Accurate identification of axillary lymph node (ALN) involvement in patients with early-stage breast cancer is important for determining appropriate axillary treatment options and therefore avoiding unnecessary axillary surgery and complications. Here, we report deep learning radiomics (DLR) of conventional ultrasound and shear wave elastography of breast cancer for predicting ALN status preoperatively in patients with early-stage breast cancer. Clinical parameter combined DLR yields the best diagnostic performance in predicting ALN status between disease-free axilla and any axillary metastasis with areas under the receiver operating characteristic curve (AUC) of 0.902 (95% confidence interval [CI]: 0.843, 0.961) in the test cohort. This clinical parameter combined DLR can also discriminate between low and heavy metastatic burden of axillary disease with AUC of 0.905 (95% CI: 0.814, 0.996) in the test cohort. Our study offers a noninvasive imaging biomarker to predict the metastatic extent of ALN for patients with early-stage breast cancer.

Genomic selection is being used increasingly in plant breeding to accelerate genetic gain per unit time. One of the most important applications of genomic selection in maize breeding is to predict and select the best un-phenotyped lines in bi-parental populations based on genomic estimated breeding values. In the present study, 22 bi-parental tropical maize populations genotyped with low density SNPs were used to evaluate the genomic prediction accuracy (rMG) of the six trait-environment combinations under various levels of training population size (TPS) and marker density (MD), and assess the effect of trait heritability (h2), TPS and MD on rMG estimation. Our results showed that: (1) moderate rMG values were obtained for different trait-environment combinations, when 50% of the total genotypes was used as training population and ~200 SNPs were used for prediction; (2) rMG increased with an increase in h2, TPS and MD, both correlation and variance analyses showed that h2 is the most important factor and MD is the least important factor on rMG estimation for most of the trait-environment combinations; (3) predictions between pairwise half-sib populations showed that the rMG values for all the six trait-environment combinations were centered around zero, 49% predictions had rMG values above zero; (4) the trend observed in rMG differed with the trend observed in rMG/h, and h is the square root of heritability of the predicted trait, it indicated that both rMG and rMG/h values should be presented in GS study to show the accuracy of genomic selection and the relative accuracy of genomic selection compared with phenotypic selection, respectively. This study provides useful information to maize breeders to design genomic selection workflow in their breeding programs.

Intraspecific haploid induction in maize (Zea mays) is triggered by a native frameshift mutation in MATRILINEAL (MATL), which encodes a pollen-specific phospholipase. To develop a haploid inducer in rice (Oryza sativa), we generated an allelic series in the putative ZmMATL orthologue, OsMATL, and found that knockout mutations led to a reduced seed set and a 2-6% haploid induction rate. This demonstrates MATL functional conservation and represents a major advance for rice breeding.

Background: Inflammation plays an important role in the pathogenesis of ovarian cancer. This study sought to investigate the association between the preoperative c-reactive protein/albumin ratio (CRP/Alb) and oncological outcomes in ovarian cancer patients. Methods: Two hundred patients with histologically verified ovarian cancer between June 2006 and July 2012 were retrospectively reviewed. Overall survival was evaluated by the Kaplan-Meier method and log-rank test. The significance of risk factors for overall survival was evaluated with the Cox proportional hazards model. Additionally, area under the receiver operating characteristic curve (AUC) was used to compare the predictive ability of CRP/Alb, Glasgow Prognostic Score (GPS), modified GPS (mGPS), neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), prognostic index (PI) and prognostic nutritional index (PNI). Results: The optimal cutoff value of CRP/Alb was 0.68. Increased CRP/Alb (≥0.68) was associated with advanced stage, residual tumor, ascites, elevated serum carbohydrate antigen(CA)-125 level, GPS, and mGPS (all p < 0.05). Patients with high CRP/Alb had poor overall survival compared to those with low CRP/Alb (p < 0.001). Multivariable analysis showed that CRP/Alb (Hazard Ratio (HR) 1.330, 95% confidence interval (CI) 1.131-1.564, p = 0.001), tumor stage (HR 1.577, 95% CI 1.189-2.091, p = 0.002), residual tumor (HR 2.337, 95% CI 1.518-3.597, p < 0.001) and age (HR 1.017, 95% CI 1.000-1.035, p = 0.046) were independent prognostic factors for overall survival. Additionally, the CRP/Alb showed greater AUC values at 1 year (0.692), 3 years (0.659), and 5 years (0.682) than GPS, mGPS and PNI. Conclusions: The CRP/Alb is a novel independent marker of poor prognosis among ovarian cancer patients and shows superior prognostic ability compared to the established inflammation-based prognostic indices.

