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Abstract Background Nonsuicidal self-injury (NSSI) is a serious problem in the adolescent population worldwide. Childhood trauma and bullying have been identified as risk factors for NSSI. We explored the relationships among Childhood trauma, Bullying victimization and the severity of NSSI behaviours, and test the effect of Bullying victimization in mediating the association between Childhood trauma and the NSSI behaviours. Methods A total of 123 adolescents were recruited. They were diagnosed with depression or depressive episodes of bipolar disorder and had experienced NSSI in the last year. They were assessed using the Chinese version of the Childhood Trauma Questionnaire (CTQ-C), the Revised Olweus Bullying Victimization Questionnaire (OBVQ-R), and the Adolescent Self-Harm Questionnaire (ASHQ). Results Females presented a significantly greater prevalence of sexual abuse and relationship bullying than boys. Individuals in the younger age group (10–14 years) presented a greater incidence of emotional neglect, verbal bullying, relationship bullying, and total bullying, and their NSSI score was also higher than that of those in the older age group (15–19 years). Only children show a greater prevalence of sexual abuse than nononly children. Single-parent families scored higher on emotional abuse, emotional neglect, physical neglect and physical bullying than two-parent families. There was a significant positive correlation between each dimension of childhood trauma and all the dimensions of bullying, between childhood trauma and NSSI, and between bullying and NSSI. Childhood trauma can not only directly affect the severity of NSSI but also indirectly aggravate the severity of NSSI through bullying victimization. The mediating effects of bullying victimization on emotional abuse, physical abuse, emotional neglect and physical neglect were 14%, 21%, 20%, 13% and 20%, respectively. Conclusion There was a significant positive correlation between childhood trauma and bullying, between childhood trauma and NSSI, and between bullying and NSSI. Childhood trauma can not only directly affect the severity of NSSI but also indirectly aggravate the severity of NSSI through bullying victimization. Bullying victimization played the partial mediating effects between Childhood trauma and NSSI.

Abstract Background Acute lung injury (ALI) is a devastating clinical disorder with a high mortality rate, and there is an urgent need for more effective therapies. Fibroblast growth factor 18 (FGF18) has potent anti-inflammatory properties and therefore has become a focus of research for the treatment of lung injury. However, the precise role of FGF18 in the pathological process of ALI and the underlying mechanisms have not been fully elucidated. Methods A mouse model of ALI and human umbilical vein endothelial cells (HUVEC) stimulated with lipopolysaccharide (LPS) was established in vivo and in vitro. AAV-FGF18 and FGF18 proteins were used in C57BL/6J mice and HUVEC, respectively. Vascular cell adhesion molecule-1 (VCAM-1), intercellular adhesion molecule-1 (ICAM-1), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and p65 protein levels were determined by western blotting or immunofluorescent staining. Afterward, related inhibitors were used to explore the potential mechanism by which FGF18 relieves inflammation. Results In this study, we found that FGF18 was significantly upregulated in LPS-induced ALI mouse lung tissues and LPS-stimulated HUVECs. Furthermore, our studies demonstrated that overexpressing FGF18 in the lung or HUVEC could significantly alleviate LPS-induced lung injury and inhibit vascular leakage. Conclusions Mechanically, FGF18 treatment dramatically inhibited the NF-κB signaling pathway both in vivo and in vitro. In conclusion, these results indicate that FGF18 attenuates lung injury, at least partially, via the NF-κB signaling pathway and therefore may be a potential therapeutic target for ALI.

System-level fault diagnosis model, namely, the PMC model, detects fault nodes only through the mutual testing of nodes in the system without physical equipment. In order to achieve server nodes fault diagnosis in large-scale data center networks (DCNs), the traditional algorithm based on the PMC model cannot meet the characteristics of high diagnosability, high accuracy and high efficiency due to its inability to ensure that the test nodes are fault-free. This paper first proposed a fault-tolerant Hamiltonian cycle fault diagnosis (FHFD) algorithm, which tests nodes in the order of the Hamiltonian cycle to ensure that the test nodes are faultless. In order to improve testing efficiency, a hierarchical diagnosis mechanism was further proposed, which recursively divides high scale structures into a large number of low scale structures based on the recursive structure characteristics of DCNs. Additionally, we proved that $ 2(n-2){n^{k-1}} $ and $ (n-2){t_{n, k}}/{t_{n, 1}} $ faulty nodes could be detected for $ BCub{e_{n, k}} $ and $ DCel{l_{n, k}} $ within a limited time for the proposed diagnosis strategy. Simulation experiments have also shown that our proposed strategy has improved the diagnosability and test efficiency dramatically.

