Potential of Trap Crops for Integrated Management of the Tropical Armyworm, Spodoptera litura in Tobacco

The tropical armyworm, Spodoptera litura (F.) (Lepidoptera: Noctuidae), is an important pest of tobacco, Nicotiana tabacum L. (Solanales: Solanaceae), in South China that is becoming increasingly resistant to pesticides. Six potential trap crops were evaluated to control S. litura on tobacco. Castor bean, Ricinus communis L. (Malpighiales: Euphorbiaceae), and taro, Colocasia esculenta (L.) Schott (Alismatales: Araceae), hosted significantly more S. litura than peanut, Arachis hypogaea L. (Fabales: Fabaceae), sweet potato, Ipomoea batata Lam. (Solanales: Convolvulaceae) or tobacoo in a greenhouse trial, and tobacco field plots with taro rows hosted significantly fewer S. litura than those with rows of other trap crops or without trap crops, provided the taro was in a fast-growing stage. When these crops were grown along with eggplant, Solanum melongena L. (Solanales: Solanaceae), and soybean, Glycines max L. (Fabales: Fabaceae), in separate plots in a randomized matrix, tobacco plots hosted more S. litura than the other crop plots early in the season, but late in the season, taro plots hosted significantly more S. litura than tobacco, soybean, sweet potato, peanut or eggplant plots. In addition, higher rates of S. litura parasitism by Microplitis prodeniae Rao and Chandry (Hymenoptera: Bracondidae) and Campoletis chlorideae Uchida (Ichnumonidae) were observed in taro plots compared to other crop plots. Although taro was an effective trap crop for managing S. litura on tobacco, it did not attract S. litura in the seedling stage, indicating that taro should either be planted 20–30 days before tobacco, or alternative control methods should be employed during the seedling stage

A novel prognostic 7-methylguanosine signature reflects immune microenvironment and alternative splicing in glioma based on multi-omics analysis

Glioma is the most common type of central nervous system tumor with increasing incidence. 7-methylguanosine (m7G) is one of the diverse RNA modifications that is known to regulate RNA metabolism and its dysregulation was associated with various cancers. However, the expression pattern of m7G regulators and their roles in regulating tumor immune microenvironments (TIMEs) as well as alternative splicing events (ASEs) in glioma has not been reported. In this study, we showed that m7G regulators displayed a close correlation with each other and most of them were differentially expressed between normal and glioma tissues. Two m7G signatures were then constructed to predict the overall survival of both GBM and LGG patients with moderate predictive performance. The risk score calculated from the regression coefficient and expression level of signature genes was proved to be an independent prognostic factor for patients with LGG, thus, a nomogram was established on the risk score and other independent clinical parameters to predict the survival probability of LGG patients. We also investigated the correlation of m7G signatures with TIMEs in terms of immune scores, expression levels of HLA and immune checkpoint genes, immune cell composition, and immune-related functions. While exploring the correlation between signature genes and the ASEs in glioma, we found that EIF4E1B was a key regulator and might play dual roles depending on glioma grade. By incorporating spatial transcriptomic data, we found a cluster of cells featured by high expression of PTN exhibited the highest m7G score and may communicate with adjacent cancer cells via SPP1 and PTN signaling pathways. In conclusion, our work brought novel insights into the roles of m7G modification in TIMEs and ASEs in glioma, suggesting that evaluation of m7G in glioma could predict prognosis. Moreover, our data suggested that blocking SPP1 and PTN pathways might be a strategy for combating glioma

Promotive role of IRF7 in ferroptosis of colonic epithelial cells in ulcerative colitis by the miR-375-3p/SLC11A2 axis