Lithium recovery from spent LiFePO 4 batteries is significant to prevent resource depletion and environmental pollution. In this study, the employment of "water in salt" electrolyte in LiFePO 4 battery enlightened us to develop a novel method for the selective recovery of lithium from spent LiFePO 4 batteries through oxidizing LiFePO 4 to FePO 4 with sodium persulfate (Na 2 S 2 O 8 ). Effect of several variables on the Li leaching efficiency was investigated. Additionally, combined thermodynamic analysis and characterization of XRD, XPS were employed to investigate the leaching mechanism. More than 99% of Li can be selectively leached in 20 min at ambient temperature with only 0.05 times excess of Na 2 S 2 O 8 . The high leaching efficiency can be ascribed to the stability and without destruction for the solid structure during the oxidation leaching. A closed-loop process was then proposed for recycling entire spent LiFePO 4 batteries, and finally high purity Li 2 CO 3 (99 wt %) was successfully prepared. The process is economically feasible and environmentally friendly and has great potential for the industrial-scale recycling of spent LiFePO 4 batteries.

Drought stress (DS) is a major constraint to maize yield production. Heat stress (HS) alone and in combination with DS are likely to become the increasing constraints. Association mapping and genomic prediction (GP) analyses were conducted in a collection of 300 tropical and subtropical maize inbred lines to reveal the genetic architecture of grain yield and flowering time under well-watered (WW), DS, HS, and combined DS and HS conditions. Out of the 381,165 genotyping-by-sequencing SNPs, 1549 SNPs were significantly associated with all the 12 trait-environment combinations, the average PVE (phenotypic variation explained) by these SNPs was 4.33%, and 541 of them had a PVE value greater than 5%. These significant associations were clustered into 446 genomic regions with a window size of 20 Mb per region, and 673 candidate genes containing the significantly associated SNPs were identified. In addition, 33 hotspots were identified for 12 trait-environment combinations and most were located on chromosomes 1 and 8. Compared with single SNP-based association mapping, the haplotype-based associated mapping detected fewer number of significant associations and candidate genes with higher PVE values. All the 688 candidate genes were enriched into 15 gene ontology terms, and 46 candidate genes showed significant differential expression under the WW and DS conditions. Association mapping results identified few overlapped significant markers and candidate genes for the same traits evaluated under different managements, indicating the genetic divergence between the individual stress tolerance and the combined drought and HS tolerance. The GP accuracies obtained from the marker-trait associated SNPs were relatively higher than those obtained from the genome-wide SNPs for most of the target traits. The genetic architecture information of the grain yield and flowering time revealed in this study, and the genomic regions identified for the different trait-environment combinations are useful in accelerating the efforts on rapid development of the stress-tolerant maize germplasm through marker-assisted selection and/or genomic selection.

We investigated the influence of resistance exercise (RE) with different intensities on HbA1c, insulin and blood glucose levels in patients with type 2 diabetes (T2D). Diabetes trials that compared RE group with a control were included in meta-analysis. Exercise intensities were categorized into low-to-moderate-intensity and high-intensity subgroups. Intensity effect on glycemic control was determined by meta-regression analysis, and risk-of-bias was assessed using Cochrane Collaboration tool. 24 trials met the inclusion criteria, comprised of 962 patients of exercise (n = 491) and control (n = 471). Meta-regression analysis showed decreased HbA1c (p = 0.006) and insulin (p = 0.015) after RE was correlated with intensity. Subgroup analysis revealed decreased HbA1c was greater with high intensity (−0.61; 95% CI −0.90, −0.33) than low-to-moderate intensity (−0.23; 95% CI −0.41, −0.05). Insulin levels were significantly decreased only with high intensity (−4.60; 95% CI −7.53, −1.67), not with low-to-moderate intensity (0.07; 95% CI −3.28, 3.42). Notably, values between the subgroups were statistically significant for both HbA1c (p = 0.03) and insulin (p = 0.04), indicative of profound benefits of high-intensity RE. Pooled outcomes of 15 trials showed only a decreased trend in blood glucose with RE (p = 0.09), and this tendency was not associated with intensity. Our meta-analysis provides additional evidence that high-intensity RE has greater beneficial effects than low-to-moderate-intensity in attenuation of HbA1c and insulin in T2D patients.

Chemoresistance has become a major obstacle to the success of cancer therapy, but the mechanisms underlying chemoresistance are not yet fully understood. O-GlcNAcylation is a post-translational modification that is regulated by the hexosamine biosynthetic pathway (HBP) and has an important role in a wide range of cellular functions. Here we assessed the role of O-GlcNAcylation in chemoresistance and investigated the underlying cellular mechanisms. The results showed that the HBP has an important role in cancer cell chemoresistance by regulating O-GlcNAcylation. An increase in the levels of O-GlcNAcylation indicates an increased resistance of cancer cells to chemotherapy. Acute treatment with doxorubicin (DOX) or camptothecin (CPT) induced O-GlcNAcylation through HBP activation. In fact, the chemotherapy agents activated the AKT/X-box-binding protein 1 (XBP1) axis and then induced the HBP. Furthermore, the observed elevation of cellular O-GlcNAcylation led to activation of survival signalling pathways and chemoresistance in cancer cells. Finally, suppression of O-GlcNAcylation reduced the resistance of both established and primary cancer cells to chemotherapy. These results provide significant novel insights regarding the important role of the HBP and O-GlcNAcylation in regulating cancer chemoresistance. Thus, O-GlcNAc inhibition might offer a new strategy for improving the efficacy of chemotherapy.