Rydberg atom electric field sensing for metrology, communication and hybrid quantum systems.

Rydberg atoms-based electric field sensing has developed rapidly over the past decade. A variety of theoretical proposals and experiment configurations are suggested and realized to improve the measurement metrics, such as intensity sensitivity, bandwidth, phase, and accuracy. The Stark effect and electromagnetically induced transparency (EIT) or electromagnetically induced absorption (EIA) are fundamental physics principles behind the stage. Furthermore, various techniques such as amplitude- or frequency-modulation, optical homodyne read-out, microwave superheterodyne and frequency conversion based on multi-wave mixing in atoms are utilized to push the metrics into higher levels. In this review, different technologies and the corresponding metrics they had achieved were presented, hoping to inspire more possibilities in the improvement of metrics of Rydberg atom-based electric field sensing and broadness of application scenarios.

Ergodicity breaking from Rydberg clusters in a driven-dissipative many-body system.

It is challenging to probe ergodicity breaking trends of a quantum many-body system when dissipation inevitably damages quantum coherence originated from coherent coupling and dispersive two-body interactions. Rydberg atoms provide a test bed to detect emergent exotic many-body phases and nonergodic dynamics where the strong Rydberg atom interaction competes with and overtakes dissipative effects even at room temperature. Here, we report experimental evidence of a transition from ergodic toward ergodic breaking dynamics in driven-dissipative Rydberg atomic gases. The broken ergodicity is featured by the long-time phase oscillation, which is attributed to the formation of Rydberg excitation clusters in limit cycle phases. The broken symmetry in the limit cycle is a direct manifestation of many-body collective effects, which is verified experimentally by tuning atomic densities. The reported result reveals that Rydberg many-body systems are a promising candidate to probe ergodicity breaking dynamics, such as limit cycles, and enable the benchmark of nonequilibrium phase transition.

Current knowledge and potential intervention of hexosamine biosynthesis pathway in lung cancer.

Lung cancer is a highly prevalent malignancy characterized by significant metabolic alterations. Understanding the metabolic rewiring in lung cancer is crucial for the development of effective therapeutic strategies. The hexosamine biosynthesis pathway (HBP) is a metabolic pathway that plays a vital role in cellular metabolism and has been implicated in various cancers, including lung cancer. Abnormal activation of HBP is involved in the proliferation, progression, metastasis, and drug resistance of tumor cells. In this review, we will discuss the function and regulation of metabolic enzymes related to HBP in lung cancer. Furthermore, the implications of targeting the HBP for lung cancer treatment are also discussed, along with the challenges and future directions in this field. This review provides a comprehensive understanding of the role and intervention of HBP in lung cancer. Future research focusing on the HBP in lung cancer is essential to uncover novel treatment strategies and improve patient outcomes.

The RUBY reporter enables efficient haploid identification in maize and tomato.

In vivo haploid induction has been extended from maize to monocotyledonous plants like rice, wheat, millet and dicotyledonous plants such as tomato, rapeseed, tobacco and cabbage. Accurate identification of haploids is a crucial step of doubled haploid technology, where a useful identification marker is very pivotal. R1-nj is an extensively used visual marker for haploid identification in maize. RFP and eGFP have been shown to be feasible in identifying haploid. However, these methods are either limited to specific species, or require specific equipment. It still lacks an efficient visual marker that is practical across different crop species. In this study, we introduced the RUBY reporter, a betalain biosynthesis system, into maize and tomato haploid inducers as a new marker for haploid identification. Results showed that expression of RUBY could result in deep betalain pigmentation in maize embryos as early as 10 days after pollination, and enabled 100% accuracy of immature haploid embryo identification. Further investigation in tomato revealed that the new marker led to deep red pigmentation in radicles and haploids can be identified easily and accurately. The results demonstrated that the RUBY reporter is a background-independent and efficient marker for haploid identification and would be promising in doubled haploid breeding across different crop species.

Genome-wide association and genomic prediction for resistance to southern corn rust in DH and testcross populations.