Ferroptosis is implicated in the progression of ulcerative colitis (UC), and interferon regulatory factor 7 (IRF7) contributes to cell death. This study probed the mechanism of IRF7 in ferroptosis of colonic epithelial cells (ECs) in mice with dextran sodium sulfate (DSS)-induced UC. The UC mouse model and the in vitro ferroptosis model were respectively established by DSS feeding and the treatment with FIN56 (a ferroptosis inducer). Results of quantitative real-time polymerase chain reaction and western blotting revealed the upregulation of IRF7 and solute carrier family 11 member 2 (SLC11A2/NRAMP2/DMT1) and the downregulation of microRNA (miR)-375-3p in DSS-treated mice and FIN56-treated ECs. Silencing of IRF7 improved the symptoms of UC in DSS-induced mice and decreased the levels of tumor necrosis factor α, interleukin 6, monocyte chemoattractant protein 1, and interleukin 1β, reactive oxygen species, iron ions, lipid peroxidation, and increased glutathione and glutathione peroxidase 4. Chromatin immunoprecipitation and dual-luciferase assays showed that binding of IRF7 to the miR-375-3p promoter inhibited miR-375-3p expression, and miR-375-3p suppressed SLC11A2 transcription. The rescue experiments revealed that knockdown of miR-375-3p neutralized the role of silencing IRF7 in alleviating ferroptosis of colonic ECs. Overall, IRF7 upregulated SLC11A2 transcription by inhibiting miR-375-3p expression, thereby prompting ferroptosis of colonic ECs and UC progression in DSS-treated mice

Event-Triggered Multi-Lane Fusion Control for 2-D Vehicle Platoon Systems with Distance Constraints

This paper investigates the event-triggered fixedtime multi-lane fusion control for vehicle platoon systems with distance keeping constraints where the vehicles are spread in multiple lanes. To realize the fusion of vehicles in different lanes, the vehicle platoon systems are firstly constructed with respect to a two-dimensional (2-D) plane. In case of the collision and loss of effective communication, the distance constraints for each vehicle are guaranteed by a barrier function-based control strategy. In contrast to the existing results regarding the command filter techniques, the proposed distance keeping controller can constrain the distance tracking error directly and the error generated by the command filter is coped with by adaptive fuzzy control technique. Moreover, to offset the impacts of the unknown system dynamics and the external disturbances, an unknown input reconstruction method with asymptotic convergence is developed by utilizing the interval observer technique. Finally, two relative threshold triggering mechanisms are utilized in the proposed fixed-time multi-lane fusion controller design so as to reduce the communication burden. The corresponding simulation results also verify the effectiveness of the proposed strategy

A Study of Unsupervised Evaluation Metrics for Practical and Automatic Domain Adaptation

Unsupervised domain adaptation (UDA) methods facilitate the transfer of models to target domains without labels. However, these methods necessitate a labeled target validation set for hyper-parameter tuning and model selection. In this paper, we aim to find an evaluation metric capable of assessing the quality of a transferred model without access to target validation labels. We begin with the metric based on mutual information of the model prediction. Through empirical analysis, we identify three prevalent issues with this metric: 1) It does not account for the source structure. 2) It can be easily attacked. 3) It fails to detect negative transfer caused by the over-alignment of source and target features. To address the first two issues, we incorporate source accuracy into the metric and employ a new MLP classifier that is held out during training, significantly improving the result. To tackle the final issue, we integrate this enhanced metric with data augmentation, resulting in a novel unsupervised UDA metric called the Augmentation Consistency Metric (ACM). Additionally, we empirically demonstrate the shortcomings of previous experiment settings and conduct large-scale experiments to validate the effectiveness of our proposed metric. Furthermore, we employ our metric to automatically search for the optimal hyper-parameter set, achieving superior performance compared to manually tuned sets across four common benchmarks. Codes will be available soon

Enhanced Fireworks Algorithm-Auto Disturbance Rejection Control Algorithm for Robot Fish Path Tracking

