probability of DVT occurrence.

Identification of Ear Morphology Genes in Maize (Zea mays L.) Using Selective Sweeps and Association Mapping.

The performance of maize hybrids largely depend on two parental inbred lines. Improving inbred lines using artificial selection is a key task in breeding programs. However, it is important to elucidate the effects of this selection on inbred lines. Altogether, 208 inbred lines from two maize heterosis groups, named Shaan A and Shaan B, were sequenced by the genotype-by-sequencing to detect genomic changes under selection pressures. In addition, we completed genome-wide association analysis in 121 inbred lines to identify candidate genes for ear morphology related traits. In a genome-wide selection scan, the inbred lines from Shaan A and Shaan B groups showed obvious population divergences and different selective signals distributed in 337 regions harboring 772 genes. Meanwhile, functional enrichment analysis showed those selected genes are mainly involved in regulating cell development. Interestingly, some ear morphology related traits showed significant differentiation between the inbred lines from the two heterosis groups. The genome-wide association analysis of ear morphology related traits showed that four associated genes were co-localized in the selected regions with high linkage disequilibrium. Our spatiotemporal pattern and gene interaction network results for the four genes further contribute to our understanding of the mechanisms behind ear and fruit length development. This study provides a novel insight into digging a candidate gene for complex traits using breeding materials. Our findings in relation to ear morphology will help accelerate future maize improvement.