Cytosolic isocitrate dehydrogenase regulates plant stem cell maintenance in response to nutrient deficiency.

WUSCHEL (WUS) and WUSCHEL-RELATED HOMEOBOX (WOX) proteins determine stem cell maintenance for continual plant growth and development under changing environmental conditions. Nutrient availability is an environmental factor that substantially controls plant growth and development. However, how plant stem cell homeostasis is regulated under nutrient deficiency remains to be elucidated. Here, we showed that cytosolic isocitrate dehydrogenase (ICDH) plays an important role in nutrient sensing of stem cells in Arabidopsis (Arabidopsis thaliana). Nutrient deficiency induced the cytoplasmic-to-nuclear translocation of cytosolic ICDH protein. ICDH can interact with WUS/WOX protein as a complex that further promotes WUS/WOX expression by binding to its promoter. WUS/WOX expression in the icdh-2 mutant was lower than that of wild-type plants under nutrient deficiency. Consistently, loss of ICDH function caused a more serious growth repression under nutrient deficiency that was independent of ICDH's catalytic activity. Therefore, cytosolic ICDH regulates stem cell homeostasis of plants in response to nutrient deficiency.

Comparative study of the volatile fingerprints of roasted and unroasted oolong tea by sensory profiling and HS-SPME-GC-MS.

Roasting plays important roles in shaping the volatile profile of oolong tea. In this study, the sensory attributes and volatile compositions of 153 roasted or unroasted oolong tea samples, belonging to four typical types, namely, High Mountain oolong tea (HMT), Tieguanyin tea (TGYT), Dongding oolong tea (DDT) and Wuyi rock tea (WRT), were studied in detail. Based on the sensory evaluation by tea evaluation experts, their respective sensory profiles were established and compared. Unroasted teas had more pronounced fresh and green flavors, while roasted teas had higher scores in pungent and caramel flavors. In particular, WRT demonstrated a unique fragrance of floral fruity flavors. By using HS-SPME-GC-MS analysis, a total of 128 compounds were identified across all samples. Notably, it was found that roasting largely increased the variety of volatile compounds in oolong tea. Furthermore, the characteristic volatile compounds of each type of tea were identified by PLS-DA modeling. Linalool and geraniol were the characteristic volatiles of HMT. Four volatiles, including (E)-nerolidol, jasmin lactone, benzeneacetaldehyde, and 4-methyl benzaldehyde oxime were identified as the characteristic volatiles of TGYT. Seven volatiles, including N-ethyl pyrrole, 3-(hydroxy methyl) pyridine, 4-pyridylcarbinol, 1-methyl pyrrole-2-carboxaldehyde, 2-ethyl-3,5-dimethyl pyrazine, 4-amino-2,3-xylenol, and 4,6-dimethyl pyrimidine were the characteristic volatiles of DDT. For WRT, 2,2,6-trimethyl cyclohexan-1-one, hexanoic acid, benzaldehyde, benzyl alcohol, ß-cyclocitral, (E)-ß-ionone, α-ionone, and octanoic acid were the characteristic volatiles. These findings expand our knowledge of the volatile fingerprints of oolong tea.

Evaluation of Volatile Profile and In Vitro Antioxidant Activity of Fermented Green Tea Infusion With Pleurotus sajor-caju (Oyster Mushroom).

Green tea has distinct astringency, bitter taste, and typical green flavor because of its post-harvest treatment without withering and enzymatic oxidation. Microbial fermentation has been identified as a promising strategy that could give green tea infusion a special taste flavor. This might be linked to the metabolic transformation ability of microorganisms. In this study, starter culture of edible mushroom Pleurotus sajor-caju (oyster mushroom) was used for submerged fermentation of green tea infusion in order to improve its flavor and taste quality. The volatile profile determined by headspace solid-phase microextraction, coupled with gas chromatography mass spectrometry, showed that the contents of (Z)-2-penten-1-ol and methyl heptadienone in green tea infusion were decreased significantly by the fermentation with the basidiomycete P. sajor-caju (p < 0.01), which would alleviate the herbal and grass flavor of green tea infusion to a certain extent. Meanwhile, the contents of linalool and geraniol were increased 9.3 and 11.3 times, respectively, whereas methyl salicylate was newly produced after fermentation by P. sajor-caju, endowing the fermented tea infusion with a pleasant flower and fruit aroma. In addition, the polyphenol profile was determined using high-performance liquid chromatography equipped with ion trap mass spectrometry, and the results indicated that the contents of most polyphenols in green tea infusion decreased significantly after fermentation by P. sajor-caju. The reduction of catechins and anthocyanins in fermented green tea infusion alleviated the astringency and bitterness. Moreover, the antioxidant activity of fermented green tea infusion was obviously decreased, especially the DPPH-free radical-scavenging ability and the ferric-reducing power. However, it is noteworthy that the ABTS-free radical scavenging ability was improved compared with the unfermented one, indicating that the increased tea pigments and volatile metabolites (such as linalool and geraniol) after fermentation with P. sajor-caju may also contribute to the antioxidant capacity of fermented green tea infusion. Overall, the innovative approach driven by P. sajor-caju fermentation has achieved promising potential to manipulate the green tea flavor.

Low-Rate DoS Attacks Detection Based on MAF-ADM.

Low-rate denial of service (LDoS) attacks reduce the quality of network service by sending periodical packet bursts to the bottleneck routers. It is difficult to detect by counter-DoS mechanisms due to its stealthy and low average attack traffic behavior. In this paper, we propose an anomaly detection method based on adaptive fusion of multiple features (MAF-ADM) for LDoS attacks. This study is based on the fact that the time-frequency joint distribution of the legitimate transmission control protocol (TCP) traffic would be changed under LDoS attacks. Several statistical metrics of the time-frequency joint distribution are chosen to generate isolation trees, which can simultaneously reflect the anomalies in time domain and frequency domain. Then we calculate anomaly score by fusing the results of all isolation trees according to their ability to isolate samples containing LDoS attacks. Finally, the anomaly score is smoothed by weighted moving average algorithm to avoid errors caused by noise in the network. Experimental results of Network Simulator 2 (NS2), testbed, and public datasets (WIDE2018 and LBNL) demonstrate that this method does detect LDoS attacks effectively with lower false negative rate.