Ferroptosis is a newly found non-apoptotic forms of cell death that plays an important role in tumors. However, the prognostic value of ferroptosis-related genes (FRG) in bladder cancer (BLCA) have ...not been well examined.
FRG data and clinical information were collected from The Cancer Genome Atlas (TCGA). Then, significantly different FRGs were investigated by functional enrichment analyses. The prognostic FRG signature was identified by univariate cox regression and least absolute shrinkage and selection operator (LASSO) analysis, which was validated in TCGA cohort and Gene Expression Omnibus (GEO) cohort. Subsequently, the nomogram integrating risk scores and clinical parameters were established and evaluated. Additionally, Gene Set Enrichment Analyses (GSEA) was performed to explore the potential molecular mechanisms underlying our prognostic FRG signature. Finally, the expression of three key FRGs was verified in clinical specimens.
Thirty-two significantly different FRGs were identified from TCGA-BLCA cohort. Enrichment analyses showed that these genes were mainly related to the ferroptosis. Seven genes (TFRC, G6PD, SLC38A1, ZEB1, SCD, SRC, and PRDX6) were then identified to develop a prognostic signature. The Kaplan-Meier analysis confirmed the predictive value of the signature for overall survival (OS) in both TCGA and GEO cohort. A nomogram integrating age and risk scores was established and demonstrated high predictive accuracy, which was validated through calibration curves and receiver operating characteristic (ROC) curve area under the curve (AUC) = 0.690. GSEA showed that molecular alteration in the high- or low-risk group was closely associated with ferroptosis. Finally, experimental results confirmed the expression of SCD, SRC, and PRDX6 in BLCA.
Herein, we identified a novel FRG prognostic signature that maybe involved in BLCA. It showed high values in predicting OS, and targeting these FRGs may be an alternative for BLCA treatment. Further experimental studies are warranted to uncover the mechanisms that these FRGs mediate BLCA progression.
In order to meet the obstacle avoidance requirements of unmanned agricultural machinery in operation, it is necessary to plan a path to avoid obstacles in real time after obstacles are detected. ...However, the traditional path planning algorithm does not consider kinematic constraints, which makes it difficult to realize the plan, thus affecting the performance of the path tracking controller. In this paper, a real-time path planning algorithm based on particle swarm optimization for an agricultural machinery parametric kinematic model is proposed. The algorithm considers the agricultural machinery kinematic model, defines the path satisfying the kinematic model through a parametric equation, and solves the initial path through the analytic method. Then, considering the constraints of obstacles, acceleration, and turning angle, two objective functions are proposed. The particle swarm optimization algorithm is used to search the path near the initial path which satisfies the obstacle avoidance condition and has a better objective function value. In addition, the influence of the algorithm parameters on the running time is analyzed, and the method of compensating the radius of the obstacle is proposed to compensate the influence of the discrete time on the obstacle collision detection. Finally, experimental results show that the algorithm can plan a path in real time that avoids any moving obstacles and has a better objective function value.
In the domain of data enhancement, image restoration and data augmentation are two tasks gaining increasing attention. Current image restoration models focus on improving clarity using pre-trained ...generative models, and data augmentation methods try to generate new samples with the help of generative models. These two related topics have long been studied completely separately. We propose a downstream-friendly restoration framework based on pre-trained generative models with the capability of data augmentation for face images. We carefully design our framework to achieve high fidelity when inheriting the generation ability from the pre-trained generator. To achieve this goal, we use a modified U-Net to predict the biases of latent codes and feature maps to guide the generator. We further propose to adopt linear interpolation as an approach to enriching the datasets for downstream tasks, especially for class-imbalanced tasks. Effectiveness of our method is demonstrated through experiments on three datasets and one downstream task.
Cervical cancer is one of the most common gynecological malignancies with poor prognosis due to constant chemoresistance and repeated relapse. Ciclopirox olamine (CPX), a synthetic antifungal agent, ...has recently been identified to be a promising anti-cancer candidate. However, the detailed mechanisms related to its anti-cancer effects remain unclear and need to be further elucidated. In this study, we found that CPX could induce proliferation inhibition in cervical cancer cells by targeting PARK7. Further results demonstrated that CPX could induce cytoprotective autophagy by downregulating the expression of PARK7 to activate PRKAA1 or by PARK7-independent accumulation of ROS to inhibit mTOR signaling. Meanwhile, CPX treatment increased the glycogen clustering and glycophagy in cervical cancer cells. The presence of N-acetyl-l-cysteine (NAC), a ROS scavenger, led to further clustering of glycogen in cells by reducing autophagy and enhancing glycophagy, which promoted CPX-induced inhibition of cervical cancer cell proliferation. Together, our study provides new insights into the molecular mechanisms of CPX in the anti-cancer therapy and opens new avenues for the glycophagy in cancer therapeutics.
