BackgroundThe pollen wall, which protects male gametophyte against various stresses and facilitates pollination, is essential for successful reproduction in flowering plants. The pollen wall consists of gametophyte-derived intine and sporophyte-derived exine. From outside to inside of exine are tectum, bacula, nexine I and nexine II layers. How these structural layers are formed has been under extensive studies, but the molecular mechanisms remain obscure.ResultsHere we identified two osabcg3 allelic mutants and demonstrated that OsABCG3 was required for pollen development in rice. OsABCG3 encodes a half-size ABCG transporter localized on the plasma membrane. It was mainly expressed in anther when exine started to form. Loss-function of OsABCG3 caused abnormal degradation of the tapetum. The mutant pollen lacked the nexine II and intine layers, and shriveled without cytoplasm. The expression of some genes required for pollen wall formation was examined in osabcg3 mutants. The mutation did not alter the expression of the regulatory genes and lipid metabolism genes, but altered the expression of lipid transport genes.ConclusionsBase on the genetic and cytological analyses, OsABCG3 was proposed to transport the tapetum-produced materials essential for pollen wall formation. This study provided a new perspective to the genetic regulation of pollen wall development.Electronic supplementary materialThe online version of this article (10.1186/s12284-018-0248-8) contains supplementary material, which is available to authorized users.

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Objective. To investigate the association of the plasma level of cytokines and blood routine indexes with clinical characteristics in patients with cancer. Methods. We analyzed plasma samples derived from 134 cancer patients. Interleukins (IL) 1β, 2, 4, 5, 6, 8, 10, 12p70, 17, IFN-c, IFN-α, and TNF-α, and blood routine indexes were measured. e associations of the levels of cytokine and blood routine indexes with demographic and clinical characteristics of cancer patients were analyzed. Partial least-squares discriminant analysis was employed to identify cancer metastasis using these plasma cytokine metrics as input. We compared the predictive e ectiveness of numeric machine learning algorithms using these indexes and showed a promising model implemented with random forest. Results. Plasma levels of IL-6 and IL-8 in cancer patients with metastases were higher than those without metastases (P < 0.05). Cancer patients without metastases had signi cantly higher levels of plasma IL-12p70 and percentage of lymphocytes as compared with those with metastases (P < 0.05). Our random forest model showed the highest prediction performance (upper quantile AUC, 0.885) among the six machine learning algorithms we evaluated. Conclusion. Our ndings suggest that plasma levels of IL-6, IL-8, and IL-12p70 and the percentage of lymphocytes could predict the recurrence, metastasis, and progression of cancer. Our ndings will provide guidance for tumor monitoring and treatment.

Pancreatic adenocarcinomas (PAADs) often remain undiagnosed until later stages, limiting treatment options and leading to poor survival. The lack of robust biomarkers complicates PAAD prognosis, and patient risk stratification remains a major challenge. To address this issue, we established a panel constructed by four miRNAs (miR-4444-2, miR-934, miR-1301 and miR-3655) based on The Cancer Genome Atlas (TCGA) and Human Cancer Metastasis Database (HCMDB) to predicted the prognosis of PAAD patients. Then, a risk prediction model of these four miRNAs was constructed by using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) regression analysis. This model stratified TCGA PAAD cohort into the low-risk and high-risk groups based on the panel-based risk score, which was significantly associated with 1-, 2-, 3-year OS (AUC=0.836, AUC=0.844, AUC=0.952, respectively). The nomogram was then established with a robust performance signature for predicting prognosis compared to clinical characteristics of pancreatic cancer (PC) patients, including age, gender and clinical stage. Moreover, two GSE data were validated the expressions of 4 miRNAs with prognosis/survival outcome in PC. In the external clinical sample validation, the high-risk group with the upregulated expressions of miR-934/miR-4444-2 and downregulated expressions of miR-1301/miR-3655 were indicated a poor prognosis. Furthermore, the cell counting kit-8 (CCK-8) assay, clone formation, transwell and wound healing assay also confirmed the promoting effect of miR-934/miR-4444-2 and the inhibiting effect of miR-1301/miR-3655 in PC cell proliferation and migration. Taken together, we identified a new 4-miRNA risk stratification model could be used in predicting prognosis in PAAD.