STM-ac4C: a hybrid model for identification of N4-acetylcytidine (ac4C) in human mRNA based on selective kernel convolution, temporal convolutional network, and multi-head self-attention.

N4-acetylcysteine (ac4C) is a chemical modification in mRNAs that alters the structure and function of mRNA by adding an acetyl group to the N4 position of cytosine. Researchers have shown that ac4C is closely associated with the occurrence and development of various cancers. Therefore, accurate prediction of ac4C modification sites on human mRNA is crucial for revealing its role in diseases and developing new diagnostic and therapeutic strategies. However, existing deep learning models still have limitations in prediction accuracy and generalization ability, which restrict their effectiveness in handling complex biological sequence data. This paper introduces a deep learning-based model, STM-ac4C, for predicting ac4C modification sites on human mRNA. The model combines the advantages of selective kernel convolution, temporal convolutional networks, and multi-head self-attention mechanisms to effectively extract and integrate multi-level features of RNA sequences, thereby achieving high-precision prediction of ac4C sites. On the independent test dataset, STM-ac4C showed improvements of 1.81%, 3.5%, and 0.37% in accuracy, Matthews correlation coefficient, and area under the curve, respectively, compared to the existing state-of-the-art technologies. Moreover, its performance on additional balanced and imbalanced datasets also confirmed the model's robustness and generalization ability. Various experimental results indicate that STM-ac4C outperforms existing methods in predictive performance. In summary, STM-ac4C excels in predicting ac4C modification sites on human mRNA, providing a powerful new tool for a deeper understanding of the biological significance of mRNA modifications and cancer treatment. Additionally, the model reveals key sequence features that influence the prediction of ac4C sites through sequence region impact analysis, offering new perspectives for future research. The source code and experimental data are available at https://github.com/ymy12341/STM-ac4C.

Cooperative Dynamic Motion Planning for Dual Manipulator Arms Based on RRT*Smart-AD Algorithm.

Intelligent manufacturing requires robots to adapt to increasingly complex tasks, and dual-arm cooperative operation can provide a more flexible and effective solution. Motion planning serves as a crucial foundation for dual-arm cooperative operation. The rapidly exploring random tree (RRT) algorithm based on random sampling has been widely used in high-dimensional manipulator path planning due to its probability completeness, handling of high-dimensional problems, scalability, and faster exploration speed compared with other planning methods. As a variant of RRT, the RRT*Smart algorithm introduces asymptotic optimality, improved sampling techniques, and better path optimization. However, existing research does not adequately address the cooperative motion planning requirements for dual manipulator arms in terms of sampling methods, path optimization, and dynamic adaptability. It also cannot handle dual-manipulator collaborative motion planning in dynamic scenarios. Therefore, in this paper, a novel motion planner named RRT*Smart-AD is proposed to ensure that the dual-arm robot satisfies obstacle avoidance constraints and dynamic characteristics in dynamic environments. This planner is capable of generating smooth motion trajectories that comply with differential constraints and physical collision constraints for a dual-arm robot. The proposed method includes several key components. First, a dynamic A* cost function sampling method, combined with an intelligent beacon sampling method, is introduced for sampling. A path-pruning strategy is employed to improve the computational efficiency. Strategies for dynamic region path repair and regrowth are also proposed to enhance adaptability in dynamic scenarios. Additionally, practical constraints such as maximum velocity, maximum acceleration, and collision constraints in robotic arm applications are analyzed. Particle swarm optimization (PSO) is utilized to optimize the motion trajectories by optimizing the parameters of quintic non-uniform rational B-splines (NURBSs). Static and dynamic simulation experiments verified that the RRT*Smart-AD algorithm for cooperative dynamic path planning of dual robotic arms outperformed biased RRT* and RRT*Smart. This method not only holds significant practical engineering significance for obstacle avoidance in dual-arm manipulators in intelligent factories but also provides a theoretical reference value for the path planning of other types of robots.

[Urban thermal environment effects based on visual indices: A case study in Xuzhou City, China]. / 基于视觉指数的城市热环境效应­­ä»¥å¾å·žå¸‚为例.

