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Music is widely used as an emotion regulation resource, yet music preference is often conceptualized as a stable taste rather than as a context-sensitive processing tendency expressed under affective demand. Drawing on processing fluency and experiential engagement frameworks, the present study examined whether an experiential music preference composite—integrating emotional connectedness and familiarity—modulates the association between anxiety and psychological resilience. Across specifications, the anxiety–resilience association increased as MF_EF increased; this conditional pattern was most evident for state anxiety, whereas the incremental moderating contribution in trait-anxiety models was smaller after accounting for MF_04. These results suggest that emotionally meaningful and familiar music engagement may be better characterized as a conditional experiential resource that becomes salient under transient anxiety, rather than a uniform buffer. These findings refine feature-level accounts of music-based emotion regulation by distinguishing experiential engagement from structural preference processes, while also underscoring the correlational nature of the evidence and the need for longitudinal and cross-cultural validation.

Double helical conformation of polymer chains is widely observed in biomacromolecules and plays an essential role in exerting their biological functions, such as molecular recognition and information storage. It has remained challenging, however, to prepare synthetic helical polymers, and those that exist have mainly been limited to single-stranded polymers or short oligomeric double helices. Here, we report the synthesis of covalent helical polymers, with a high molecular weight, from the achiral monomer hexahydroxytriphenylene through to spiroborate formation. Polymerization and crystallization occurred simultaneously under solvothermal conditions to form single crystals of the resulting helical covalent polymers. Characterization by single-crystal X-ray diffraction showed that each crystal consisted of pairs of mechanically entwined polymers. No strong non-covalent interactions were observed between the two helical polymers that formed a pair; instead, each strand interacted with neighbouring pairs through hydrogen bonding. Each individual crystal was made up of helical polymers of the same handedness, but the crystallization process produced a racemic conglomerate, with equal amounts of right-handed and left-handed crystals.Single crystals of a helical covalent polymer have been obtained from an achiral monomer through spiroborate formation. Polymerization and crystallization occur simultaneously to give a network of pairs of entwined helical strands of the same handedness. No strong non-covalent interactions were observed between the two helical polymers forming a pair; instead, each interacts with neighbouring pairs through hydrogen bonding.

Traditional differential expression genes (DEGs) identification models have limitations in small sample size datasets because they require meeting distribution assumptions, otherwise resulting high false positive/negative rates due to sample variation. In contrast, tabular data model based on deep learning (DL) frameworks do not need to consider the data distribution types and sample variation. However, applying DL to RNA-Seq data is still a challenge due to the lack of proper labeling and the small sample size compared to the number of genes. Data augmentation (DA) extracts data features using different methods and procedures, which can significantly increase complementary pseudo-values from limited data without significant additional cost. Based on this, we combine DA and DL framework-based tabular data model, propose a model TabDEG, to predict DEGs and their up-regulation/down-regulation directions from gene expression data obtained from the Cancer Genome Atlas database. Compared to five counterpart methods, TabDEG has high sensitivity and low misclassification rates. Experiment shows that TabDEG is robust and effective in enhancing data features to facilitate classification of high-dimensional small sample size datasets and validates that TabDEG-predicted DEGs are mapped to important gene ontology terms and pathways associated with cancer.

Alkyne metathesis represents a rapidly emerging synthetic method that has shown great potential in small molecule and polymer synthesis. However, its practical use has been impeded by the limited availability of user-friendly catalysts and their generally high moisture/air sensitivity. Herein, we report an alkyne metathesis catalyst system that can operate under open-air conditions with a broad substrate scope and excellent yields. These catalysts are composed of simple multidentate tris(2-hydroxyphenyl)methane ligands, which can be easily prepared in multi-gram scale. The catalyst substituted with electron withdrawing cyano groups exhibits the highest activity at room temperature with excellent functional group tolerance (-OH, -CHO, -NO 2 , pyridyl). More importantly, the catalyst provides excellent yields (typically >90%) in open air, comparable to those operating under argon. When dispersed in paraffin wax, the active catalyst can be stored on a benchtop under ambient conditions without any decrease in activity for one day (retain 88% after 3 days). This work opens many possibilities for developing highly active user-friendly alkyne metathesis catalysts that can function in open air. Alkyne metathesis catalysts usually suffer from high moisture/air sensitivity, which limit their wide applicability. Here, the authors report efficient alkyne metathesis catalysts that can operate under open-air conditions with a broad functional group tolerance.