Southern corn rust (SCR), caused by Puccinia polysora Underw, is a destructive disease that can severely reduce grain yield in maize (Zea mays L.). Owing to P. polysora being multi-racial, it is very important to explore more resistance genes and develop more efficient selection approaches in maize breeding programs. Here, four Doubled Haploid (DH) populations with 384 accessions originated from selected parents and their 903 testcross hybrids were used to perform genome-wide association (GWAS). Three GWAS processes included the additive model in the DH panel, additive and dominant models in the hybrid panel. As a result, five loci were detected on chromosomes 1, 7, 8, 8, and 10, with P-values ranging from 4.83×10-7 to 2.46×10-41. In all association analyses, a highly significant locus on chromosome 10 was detected, which was tight chained with the known SCR resistance gene RPPC and RPPK. Genomic prediction (GP), has been proven to be effective in plant breeding. In our study, several models were performed to explore predictive ability in hybrid populations for SCR resistance, including extended GBLUP with different genetic matrices, maker based prediction models, and mixed models with QTL as fixed factors. For GBLUP models, the prediction accuracies ranged from 0.56-0.60. Compared with traditional prediction only with additive effect, prediction ability was significantly improved by adding additive-by-additive effect (P-value< 0.05). For maker based models, the accuracy of BayesA and BayesB was 0.65, 8% higher than other models (i.e., RRBLUP, BRR, BL, BayesC). Finally, by adding QTL into the mixed linear prediction model, the accuracy can be further improved to 0.67, especially for the G_A model, the prediction performance can be increased by 11.67%. The prediction accuracy of the BayesB model can be further improved significantly by adding QTL information (P-value< 0.05). This study will provide important valuable information for understanding the genetic architecture and the application of GP for SCR in maize breeding.

Deep learning enhanced Rydberg multifrequency microwave recognition.

Recognition of multifrequency microwave (MW) electric fields is challenging because of the complex interference of multifrequency fields in practical applications. Rydberg atom-based measurements for multifrequency MW electric fields is promising in MW radar and MW communications. However, Rydberg atoms are sensitive not only to the MW signal but also to noise from atomic collisions and the environment, meaning that solution of the governing Lindblad master equation of light-atom interactions is complicated by the inclusion of noise and high-order terms. Here, we solve these problems by combining Rydberg atoms with deep learning model, demonstrating that this model uses the sensitivity of the Rydberg atoms while also reducing the impact of noise without solving the master equation. As a proof-of-principle demonstration, the deep learning enhanced Rydberg receiver allows direct decoding of the frequency-division multiplexed signal. This type of sensing technology is expected to benefit Rydberg-based MW fields sensing and communication.

ZmCOI2a and ZmCOI2b redundantly regulate anther dehiscence and gametophytic male fertility in maize.

In higher plants, the generation and release of viable pollen from anthers is vital for double fertilization and the initiation of seed development. Thus, the characterization of genes related to pollen development and anther dehiscence in plants is of great significance. The F-box protein COI1 plays a crucial role in the jasmonate (JA) signaling pathway and interacts with many JAZ family proteins in the presence of jasmonoyl-isoleucine (JA-Ile) or coronatine (COR). The mutation of AtCOI1 in Arabidopsis leads to defective anther dehiscence and male sterility (MS), although COI has not been shown to affect fertility in Zea mays (maize). Here we identified two genes, ZmCOI2a and ZmCOI2b, that redundantly regulate gametophytic male fertility. Both ZmCOI2a and ZmCOI2b are highly homologous and constitutively expressed in all tissues tested. Subcellular localization revealed that ZmCOI2a and ZmCOI2b were located in the nucleus. The coi2a coi2b double mutant, generated by CRISPR/Cas9, had non-dehiscent anthers, delayed anther development and MS. In addition, coi2a coi2b male gametes could not be transmitted to the next generation because of severe defects in pollen germination. The JA content of coi2a coi2b anthers was unaltered compared with those of the wild type, and the exogenous application of JA could not rescue the fertility defects of coi2a coi2b. Transcriptome analysis showed that the expression of genes involving the JA signaling transduction pathway, including ZmJAZ3, ZmJAZ4, ZmJAZ5 and ZmJAZ15, was affected in coi2a coi2b. However, yeast two-hybrid assays showed that ZmJAZs interacted with ZmCOI1s, but not with ZmCOI2s. In conclusion, ZmCOI2a and ZmCOI2b redundantly regulate anther dehiscence and gametophytic male fertility in maize.

Nano-realgar suppresses lung cancer stem cell growth by repressing metabolic reprogramming.

BACKGROUND: Recent studies in cancer biology suggest that metabolic glucose reprogramming is a potential target for cancer treatment. However, little is known about drug intervention in the glucose metabolism of cancer stem cells (CSCs) and its related underlying mechanisms. METHODS: The crude realgar powder was Nano-grinded to meets the requirements of Nano-pharmaceutical preparations, and Nano-realgar solution (NRS) was prepared for subsequent experiments. Isolation and characterization of lung cancer stem cells (LCSCs) was performed by magnetic cell sorting (MACS) and immunocytochemistry, respectively. Cell viability and intracellular glucose concentration were detected by MTT assay and glucose oxidase (GOD) kit. Protein expressions related to metabolic reprogramming was detected by ELISA assay. Determination of the expression of HIF-1α and PI3K/Akt/mTOR pathways was carried out by RT-PCR and western blotting analysis. A subcutaneous tumor model in BALB/c-nu mice was successfully established to evaluate the effects of Nano-realgar on tumor growth and histological structure, and the expression of HIF-1α in tumor tissues was measured by immunofluorescence. RESULTS: Nano-realgar inhibits cell viability and induces glucose metabolism in LCSCs, and inhibits protein expression related to metabolic reprogramming in a time- and dose-dependent manner. Nano-realgar downregulated the expression of HIF-1α and PI3K/Akt/mTOR pathways in vitro and in vivo. Nano-realgar inhibits tumor growth and changes the histological structure of tumors through in vivo experiments and consequently inhibits the constitutive activation of HIF-1α signaling. CONCLUSIONS: These results reveal that Nano-realgar inhibits tumor growth in vitro and in vivo by repressing metabolic reprogramming. This inhibitory effect potentially related to the downregulation HIF-1α expression via PI3K/Akt/mTOR pathway.