Abstract Highly stretchable porous materials are promising for flexible electronics but their fabrication is a great challenge. Herein, several kinds of highly stretchable conductive porous elastomers with low or negative Poisson’s ratios are achieved by uniaxial, biaxial, and triaxial hot-pressing strategies. The reduced graphene oxide/polymer nanocomposite elastomers with folded porous structures obtained by uniaxial hot pressing exhibit high stretchability up to 1200% strain. Furthermore, the meta-elastomers with reentrant porous structures combining high biaxial (or triaxial) stretchability and negative Poisson’s ratios are achieved by biaxial (or triaxial) hot pressing. The resulting elastomer-based wearable strain sensors exhibit an ultrawide response range (0-1200%). The materials can be applied for smart thermal management and electromagnetic interference shielding, which are achieved by regulating the porous microstructures via stretching. This work provides a versatile strategy to highly stretchable and negative-Poisson-ratio porous materials with promising features for various applications such as flexible electronics, thermal management, electromagnetic shielding, and energy storage.

Background Non-suicidal self-injury (NSSI), of which the predisposing factors are complex and diverse, profoundly affects the physical and mental health of young people. Therefore, this work established an NSSI intermediary network model considering the interaction of multiple factors. A mediating effect between attention-deficit/hyperactivity disorder (ADHD) and NSSI, considering the influence of comorbidities, such as depression, anxiety, and impulsive personality, was proposed based on sex differences. Methods A total of 2,689 middle school students in Ningbo City, Zhejiang Province, China, were randomly sampled and participated in this study. Data regarding their demographic characteristics, attention deficit, hyperactivity/impulsivity, NSSI, anxiety, depression, internet addiction, and other comorbid symptoms were collected and analyzed. After initially screening the data, variables were assessed for significance using a single-factor inter-group difference analytic method, and a binary logistic regression analysis was performed. The intermediary effect of factors influencing NSSI in males and females was also analyzed. Results The overall NSSI rate was 15.16%. The results showed that the impact of individual impulsivity characteristics (impulsiveness, the ADHD with hyperactivity/impulsivity subtype) on NSSI behavior was not significant (regression results, P > 0.05). The degree of association between ADHD with attention deficit and ADHD with comprehension deficit subtypes, and other comorbid symptoms (depression, anxiety, and internet addiction disorder) and NSSI, with odds ratios (ORs) of 7.6/6.42/436.68/3.82/1.86, and 95% bootstrap confidence intervals (CIs) of 4.64, 12.87/3.46, 12.67/137.42, 2659.13/2.32, 6.37/1.31, 2.82, respectively. The results also showed significant effects of ADHD subtypes on comorbid symptoms and the path effects of NSSI (P

Background: California hare coltivirus (CHCV) was isolated in California in 1976 from a hare. Despite its long history, it remained unclear whether CHCV was exclusively distributed in California with limited host ranges. Main body: By next-generation sequencing (NGS), we obtained a complete sequence of CHCV from Ixodes persulcatus collected in 2019 in northeast China. An expanded epidemiological investigation was subsequently performed on ticks belonging to four species (Ix. persulcatus, Haemaphysalis concinna, Devmacentor silvarum, Haemaphysalis longicornis) collected in northeastern China by applying CHCV-specific RT-PCR and sequencing. CHCV RNA-positive results were found in 1.56% of the tick samples. Positive ticks were obtained in three of four sampled locations, with the highest rate observed in Inner Mongolia (2.69%), followed by Heilongjiang (1.94%) and Jilin provinces (0.55%). All positive results were derived from Ix. persulcatus ticks (2.33%), while no positive detection was found in the other tick species, even at the same location. Sequence analysis revealed that the current CHCV showed a high genetic identity (>80% amino acid identity) with the previously reported CHCV in all segments except segment seven (64.59% amino acid identity). Phylogenetic analysis based on RNA-dependent RNA polymerase (RdRp) amino acid sequences demonstrated that both the current and previously reported CHCV strains were grouped phylogenetically into the genus Coltivirus. Both CHCV strains formed a distinct clade, clustering with three human pathogenic coltiviruses (Colorado tick fever virus, Salmon River virus, and Eyach virus), and were distant from the other coltiviruses. Conclusions: We report the identification and characterization of CHCV for the first time in Ix. persulcatus ticks, expanding the currently known geographic scope, host, and genetic heterogeneity in CHCV.

