Two Calcium Sensor-Activated Kinases Function in Root Hair Growth.

Plant pollen tubes and root hairs typical polarized tip growth. It is well established that calcium ions (Ca2+) play essential roles in maintaining cell polarity and guiding cell growth orientation. Ca2+ signals are encoded by Ca2+ channels and transporters and are decoded by a variety of Ca2+-binding proteins often called Ca2+ sensors, in which calcineurin B-like protein (CBL) proteins function by interacting with and activating a group of kinases, activate CBL-interacting protein kinases (CIPKs). Some CBL-CIPK complexes, such as CBL2/3-CIPK12/19, act as crucial regulators of pollen tube growth. Whether these calcium decoding components regulate the growth of root hairs, another type of plant cell featuring Ca2+-regulated polarized growth, remains unknown. In this study, we identified CIPK13 and CIPK18 as genes specifically expressed in Arabidopsis (Arabidopsis thaliana) root hairs. The cipk13 cipk18 double mutants showed reduced root hair length and lower growth rates. The calcium oscillations at the root hair tip were attenuated in the cipk13 cipk18 mutants as compared to the wild-type plants. Through yeast two-hybrid screens, CBL2 and CBL3 were identified as interacting with CIPK13 and CIPK18. cbl2 cbl3 displayed a shortened root hair phenotype similar to cipk13 cipk18. This genetic analysis, together with biochemical assays showing activation of CIPK13/18 by CBL2/3, supported the conclusion that CBL2/3 and CIPK13/18 may work as Ca2+-decoding modules in controlling root hair growth. Thus, the findings that CIPK12/19 and CIPK13/18 function in pollen tube and root hair growth, respectively, illustrate a molecular mechanism in which the same CBLs recruit distinct CIPKs in regulating polarized tip growth in different types of plant cells.

A Deep Learning-Based Algorithm for Identifying Precipitation Clouds Using Fengyun-4A Satellite Observation Data.

Rapid and accurate identification of precipitation clouds from satellite observations is essential for the research of quantitative precipitation estimation and precipitation nowcasting. In this study, we proposed a novel Convolutional Neural Network (CNN)-based algorithm for precipitation cloud identification (PCINet) in the daytime, nighttime, and nychthemeron. High spatiotemporal and multi-spectral information from the Fengyun-4A (FY-4A) satellite is utilized as the inputs, and a multi-scale structure and skip connection constraint strategy are presented in the framework of the algorithm to improve the precipitation cloud identification. Moreover, the effectiveness of visible/near-infrared spectral information in improving daytime precipitation cloud identification is explored. To evaluate this algorithm, we compare it with five other deep learning models used for image segmentation and perform qualitative and quantitative analyses of long-time series using data from 2021. In addition, two heavy precipitation events are selected to analyze the spatial distribution of precipitation cloud identification. Statistics and visualization of the experiment results show that the proposed model outperforms the baseline models in this task, and adding visible/near-infrared spectral information in the daytime can effectively improve model performance. More importantly, the proposed model can provide accurate and near-real-time results, which has important application in observing precipitation clouds.

Response of Soil Nematode Community Structure and Function to Monocultures of Pumpkin and Melon.

It is well known that crop monoculture can induce negative effects on soil ecosystems and crop productivity. However, little is known about how vegetable monoculture affects the soil nematode community structure and its relationship with vegetable yields. In this study, the composition, abundance, metabolic footprint, and ecological indices of soil nematodes are investigated in monocultures of pumpkin and melon. The relationships between nematode community structure and yields of pumpkin and melon were analyzed by linear regression. Both monoculture soils of pumpkin and melon suppressed the relative abundance of bacterivores but increased the relative abundance of plant parasites. Pumpkin monoculture soils decreased soil nematode diversity but increased the maturity index of plant parasites. Monoculture soils of pumpkin and melon decreased the metabolic footprint of lower- and higher-level trophic groups of the soil food web, respectively. Pumpkin and melon monoculture soils increased the food web indices channel index (CI) but decreased the enrichment index (EI) and the structure index (SI). The monoculture soils of pumpkin and melon led to a more fungal-dominated decomposition pathway and degraded soil food web conditions. The abundance of bacterivores and food web indices EI and SI were positively correlated with soil nutrients and pH, while the abundance of plant parasites and CI were negatively correlated with soil nutrients and pH. Paratylenchus was negatively correlated with pumpkin and melon yields and could be the potential plant parasites threatening pumpkin and melon productions. Redundancy analysis showed that monocultures of pumpkin and melon altered the soil nematode community via soil properties; total N, total P, alkeline-N, and pH were the main driving factors.