Maternally Expressed Gene 3 (MEG3) encodes a lncRNA which is suggested to function as a tumor suppressor. Previous studies suggested that MEG3 functioned through activation of p53, however, the functional properties of MEG3 remain obscure and their relevance to human diseases is under continuous investigation. Here, we try to illuminate the relationship of MEG3 and p53, and the consequence in hepatoma cells. We find that transfection of expression construct of MEG3 enhances stability and transcriptional activity of p53. Deletion analysis of MEG3 confirms that full length and intact structure of MEG3 are critical for it to activate p53-mediated transactivation. Interestingly, our results demonstrate for the first time that MEG3 can interact with p53 DNA binding domain and various p53 target genes are deregulated after overexpression of MEG3 in hepatoma cells. Furthermore, results of qRT-PCR have shown that MEG3 RNA is lost or reduced in the majority of HCC samples compared with adjacent non-tumorous samples. Ectopic expression of MEG3 in hepatoma cells significantly inhibits proliferation and induces apoptosis. In conclusion, our data demonstrates that MEG3 functions as a tumor suppressor in hepatoma cells through interacting with p53 protein to activate p53-mediated transcriptional activity and influence the expression of partial p53 target genes.

Vegetation is the main component of the terrestrial ecosystem and plays a key role in global climate change. Remotely sensed vegetation indices are widely used to detect vegetation trends at large scales. To understand the trends of vegetation cover, this research examined the spatial-temporal trends of global vegetation by employing the normalized difference vegetation index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) time series (1982–2015). Ten samples were selected to test the temporal trend of NDVI, and the results show that in arid and semi-arid regions, NDVI showed a deceasing trend, while it showed a growing trend in other regions. Mann-Kendal (MK) trend test results indicate that 83.37% of NDVI pixels exhibited positive trends and that only 16.63% showed negative trends ( P < 0.05) during the period from 1982 to 2015. The increasing NDVI trends primarily occurred in tree-covered regions because of forest growth and re-growth and also because of vegetation succession after a forest disturbance. The increasing trend of the NDVI in cropland regions was primarily because of the increasing cropland area and the improvement in planting techniques. This research describes the spatial vegetation trends at a global scale over the past 30+ years, especially for different land cover types.

This paper develops an extended Cucker–Smale model that integrates nonlinear velocity alignment with state-dependent binding forces to achieve stable, collision-free flocking in multi-agent systems. Our framework introduces two dedicated control mechanisms: a velocity-dissipative term (K1) for accelerated convergence, and a distance-regulating term (K2) for formation cohesion and collision avoidance, which collectively ensure stable flocking. Rigorous Lyapunov analysis establishes provable guarantees for asymptotic velocity alignment and collision safety under verifiable initial energy conditions. Numerical simulations validate the theoretical predictions for a 20-agent swarm; scalability analysis demonstrates effective coordination in systems of up to 100 agents and reveals that velocity synchronization improves substantially—with errors decreasing by nearly two orders of magnitude—as K2 increases from 0.05 to 0.50. A Pareto-optimal parameter region (K2∈[0.15,0.30]) is identified, which achieves sub-centimeter-per-second alignment accuracy while maintaining energy consumption below 35% of the baseline. The proposed framework provides a theoretically rigorous yet practically viable solution for applications demanding guaranteed safety and precise coordination, such as UAV formations, robotic swarms, and autonomous vehicle platoons.