To improve the ecological and economic benefits of Korean pine (Pinus koraiensis), we analysed and evaluated its germplasm resources. This promotes in-depth research and utilisation of germplasm resources, providing excellent genetic resources for Korean pine breeding. We performed genetic analysis based on morphological and physiological traits and nuclear SSR molecular marker data was performed by collecting 314 clones (5 ramets of each clone) of Korean pine from eight (8) locations within the Korean pine range. The core collection underwent testing and evaluation for representativeness using variable rate (VR), coincidence rate (CR), variance difference percentage (VD), mean difference percentage (MD), Shannon index (I), and other indicators. The results indicated significant differences in morphological and physiological traits among the populations. All traits had a coefficient of variation (CV) greater than 10%, except for the water content of the needles (WC), which had an average CV of 17.636%. The populations showed high overall genetic diversity, with the HL (Helong) population exhibiting the highest genetic diversity, with an Ne (number of effective alleles), I, and He (expected heterozygosity) of 3.171, 1.103, and 0.528, respectively. Genetic variation mainly originated from individuals within populations, while the variation between populations was relatively small, at only 3%. The population did not exhibit any distinct subpopulation structures and was mainly derived from two admixed gene pools. Six core sets were obtained using different sampling strategies, and subset 6 was identified as the core collection, consisting of 114 individuals, representing a selection rate of 36.31%. In conclusion, the most appropriate method for constructing the core collection of Korean pines is the M-strategy (maximizing the number of alleles), based on both phenotypic and molecular data. The resulting core collection effectively represents the genetic diversity of the entire population effectively.

Abstract Background Cancer cachexia‐induced skeletal muscle fibrosis (SMF) impairs muscle regeneration, alters the muscle structure and function, reduces the efficacy of anticancer drugs, diminishes the patient's quality of life and shortens overall survival. RUNX family transcription factor 2 (Runx2), a transcription factor, and collagen type I alpha 1 chain (COL1A1), the principal constituent of SMF, have been linked previously, with Runx2 shown to directly modulate COL1A1 mRNA levels. l‐Carnitine, a marker of cancer cachexia, can alleviate fibrosis in liver and kidney models; however, its role in cancer cachexia‐associated fibrosis and the involvement of Runx2 in the process remain unexplored. Methods Female C57 mice (48 weeks old) were inoculated subcutaneously with MC38 cells to establish a cancer cachexia model. A 5 mg/kg dose of l‐carnitine or an equivalent volume of water was administered for 14 days via oral gavage, followed by assessments of muscle function (grip strength) and fibrosis. To elucidate the interplay between the deltex E3 ubiquitin ligase 3L(DTX3L)/Runx2/COL1A1 axis and fibrosis in transforming growth factor beta 1‐stimulated NIH/3T3 cells, a suite of molecular techniques, including quantitative real‐time PCR, western blot analysis, co‐immunoprecipitation, molecular docking, immunofluorescence and Duolink assays, were used. The relevance of the DTX3L/Runx2/COL1A1 axis in the gastrocnemius was also explored in the in vivo model. Results l‐Carnitine supplementation reduced cancer cachexia‐induced declines in grip strength (>88.2%, P 57.9%, P