The robot fish is affected by many unknown internal and external interference factors when it performs path tracking in unknown waters. It was proposed that a path tracking method based on the EFWA-ADRC (enhanced fireworks algorithmauto disturbance rejection control) to obtain high-quality tracking effect. ADRC has strong adaptability and robustness. It is an effective method to solve the control problems of nonlinearity, uncertainty, strong interference, strong coupling and large time lag. For the optimization of parameters in ADRC, the enhanced fireworks algorithm (EFWA) is used for online adjustment. It is to improve the anti-interference of the robot fish in the path tracking process. The multi-joint bionic robot fish was taken as the research object in the paper. It was established a path tracking error model in the Serret-Frenet coordinate system combining the mathematical model of robotic fish. It was focused on the forward speed and steering speed control rate. It was constructed that the EFWA-ADRC based path tracking system. Finally, the simulation and experimental results show that the control method based on EFWAADRC and conventional ADRC makes the robotic fish track the given path at 2:8s and 3:3s respectively, and the tracking error is kept within plus or minus 0:09m and 0:1m respectively. The new control method tracking steady-state error was reduces by 10% compared with the conventional ADRC. It was proved that the proposed EFWA-ADRC controller has better control effect on the controlled system, which is subject to strong interference

Effect of sample selection on the susceptibility assessment of geological hazards: A case study in Liulin County, Shanxi Province

The rational selection of non-geological hazard samples is of great significance to improve the accuracy of geological hazard susceptibility prediction. This study uses Liulin County as a case study, where appropriate impact factors were selected, and the random forest (RF) model was employed for susceptibility assessment based on GIS technology. A total of twenty sets of models were created by varying the ratio of geological hazard to non-geological hazard points (1∶1, 1∶1.5, 1∶3, 1∶5 and 1∶10) and the distance from non-geological hazard points to known hazard points (100,500,800,1000 m). The results demonstrate that: (1) Through error index, confusion matrix, and ROC curve tests, the sample proportion and distance from the known hazard point significantly influenced the geological hazard susceptibility evaluation. As the sample proportion decreased and the distance from known hazard points increased, the overall MAE and RMSE of the models decreased, while the overall ACC increased. All models achieved AUC value greater than 0.8, indicating excellent predictive performance. When the sample proportion was less than 1∶3, the increasing distance from the known hazard points on model error and accuracy became less pronounced, stabilizing the results. The most suitable model for the study area was found to have a sample ratio of 1∶10 and a distance of 1000 m from known hazard points. (2) High and very high susceptibility areas were primarily located in the central and northern regions, adjacent to roads and rivers, making them key areas for hazard prevention and reduction in Liulin County. (3) Differences in sample selection led to varying susceptibility results mainly due to changes in the RF model's data feature collection and judgment during the modeling process, as well as the representativeness of the samples. These research findings hold significant implications for the implementation of hazard prevention and reduction measures

Circulating soluble suppression of tumorigenicity-2 and the recurrence of atrial fibrillation after catheter ablation: A meta-analysis

Soluble suppression of tumorigenicity-2 (sST-2), a marker of myocardial fibrosis and remodeling, has been related to the development of atrial fibrillation (AF). The aim of this meta-analysis was to evaluate the relationship between baseline serum sST-2 levels and the risk of AF recurrence after ablation. Relevant observational studies were retrieved from PubMed, Web of Science, Embase, Wanfang and China National Knowledge Infrastructure (CNKI). A random-effects model was used to combine the data, accounting for between-study heterogeneity. Fourteen prospective cohorts were included. Pooled results showed higher sST-2 levels before ablation in patients with AF recurrence compared to those without AF recurrence (standardized mean difference = 1.15, 95% confidence interval [CI] = 0.67 to 1.63, P < 0.001; I2 = 92%). Meta-regression analysis suggested that the proportion of patients with paroxysmal AF (PaAF) was positively related to the difference in serum sST-2 levels between patients with and without AF recurrence (coefficient = 0.033, P < 0.001). Subgroup analysis showed a more remarkable difference in serum sST-2 levels between patients with and without AF recurrence in studies where PaAF was ≥ 60% compared to those where it was < 60% (P = 0.007). Further analyses showed that high sST-2 levels before ablation were associated with an increased risk of AF recurrence (odds ratio [OR] per 1 ng/mL increment of sST-2 =1.05, OR for high versus low sST-2 = 1.73, both P values < 0.05). In conclusion, high sST-2 baseline levels may be associated with an increased risk of AF recurrence after catheter ablation