Taxol-synthesizing enzyme structure The first step in the biosynthesis of the anticancer compound Taxol (paclitaxel) and many other natural C20 diterpenes is the cyclization of an isoprenoid, catalysed by taxadiene synthase. The X-ray crystal structure of this enzyme from the Pacific yew has now been determined. Its C-terminal catalytic domain binds and activates the substrate in a manner seen in class I terpenoid cyclases, but the N-terminal domain and a third 'insertion' domain adopt the fold of a class II terpenoid cyclase. This suggests that this enzyme could be the ancestral progenitor of all terpenoid cyclases. The first X-ray crystal structure of a diterpene cyclase is reported — this enzyme, taxadiene synthase, catalyses the cyclization of an isoprenoid in the first committed step of the biosynthesis of the cancer chemotherapeutic drug Taxol. The C-terminal catalytic domain binds and activates the substrate in a manner seen in class I terpenoid cyclases, but the N-terminal domain and a third 'insertion' domain together adopt the fold of a class II terpenoid cyclase. It is proposed that this enzyme could be the ancestral progenitor of all terpenoid cyclases. With more than 55,000 members identified so far in all forms of life, the family of terpene or terpenoid natural products represents the epitome of molecular biodiversity. A well-known and important member of this family is the polycyclic diterpenoid Taxol (paclitaxel), which promotes tubulin polymerization 1 and shows remarkable efficacy in cancer chemotherapy 2 . The first committed step of Taxol biosynthesis in the Pacific yew ( Taxus brevifolia ) 3 is the cyclization of the linear isoprenoid substrate geranylgeranyl diphosphate (GGPP) to form taxa-4(5),11(12)diene 4 , which is catalysed by taxadiene synthase 5 . The full-length form of this diterpene cyclase contains 862 residues, but a roughly 80-residue amino-terminal transit sequence is cleaved on maturation in plastids 6 . We now report the X-ray crystal structure of a truncation variant lacking the transit sequence and an additional 27 residues at the N terminus, hereafter designated TXS. Specifically, we have determined structures of TXS complexed with 13-aza-13,14-dihydrocopalyl diphosphate (1.82 Å resolution) and 2-fluorogeranylgeranyl diphosphate (2.25 Å resolution). The TXS structure reveals a modular assembly of three α-helical domains. The carboxy-terminal catalytic domain is a class I terpenoid cyclase, which binds and activates substrate GGPP with a three-metal ion cluster. The N-terminal domain and a third ‘insertion’ domain together adopt the fold of a vestigial class II terpenoid cyclase. A class II cyclase activates the isoprenoid substrate by protonation instead of ionization, and the TXS structure reveals a definitive connection between the two distinct cyclase classes in the evolution of terpenoid biosynthesis.

The thermodynamic Cucker–Smale model (TCS model) describes dynamic consistency caused by different temperatures between multi-agent particles. This paper studies the flocking behaviors of the TCS model with multiplicative white noise under hierarchical leadership. First, we introduce the corresponding model of two particles. Then, by using mathematical induction and considering the properties of differential functions, it is proved that, under certain conditions, the group can achieve flocking. Finally, we verify the conclusion through numerical simulation results. Similarly, this paper studies the above model with perturbation functions.

Thousands of long noncoding RNAs (lncRNAs) have been reported in mammalian genomes. These RNAs represent an important subset of pervasive genes involved in a broad range of biological functions. Aberrant expression of lncRNAs is associated with many types of cancers. Here, in order to explore the potential lncRNAs involved in hepatocellular carcinoma (HCC) oncogenesis, we performed lncRNA gene expression profile analysis in 3 pairs of human HCC and adjacent non-tumor (NT) tissues by microarray. Differentially expressed lncRNAs and mRNAs were detected by human lncRNA microarray containing 33,045 lncRNAs and 30,215 coding transcripts. Bioinformatic analyses (gene ontology, pathway and network analysis) were applied for further study of these differentially expressed mRNAs. By qRT-PCR analysis in nineteen pairs of HCC and adjacent normal tissues, we found that eight lncRNAs were aberrantly expressed in HCC compared with adjacent NT tissues, which is consistent with microarray data. We identified 214 lncRNAs and 338 mRNAs abnormally expressed in all three HCC tissues (Fold Change ≥2.0, P<0.05 and FDR <0.05) with the genome-wide lncRNAs and mRNAs expression profile analysis. The lncRNA-mRNA co-expression network was constructed, which may be used for predicting target genes of lncRNAs. Furthermore, we demonstrated for the first time that BC017743, ENST00000395084, NR_026591, NR_015378 and NR_024284 were up-regulated, whereas NR_027151, AK056988 and uc003yqb.1 were down-regulated in nineteen pairs of HCC samples compared with adjacent NT samples. Expression of seven lncRNAs was significantly correlated to their nearby coding genes. In conclusion, our results indicated that the lncRNA expression profile in HCC was significantly changed, and we identified a series of new hepatocarcinoma associated lncRNAs. These results provide important insights about the lncRNAs in HCC pathogenesis.