Abstract Background Esophageal squamous cell carcinoma (ESCC) is often diagnosed at advanced stages due to the inherent limitations of current screening methodologies. Central to evaluating tumor invasion and prognostic assessment in ESCC is the integrity of the basement membrane (BM). However, current research on the implications of BM-related genes (BMRGs) in diagnosing ESCC remains sparse. Methods We performed a comprehensive analysis using single-cell RNA-sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database, alongside gene expression profiles acquired from GEO and The Cancer Genome Atlas (TCGA) databases. This identified differentially expressed BMRGs in ESCC. Employing LASSO, RF, and SVM-RFE, we selected potential BM biomarkers and crafted a diagnostic nomogram for ESCC, validated by ROC curves and AUC values. We also explored immune infiltration and biological mechanisms through consensus clustering and GSVA, and utilized single cell trajectory analysis and GSCALite to study gene distributions and pathways. In vitro experiments further elucidated the role of these genes in ESCC carcinogenesis. Results Here, we discovered that ESCC cell types exhibited markedly elevated BM-related scores. Our analysis pinpointed seven BM genes upregulated and linked to immune infiltration, showcasing unique gene expression profiles and varying immune cell densities across the BM-related subtypes. Furthermore, a robust positive correlation was observed between these genes expression and EMT activity. The knockdown of BGN significantly suppressed cell proliferation, migration, invasion, while also augmenting cell viability following chemotherapy drug treatment. Conclusion Our study identified seven key BMRGs (BGN, LAMB3, SPARC, MMP1, LUM, COL4A1, and NELL2) and established a diagnostic nomogram for ESCC. Of noteworthy significance is the discovery of BGN as a promising drug target, indicating a novel strategy for future clinical combination therapies in ESCC.

Energy storage systems (ESSs) operate as independent market participants and collaborate with photovoltaic (PV) generation units to enhance the flexible power supply capabilities of PV units. However, the dynamic variations in the profitability of ESSs in the electricity market are yet to be fully understood. This study introduces a dual-timescale dynamics model that integrates a spot market clearing (SMC) model into a system dynamics (SD) model to investigate the profit-aware capacity growth of ESSs and compares the profitability of independent energy storage systems (IESSs) with that of an ESS integrated within a PV (PV-ESS). Furthermore, this study aims to ascertain the optimal allocation of the PV-ESS. First, SD and SMC models were set up. Second, the SMC model simulated on an hourly timescale was incorporated into the SD model as a subsystem, a dual-timescale model was constructed. Finally, a development simulation and profitability analysis was conducted from 2022 to 2040 to reveal the dynamic optimal range of PV-ESS allocation. Additionally, negative electricity prices were considered during clearing processes. The simulation results revealed differences in profitability and capacity growth between IESS and PV-ESS, helping grid investors and policymakers to determine the boundaries of ESSs and dynamic optimal allocation of PV-ESSs.

This editorial summarizes the papers selected for publication in the Special Issue on Climate Change Mitigation and Adaptation in Power and Energy Systems (CMAP). After a rigorous review of 86 submitted manuscripts, 23 papers were accepted for publication. These accepted papers cover various aspects of climate change mitigation and adaptation and are classified as follows: boosting renewable energy efficiency (two papers), climate resilience strategies (four papers), decarbonization strategies (four papers), renewable energy integration (five papers), policies, incentives, and science communications (four papers), and the role of energy markets (four papers). The Guest Editorial Board is optimistic that this Special Issue will serve as a rich resource, offering invaluable insights to propel future research and advancements in climate change mitigation and adaptation.

Summary: In this study, we obtained the whole genome sequence of GCRV-DY197 and investigated the localization, post-translational modifications, and host interactions of the 11 viral proteins encoded by GCRV-DY197 in grass carp ovary (GCO) cells. The whole genome sequence is 24,704 kb and contains 11 segments (S1–S11). Subcellular localization showed that the VP1, VP2, VP3, VP5, VP56, and VP35 proteins were localized in both cytoplasm and nucleus, whereas the NS79, VP4, VP41, VP6, and NS38 proteins were localized in the cytoplasm. The NS79 and NS38 proteins were phosphorylated, and the ubiquitination modification sites were identified in VP41 and NS38. An interaction network containing 9 viral proteins and 140 host proteins was also constructed. These results offer a theoretical basis for an in-depth understanding of the biochemical characteristics and pathogenic mechanism of GCRV-II.