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•CPX induces cytoprotective autophagy and inhibits proliferation of cervical cancer cells by targeting PARK7.•ROS generation attenuates the anticancer effect of CPX by inducing cytoprotective autophagy and inhibiting glycophagy.•ROS-triggered glycogen clustering and inactivation of YAP1 are involved in the anti-cancer effects of CPX.
Green residences have enormous potential for energy savings, emission reduction, and other comprehensive benefits, and their growth is crucial to achieving China’s carbon neutrality and carbon ...peaking targets. Nevertheless, at the moment, the national green residence is impacted by complicated factors at several levels, including government agencies, green residence builders, and green residence consumers, which results in the low-quality development of domestic green residences overall. As of 2020, 94% of all labeled green residences are design-label residences that can only be achieved during the design stage, while less than 10% are operational-label residences with stronger energy and emission-saving benefits. This causes the phenomenon of “green residences on the planning” to be serious. In order to accomplish the promotion of high-quality development of green residences and to promote green residences in China, this paper analyzes the influencing factors of green residence promotion from the multi-level perspective of macro-landscape signals, meso-collective agent green residences, and micro-individual agent consumers, based on the multi-level perspective (MLP) framework of sustainability theory. The paper subsequently builds a simulation model of green residence promotion using the agent-based system dynamics modeling method. Additionally, Jiangsu Province’s green residence promotion data are chosen for analogue simulation experiments, and the simulation results are also used to analyze the success conditions as well as the path to green residence promotion. This study demonstrates that (1) the agent-based simulation model of dynamics for the green residence promotion system has high reference value for the simulation of the promotion of green residences, and the model can clearly simulate the impact of micro-individual agent–consumer factors on the promotion of green residences; (2) in order to promote green residences, exterior landscape signals must be continuously improved; the stronger the landscape signals, the quicker the development of operationally labeled green residences; (3) priority is given to the development of two-star design-labeled green residences before 2035, and three-star operationally labeled residences will occupy the majority of the market after 2040. Meanwhile, the duration of landscape signals and the change in behavioral preferences of individual agents must be maintained for a long time.
Prostate cancer (PC) is one of the most common malignancies in males. Extensive and complex connections between circadian rhythm and cancer were found. Nonetheless, in PC, the potential role of the ...core components of the mammalian circadian clock (CCMCCs) in prognosis prediction has not been fully clarified.
We firstly collected 605 patients with PC from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Survival analysis was carried out for each CCMCC. Then, we investigated the prognostic ability of CCMCCs by Cox regression analysis. Independent prognostic signatures were extracted for the establishment of the circadian clock-based risk score model. We explored the predictive performance of the risk score model in the TCGA training cohort and the independent GEO dataset. Finally, the relationships between risk score and clinicopathological parameters, biological processes, and signaling pathways were evaluated.
The expression levels of CCMCCs were widely correlated with age, tumor status, lymph node status, disease-free survival (DFS), progression-free survival (PFS), and overall survival (OS). Nine circadian clock genes, including CSNK1D, BTRC, CLOCK, CSNK1E, FBXL3, PRKAA2, DBP, NR1D2, and RORB, were identified as vital prognostic factors in PC and were used to construct the circadian clock-based risk score model. For DFS, the area under the 3-year or 5-year receiver operating characteristic curves ranged from 0.728 to 0.821, suggesting better predictive performance. When compared with T3-4N1 stage, PC patients at T2N0 stage might be benefited more from the circadian clock-based risk score model. Furthermore, a high circadian clock-based risk score indicated shorter DFS (
< 0.0001), early progression (
< 0.0001), and higher 5-year death rate (
= 0.007) in PC. The risk score was related to tumor status (
< 0.001), lymph node status (
< 0.001), and ribosome-related biogenesis and pathways.
The vital roles of circadian clock genes in clinical outcomes were fully depicted. The circadian clock-based risk score model could reflect and predict the prognosis of patients with PC.