Urban thermal environments are closely related to habitats, citizens' health, and sustainable development. Based on green view index (GVI), we proposed two new visual indices, construction view index (CVI) and imperious surface view index (R&PVI). Mobile observation was used to obtain urban thermal environment data, images and coordinates synchronously in Xuzhou City in late summer, including urban area (U), scenic area (S), exterior of university campus (E), and university campus inside (CUMT). We analyzed the impacts of the urban composition represented by the visual index on the urban thermal environment. The results showed that, along the sampling line, mean air temperature (Ta) was highest (30.42 ℃) and mean relative humidity (RH) was lowest (40.7%) in urban area, while mean Ta was lowest (29.35 ℃) and mean RH was highest (48.4%) in scenic area. The situation of mean wind-chill temperature (TaW) was the highest (32.95 ℃) in the urban area and the lowest (31.93 ℃) in the scenic area. As for CVI, urban area, university campus inside, exterior of university campus and scenic area ranked in descending order, while GVI showed an opposite pattern. CVI was significantly positively correlated to Ta and TaW, but negatively to RH. GVI was significantly negatively correlated to Ta and TaW, but positively to RH. R&PVI was significantly positively correlated to Ta and TaW, but not correlated to RH. CVI and GVI influenced Ta significantly, with the independent effects being 10.4% and 18.9%, and joint effects being 7.8% and 11.3%, respectively. As for RH, CVI and GVI contributed significantly as well, independent effects were 37.5% and 15.7%, and joint effects were 51.4% and 30.2%, respectively. As for TaW, the three visual indices contributed significantly, but independent and joint effects were lower than those on Ta. Moreover, visual indices contributed more on RH than Ta or TaW. The results could provide ideas for optimizing urban thermal environments and mitigating urban heat island effects, and have practical implications for urban renewal and improvement of the quality of human living environment.

Effects of endurance exercise on serum inflammatory cytokine level and kidney structure in a rat diabetes model.

Diabete mellitus (DM) is becoming a global health problem. Whilst many studies have previously focused on the therapeutic effects of exercise on diabetes, insufficient data exist on its effectiveness on disease prevention. The present study was designed to evaluate the effects of endurance exercises on kidney injury and on the expression of metalloproteinases (MMPs), tissue inhibitors of metalloproteinases (TIMPs) and transforming growth factor (TGF)-ß1. Type 2 diabetic rat model was created followng 8 weeks of feeding on high fat diet, followed by injection with streptozotocin (STZ; 30 mg/kg). A total of three different intensity endurance exercises, including low-intensity exercise (8 m/min and 0˚ slope), moderate-intensity exercise (15 m/min and 5˚ slope) and high-intensity exercise (20 m/min and 10˚ slope), were arranged during this process. Oral glucose tolerance (OGTT) and oral sucrose tolerance tests (OSTT) were performed in all rats 1 week after STZ injection. Serum interleukin-6 and tumor necrosis factor-α levels were measured using ELISA. After OGTT, all rats were sacrificed and kidney samples were removed for hematoxylin and eosin staining and western blot analyzes. Urea and ureatinine levels, representative of renal function, were estimated by using automatic biochemical analyzer. Rats in the DM group showed severe impaired glucose tolerance, which was alleviated in the moderate-intensity exercise (ME) and the high-intensity exercise (HE) groups. Inflammatory cytokines were also significantly reduced rats in the ME group compared with those in the DM group. No difference in renal function, MMP-9/TIMP-1 and TGF-ß1 expression was observed. In addition, rats in the DM group exhibited glomerular enlargement with structural renal abnormalities, whilst those in the ME and HE groups showed improved symptoms. To conclude, no increased expression of inflammatory cytokines and renal fibrotic proteins could be observed in the present rat model of type-2 DM, but evident structural abnormalities can be observed in the kidneys. Medium-intensity endurance exercise can reduce serum inflammatory cytokine levels and prevent aberrant changes in renal structures.

miR-21 targets jnk and ccr7 to modulate the inflammatory response of grass carp following bacterial infection.

Grass carp septicemia is a systemic inflammatory response that develops following a bacterial infection. The hyperinflammatory state develops could lead to septic shock and lethality. There is increasing evidence that microRNAs are involved in the regulation of the inflammatory response. In the present study, miR-21 was confirmed to be involved in the inflammatory response following infection with Aeromonas hydrophila and LPS stimulation. Both jnk and ccr7 were identified as target gene of miR-21 by overexpression, inhibition, and dual luciferase reporter assays experiments. Meanwhile, miR-21 targets the jnk and ccr7 to modulate downstream pro-inflammatory factors tnf-α, il-1ß, il-6, and il-12. Our results provide a theoretical basis for exploring the molecular mechanism of grass carp miR-21 regulating inflammation.