In invasive lung adenocarcinoma (LUAD), patients with micropapillary (MIP) or solid (SOL) components had a significantly poorer prognosis than those with only lepidic (LEP), acinar (ACI) or papillary (PAP) components. It is interesting to explore the genetic features of different histologic subtypes, especially the highly aggressive components.Based on a cohort of 5,933 patients, this study observed that in different tumor size groups, LUAD with MIP/SOL components showed a different prevalence, and patients with ALK alteration or TP53 mutations had a higher probability of developing MIP/SOL components. To control individual differences, this research used spatial whole-exome sequencing (WES) via laser-capture microdissection of five patients harboring these five coexistent components and identified genetic features among different histologic components of the same tumor. In tracing the evolution of components, we found that titin (TTN) mutation might serve as a crucial intratumor potential driver for MIP/SOL components, which was validated by a cohort of 146 LUAD patients undergoing bulk WES. Functional analysis revealed that TTN mutations enriched the complement and coagulation cascades, which correlated with the pathway of cell adhesion, migration, and proliferation.Collectively, the histologic subtypes of invasive LUAD were genetically different, and certain trunk genotypes might synergize with branching TTN mutation to develop highly aggressive components.

IntroductionThe marine economy has played an important role in stabilizing national economic growth and ensuring economic security. Achieving high-quality and sustainable development of the marine economy is a strategic task for China to build a maritime power. Confronting various risk factors such as financial crises, natural disasters, geopolitical conflicts, industrial transformation, and public health security, etc., marine economic resilience (MER) has received widespread attention in recent years and is considered to be crucial for high-quality and sustainable development of the marine economy. MethodsThis study takes 11 coastal provinces in China as cases, integrates 6 condition variables by building a Resistance capability-Recovery capability-Renewal capability (3R) configuration model, and uses the fuzzy-set qualitative comparative analysis (fsQCA) approach to empirically explore the configuration effect between multiple land factors and MER. Results and discussion(1) None of the 6 conditions in the three dimensions of resistance capability, recovery capability, and renewal capability alone constitute the necessary conditions for strong or weak MER, indicating that a single condition has weak explanatory power for MER; (2) There are two configurations for strong MER: Strong Resistance-Recovery Type and Comprehensive Strong Type. Industrial structure, governmental capability, and digital economy are the core conditions for strong MER configurations; (3) There are four weak MER configurations: Comprehensive Weak Type, Weak Recovery-Renewal Type, Weak Resistance-Recovery Type I, and Weak Resistance-Recovery Type II. This study may expand the research scope of MER influencing factors and enriching the research perspective of land-sea integration, as well as providing decision-makers with practical policy implications.

Modified Jiawei Juanbi decoction (MJD) is used for the treatment of early-stage knee osteoarthritis (KOA). Here, modified Jiawei Juanbi decoction (MJD) was employed for the treatment of early-stage knee osteoarthritis (KOA) and its mechanisms were assessed via metabonomics and network pharmacology. A total of 24 male Sprague-Dawley rats were randomly allocated into a normal control group, a model group, and an MJD group (n = 8 rats per group). Each rat group was further equally divided into two subgroups for investigation for either 14 or 28 days. A rat model of early-stage KOA was constructed and rats were treated with MJD. Effects were evaluated based on changes in knee circumference, mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL). We also analyzed histopathological changes in articular cartilage. High-resolution mass spectrometry was used to analyze the chemical profile of MJD, identifying 228 components. Using an LC-Q-TOF-MS metabonomics approach, 33 differential metabolites were identified. The relevant pathways significantly associated with MJD include arginine and proline metabolism, vitamin B6 metabolism, as well as the biosynthesis of phenylalanine, tyrosine and tryptophan. The system pharmacology paradigm revealed that MJD contains 1027 components and associates with 1637 genes, of which 862 disease genes are related to osteoarthritis. The construction of the MJD composition-target-KOA network revealed a total of 140 intersection genes. A total of 39 hub genes were identified via integration of betweenness centrality values greater than 100 using CytoHubba. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed several significantly affected signaling pathways including the HIF-1, AGE-RAGE (in diabetic complications), IL-17, rheumatoid arthritis and TNF pathways. Integrated-omics and network pharmacology approaches revealed a necessity for further detailed investigation focusing on two major targets, namely NOS2 and NOS3, along with their essential metabolite (arginine) and associated pathways (HIF-1 signaling and arginine and proline metabolism). Real-time PCR validated significantly greater downregulation of NOS2 and HIF-1ɑ in the MJD as compared to the model group. Molecular docking analysis further confirmed the binding of active MJD with key active components. Our findings elucidate the impact of MJD on relevant pathophysiological and metabolic networks relevant to KOA and assess the drug efficacy of MJD and its underlying mechanisms of action.