As our understanding of diseases deepens, increasing therapeutic targets are being identified, which facilitates the development of new drug candidates. However, drug screening remains to be ...challenging due to complicated processes, long development cycles, and a low success rate. Fluorescence-based techniques have drawn growing attention from scientists, gradually becoming one of the most commonly employed methods for screening potential drugs and assessing their efficacy. Among them, fluorogens with aggregation-induced emission (AIE) characteristics offer distinct advantages in drug screening applications. In this review, we highlight recent advances of employing AIE fluorogens in drug screening. Selected examples include their applications in screening inhibitors and agonists, monitoring the therapeutic effect of potential drugs, high-throughput screening of potential drugs, and fabrication of sensor array and miniaturized sample holder for drug screening. Through these examples, we aim to disseminate innovative ideas and inspire new researchers in this area, contributing to the ongoing development of drug discovery.
•The design principles for constructing AIE-based biological fluorescent probes are presented.•Recent advances on employing AIE-active probes for screening drugs are reviewed.•Future development directions of AIE materials in drug screening are presented and discussed.
The high cost of centralized photovoltaic power generation projects is an important problem affecting industrial development, which needs to be solved urgently. It is particularly important to ...explore the influencing factors of cost control and the interaction between them. This paper takes a centralized photovoltaic power generation project as the research object, and determines the index system of influencing factors of cost control from the perspective of the life cycle. Secondly, the logical relationship between influencing factors is judged by the method of combining DEMATEL (decision-making trial and evaluation laboratory) and ISM (interpretive structural modelling). Finally, the multi-order recursive interpretation structure model is obtained, and the action mechanism between various factors is obtained. The results show that national policies and standards are the most profound influencing factors, and their cause degree reaches 2.155; the reason degree of market changes is the second, which is 1.586; bidding and contract management are the factors with the highest centrality, which is 7.120; and transmission and the storage of electricity and equipment repair and maintenance are the most direct factors affecting cost control. Finally, some suggestions are put forward for different types of influencing factors. The research results can better help photovoltaic power generation enterprises solve the problem of cost control.
Combustibles, topography, and weather factors are the three essential factors affecting forest fire behavior, and current forest fire spread models need to consider weather factors fully. This paper ...proposes a forest fire spread method based on environmental weather factors to present a visualized simulation of forest fire spread in the natural environment. Forest pyrolysis differs based on water content, so a single-tree pyrolysis model with temperature as its core has been constructed to describe the differences in forest pyrolysis during different seasons visually. In addition, based on the improved Huygens principle as the theoretical basis for forest fire spread, weather factors such as wind speed, wind direction, and precipitation controlled by weather are coupled with the forest fire spread process. And the forest fire spread in three-dimensional scenarios is simulated by considering environmental factors. The visualization of the forest fire extinguishing process caused by precipitation is realized. Finally, the interaction between rain and snow, terrain and trees is realized when precipitation affects the corresponding landscape and vegetation texture to enhance the realism of the constructed forest environment. In short, this paper proposes a forest fire spread method based on environmental weather factors, which intuitively expresses the influence of different weather factors on forest fire spread, thereby improving the immersive experience of the related senses and realizing realistic scene roaming.
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•Based on the single tree pyrolysis model, differentiating forest burning.•Visualization of the influence of simulated weather factors on forest fire behavior.•Use texture mixing technology to construct 3D forest weather scene.
State-of-the-art approaches to forest fire spread are based on either 2D numerical simulations of trees on GIS or rough 3D visualization. In this paper, we approximate the tree form by dynamically ...changing sets of tree-shape modules according to the morphological structure and wind fields. Guided by finite state machine, we define the states of equilibrium, heating, pyrolysis, cooling and destruction of tree-shape modules. Interactions between tree-shape modules drive the state transfer to achieve forest fire spread. Additionally, Loose Quadtrees are adopted to the spatial distribution of trees, which allows us to maintain the visual fidelity of the representation while rendering the forest fire spreads in real-time. Our method allows us to construct the Jiufeng forest example about 10km x 10km extent at interactive rates. The capabilities of tree-shape modules and forest fire spread visualization are demonstrated by numerous examples.
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•Use FSM to define the state and transition rules of the tree-shape module, and adopt the state to drive the temperature, moisture, and mass of the tree to simulate the pyrolysis.•Use Loose Quadtree to generate tree-shape modules in real time, and tree-shape modules can be deformed by the joint action of wind field and terrain slope to control the spread of forest fire.•Calculate the barycentric coordinates of a triangle in a tree surface mesh as the position of preset flame and store in the Priority Queue to orderly generate flames on trees.
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