Development and validation of ferroptosis-related lncRNAs signature for hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) with high heterogeneity is one of the most frequent malignant tumors throughout the world. However, there is no research to establish a ferroptosis-related lncRNAs (FRlncRNAs) signature for the patients with HCC. Therefore, this study was designed to establish a novel FRlncRNAs signature to predict the survival of patients with HCC. METHOD: The expression profiles of lncRNAs were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. FRlncRNAs co-expressed with ferroptosis-related genes were utilized to establish a signature. Cox regression was used to construct a novel three FRlncRNAs signature in the TCGA cohort, which was verified in the GEO validation cohort. RESULTS: Three differently expressed FRlncRNAs significantly associated with prognosis of HCC were identified, which composed a novel FRlncRNAs signature. According to the FRlncRNAs signature, the patients with HCC could be divided into low- and high-risk groups. Patients with HCC in the high-risk group displayed shorter overall survival (OS) contrasted with those in the low-risk group (P < 0.001 in TCGA cohort and P = 0.045 in GEO cohort). This signature could serve as a significantly independent predictor in Cox regression (multivariate HR > 1, P < 0.001), which was verified to a certain extent in the GEO cohort (univariate HR > 1, P < 0.05). Meanwhile, it was also a useful tool in predicting survival among each stratum of gender, age, grade, stage, and etiology,etc. This signature was connected with immune cell infiltration (i.e., Macrophage, Myeloid dendritic cell, and Neutrophil cell, etc.) and immune checkpoint blockade targets (PD-1, CTLA-4, and TIM-3). CONCLUSION: The three FRlncRNAs might be potential therapeutic targets for patients, and their signature could be utilized for prognostic prediction in HCC.

Mannose-Modified Liposome Co-Delivery of Human Papillomavirus Type 16 E7 Peptide and CpG Oligodeoxynucleotide Adjuvant Enhances Antitumor Activity Against Established Large TC-1 Grafted Tumors in Mice.

BACKGROUND: Previously, we demonstrated the therapeutic efficacy of a human papillomavirus (HPV) vaccine, including HPV16 E7 peptide and CpG oligodeoxynucleotides (CpG ODN), against small TC-1 grafted tumors. Here, we developed an HPV16 E7 peptide and CpG ODN vaccine delivered using liposomes modified with DC-targeting mannose, Lip E7/CpG, and determined its anti-tumor effects and influence on systemic immune responses and the tumor microenvironment (TME) in a mouse large TC-1 grafted tumor model. METHODS: L-alpha-phosphatidyl choline (SPC), cholesterol (CHOL), 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy (polyethylene glycol-2000)] (DSPE-PEG-2000), 1,2-dioleoyl-3-trimethylammonium-propane chloride salt (DOTAP) and Mannose-PEG-DSPE, loaded with HPV16 E7 peptide and CpG ODN, were used to construct the Lip E7/CpG vaccine. The anti-tumor effects and potential mechanism of Lip E7/CpG were assessed by assays of tumor growth inhibition, immune cells, in vivo cytotoxic T lymphocyte (CTL) responses and cytokines, chemokines, CD31, Ki67 and p53 expression in the TME. In addition, toxicity of Lip E7/CpG to major organs was evaluated. RESULTS: Lip E7/CpG had a diameter of 122.21±8.37 nm and remained stable at 4°C for 7 days. Co-delivery of HPV16 E7 peptide and CpG ODN by liposomes exerted potent anti-tumor effects in large (tumor volume ≥200mm3) TC-1 grafted tumor-bearing mice with inhibition rates of 80% and 78% relative to the control and Free E7/CpG groups, respectively. Vaccination significantly increased numbers of CD4+ and CD8+ T cells, and IFN-γ-producing cells in spleens and tumors and enhanced HPV-specific CTL responses, while reducing numbers of inhibitory cells including myeloid-derived suppressor cells and macrophages. Expression of cytokines and chemokines was altered and formation of tumor blood vessels was reduced in the Lip E7/CpG group, indicating possible modulation of the immunosuppressive TME to promote anti-tumor responses. Lip E7/CpG did not cause morphological changes in major organs. CONCLUSION: Lip E7/CpG induced anti-tumor effects by enhancing cellular immunity and improving tumor-associated immunosuppression. Mannose-modified liposomes are the promising vaccine delivery strategy for cancer immunotherapy.