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Diffuse intrinsic pontine glioma (DIPG), a lethal pediatric cancer driven by H3K27M oncohistones, exhibits aberrant epigenetic regulation and stem-like cell states. Here, we uncover an axis involving H3.3K27M oncohistones, CREB5/ID1, which sustains the stem-like state of DIPG cells, promoting malignancy. We demonstrate that CREB5 mediates elevated ID1 levels in the H3.3K27M/ACVR1WT subtype, promoting tumor growth; while BMP signaling regulates this process in the H3.1K27M/ACVR1MUT subtype. Furthermore, we reveal that H3.3K27M directly enhances CREB5 expression by reshaping the H3K27me3 landscape at the CREB5 locus, particularly at super-enhancer regions. Additionally, we elucidate the collaboration between CREB5 and BRG1, the SWI/SNF chromatin remodeling complex catalytic subunit, in driving oncogenic transcriptional changes in H3.3K27M DIPG. Intriguingly, disrupting CREB5 super-enhancers with ABBV-075 significantly reduces its expression and inhibits H3.3K27M DIPG tumor growth. Combined treatment with ABBV-075 and a BRG1 inhibitor presents a promising therapeutic strategy for clinical translation in H3.3K27M DIPG treatment. Diffuse intrinsic pontine glioma (DIPG) is driven by H3K27M oncohistones, but the exact related mechanisms are poorly understood. Here, the authors identify an H3.3K27M oncohistone-driven CREB5/ID1 axis that promotes transcriptional changes and progression in DIPG, which could represent a potential therapeutic target.

The stability control of vehicle movement directly affects the safety and reliability of autonomous vehicles. When a vehicle is in extreme conditions, it is easy to lose stability and lead to accidents. Based on the drift control of racing vehicles under extreme conditions, this paper studies the emergency rescue control strategy for autonomous driving vehicles under extreme conditions. An algorithm similar to the drift control ability of racing drivers is designed. By predicting the vehicle’s driving trajectory and combining automatic steering, clutch, and throttle technologies, the vehicle’s active drift control is realized, so that ordinary vehicles can also have the “abnormal drift obstacle avoidance” control effect in corners like professional racing drivers. Even under extreme conditions such as snowy or icy roads, the vehicle can autonomously adjust its body posture and motion state, effectively improving the safety and reliability of autonomous vehicles and ensuring stable operation under challenging driving conditions.

Under the background of global climate change, rainstorm and flood disasters have become the most serious cataclysm. Under the circumstances of an increasingly severe risk situation, it is necessary to enhance urban disaster resilience. Based on the disaster resilience process of prevention, absorption, and enhancement, and considering the safety factors such as personnel, facility, environment and management, this paper forms a dual dimension of the urban disaster resilience assessment model covering the key elements of urban disaster response and the core capacity of urban disaster recovery. Furthermore, if taking into account the characteristics of rainstorm and flood disasters, the paper screens the key indicators to build up an assessment index system of an urban rainstorm and flood disaster. The practical application was implemented in Beijing to have an assessment of the ability to recover from rainstorm and flood disasters in all districts of Beijing. And then, some pertinent suggestions for enhancing the resilience of Beijing to rainstorm and flood disasters were proposed.

Malaria parasites depend on an inner membrane complex (IMC) and subpellicular microtubules (SPMTs) to maintain their shape, motility, and ability to replicate. This study demonstrates that knocking out or disrupting the PbIMC1j protein adversely affects asexual stage fitness, virulence, and the morphology of ookinetes, while also decreasing the motility of ookinetes in P. berghei . Furthermore, PbIMC1j interacts and stabilizes the proteins ISC1 and δ-tubulin, underscoring its role in regulating the IMC and SPMTs.

Sepiella japonica is a worldwide marine cuttlefish species of high economic value. S. japonica routinely modifying behaviors in reproductive life, such as rapid aging until death after spawning, has been recognized in artificial breeding. However, reproductive behavior at the level of genes is rarely reported, thus, the research on the genetic basis of behavior, reproduction, and artificial breeding was limited. We applied RNA-seq in different stages of reproduction to investigate the reason of rapid aging after spawning, pre-maturity, pre-spawning after maturity, and post-spawning. The retinoid X receptor ( RXR ) gene family in S. japonica was identified, and 1 343–1 452 differentially expressed genes (DEGs) in all 3 stages of reproductive life were identified from pairwise mRNA comparisons. Furthermore, through the GO term and KEGG analysis, S. japonica could handle neuronal development and network formation before maturity and have a functional degradation of neural communication, signal transduction, vision, and gene expression after spawning. Eight SjRXRαs have been identified and they played different roles in growth development or reproduction. Therefore, the regulation of several channels and receptors is the intrinsic molecular mechanism of rapid aging after spawning in S. japonica . This study revealed the survival strategy and provided fundamental data on the level of genes for understanding the reproductive behavior and the reproduction of S. japonica .

Aiming at the lack of a comprehensive evaluation of the distribution network, based on the existing distribution network evaluation index system, combined with the basic principles of constructing the evaluation index, put forward a new evaluation index system of distribution network capacity. This paper is mainly based on the total supply capability of the distribution network, combining single index and various factors, into a multi-evaluation index of the distribution network, thus forming a reasonable index system, and various indicators of rational quantification make the evaluation results more intuitive. In order to have a comprehensive judgment of distribution network, this paper uses weights to analyse the importance of each index, verify the rationality of the index system through the example, it is proved that the rationality of the index system, so as to guide the direction of distribution network planning.

In light of the success of contrastive learning in the image domain, current self-supervised video representation learning methods usually employ contrastive loss to facilitate video representation learning. When naively pulling two augmented views of a video closer, the model however tends to learn the common static background as a shortcut but fails to capture the motion information, a phenomenon dubbed as background bias. Such bias makes the model suffer from weak generalization ability, leading to worse performance on downstream tasks such as action recognition. To alleviate such bias, we propose \\textbf{F}oreground-b\\textbf{a}ckground \\textbf{Me}rging (FAME) to deliberately compose the moving foreground region of the selected video onto the static background of others. Specifically, without any off-the-shelf detector, we extract the moving foreground out of background regions via the frame difference and color statistics, and shuffle the background regions among the videos. By leveraging the semantic consistency between the original clips and the fused ones, the model focuses more on the motion patterns and is debiased from the background shortcut. Extensive experiments demonstrate that FAME can effectively resist background cheating and thus achieve the state-of-the-art performance on downstream tasks across UCF101, HMDB51, and Diving48 datasets. The code and configurations are released at https://github.com/Mark12Ding/FAME.