A DMP-triggered in vivo maternal haploid induction system in the dicotyledonous Arabidopsis.

Doubled haploid technology using inducer lines carrying mutations in ZmPLA1/MTL/NLD and ZmDMP1-4 has revolutionized traditional maize breeding. ZmPLA1/MTL/NLD is conserved in monocots and has been used to extend the system from maize to other monocots5-7, but no functional orthologue has been identified in dicots, while ZmDMP-like genes exist in both monocots and dicots4,8,9. Here, we report that loss-of-function mutations in the Arabidopsis thaliana ZmDMP-like genes AtDMP8 and AtDMP9 induce maternal haploids, with an average haploid induction rate of 2.1 ± 1.1%. In addition, to facilitate haploid seed identification in dicots, we established an efficient FAST-Red fluorescent marker-based haploid identification system that enables the identification of haploid seeds with >90% accuracy. These results show that mutations in DMP genes also trigger haploid induction in dicots. The conserved expression patterns and amino acid sequences of ZmDMP-like genes in dicots suggest that DMP mutations could be used to develop in vivo haploid induction systems in dicots.

Mutation of ZmDMP enhances haploid induction in maize.

Doubled haploid (DH) breeding based on in vivo haploid induction has led to a new approach for maize breeding1. All modern haploid inducers used in DH breeding are derived from the haploid inducer line Stock6. Two key quantitative trait loci, qhir1 and qhir8, lead to high-frequency haploid induction2. Mutation of the gene MTL/ZmPLA1/NLD in qhir1 could generate a ~2% haploid induction rate (HIR)3-5; nevertheless, this mutation is insufficient for modern haploid inducers whose average HIR is ~10%6. Therefore, cloning of the gene underlying qhir8 is important for illuminating the genetic basis of haploid induction. Here, we present the discovery that mutation of a non-Stock6-originating gene in qhir8, namely, ZmDMP, enhances and triggers haploid induction. ZmDMP was identified by map-based cloning and further verified by CRISPR-Cas9-mediated knockout experiments. A single-nucleotide change in ZmDMP leads to a 2-3-fold increase in the HIR. ZmDMP knockout triggered haploid induction with a HIR of 0.1-0.3% and exhibited a greater ability to increase the HIR by 5-6-fold in the presence of mtl/zmpla1/nld. ZmDMP was highly expressed during the late stage of pollen development and localized to the plasma membrane. These findings provide important approaches for studying the molecular mechanism of haploid induction and improving DH breeding efficiency in maize.

Prognostic Value of MicroRNA-15a in Human Cancers: A Meta-Analysis and Bioinformatics.

BACKGROUND: Although several studies have proved the relationship between the prognostic value of miRNA-15a and different types of cancer, the result remains controversial. Thus, a meta-analysis was conducted to clarify the prognostic value of miRNA-15a expression level in human cancers. METHODS: We enrolled appropriate literature by searching the databases of PubMed, Embase, and Web of Science. Subsequently, we extracted HRs and their 95% CIs and calculated pooled results of miRNA-15a for overall survival (OS) and disease-free survival (DFS). Besides, subgroup analysis, sensitivity analysis, and publication bias were also revealed in this study. We also further validated this meta-analysis using the Kaplan-Meier plotter database. RESULT: 10 studies, including 1616 patients, were embraced in our meta-analysis. The result showed the lower expression of miRNA-15a significantly predicted adverse OS (HR=2.17, 95% CI: 1.41-3.34), but there is no significant association between the expressing level and DFS in cancer patient (HR=2.04, 95% CI: 0.60-6.88). Based on Kaplan-Meier plotter database, we found the same results in bladder Carcinoma, head-neck squamous cell carcinoma, liver hepatocellular carcinoma, lung squamous cell carcinoma, pancreatic ductal adenocarcinoma, rectum adenocarcinoma, stomach adenocarcinoma, and uterine corpus endometrial carcinoma, but opposite results were found in cervical squamous cell carcinoma and esophageal carcinoma. CONCLUSION: Low expressing levels of miRNA-15a indicated poor OS, while miRNA-15a can be used as a prediction biomarker in different cancer types.