Abstract Background Apolipoprotein A1 (ApoA1) is a member of the apolipoprotein family with diverse functions. It is associated with the pathogenesis and prognosis of several types of tumors. However, the role of serum apolipoprotein A1 (ApoA1) in the prognosis of patients with diffuse large B-cell lymphoma (DLBCL) remains unclear. This study aimed to elucidate its influence on clinical outcomes in patients with DLBCL. Methods We retrospectively analyzed a cohort of 1583 consecutive DLBCL patients admitted to the Fujian Medical University Union Hospital between January 2011 and December 2021. 949 newly diagnosed DLBCL patients who met the inclusion criteria were enrolled for statistical analysis. Receiver operating characteristic curve analysis was performed to determine the optimal cut-off value for serum ApoA1 levels for prognostic prediction among patients with DLBCL. The correlations between serum ApoA1 levels and clinical and laboratory parameters were analyzed. Prognostic significance was analyzed using univariate and multivariate Cox proportional hazards models. Results Newly diagnosed patients with DLBCL demonstrated low serum ApoA1 levels (upper limit of normal), poorer performance status (Eastern Cooperative Oncology Group score of 2–4), higher percentage of advanced stage and non-germinal center B-cell (non-GCB) subtype, more cases of > 1 extranodal site, higher International Prognostic Index (IPI) score (3–5), and higher incidence of relapse or refractory diseases compared with those with high serum ApoA1 levels (≥ 0.925 g/L). Low serum ApoA1 levels were an independent adverse prognostic factor for overall survival (OS) but not progression-free survival (PFS). Conclusions Low serum ApoA1 levels were associated with poor treatment response and inferior survival in newly diagnosed patients with DLBCL.

Alzheimer’s disease (AD) is a multifaceted neurodegenerative disorder characterized by cognitive decline and neuronal loss, representing a most challenging health issue. We present a computational analysis of transcriptomic data of AD tissues vs. healthy controls, focused on the elucidation of functional roles played by long non-coding RNAs (lncRNAs) throughout the AD progression. We first assembled our own lncRNA transcripts from the raw RNA-Seq data generated from 527 samples of the dorsolateral prefrontal cortex, resulting in the identification of 31,574 novel lncRNA genes. Based on co-expression analyses between mRNAs and lncRNAs, a co-expression network was constructed. Maximal subnetworks with dense connections were identified as functional clusters. Pathway enrichment analyses were conducted over mRNAs and lncRNAs in each cluster, which served as the basis for the inference of functional roles played by lncRNAs involved in each of the key steps in an AD development model that we have previously built based on transcriptomic data of protein-encoding genes. Detailed information is presented about the functional roles of lncRNAs in activities related to stress response, reprogrammed metabolism, cell polarity, and development. Our analyses also revealed that lncRNAs have the discerning power to distinguish between AD samples of each stage and healthy controls. This study represents the first of its kind.

This article presents two quantum algorithms for computing the product of a circulant matrix and a vector. The arithmetic complexity of the first algorithm is O(Nlog2N) in most cases. For the second algorithm, when the entries in the circulant matrix and the vector take values in C or R, the complexity is O(Nlog2N) in most cases. However, when these entries take values from positive real numbers, the complexity is reduced to O(log3N) in most cases, which presents an exponential speedup compared to the classical complexity of O(NlogN) for computing the product of a circulant matrix and vector. We apply this algorithm to the convolution calculation in quantum convolutional neural networks, which effectively accelerates the computation of convolutions. Additionally, we present a concrete quantum circuit structure for quantum convolutional neural networks.

Abstract Pathological cardiac hypertrophy is the leading cause of heart failure and has an extremely complicated pathogenesis. TEA domain transcription factor 1 (TEAD1) is recognized as an important transcription factor that plays a key regulatory role in cardiovascular disease. This study aimed to explore the role of TEAD1 in cardiac hypertrophy and to clarify the regulatory role of small ubiquitin‐like modifier (SUMO)‐mediated modifications. First, the expression level of TEAD1 in patients with heart failure, mice, and cardiomyocytes is investigated. It is discovered that TEAD1 is modified by SUMO1 during cardiac hypertrophy and that the process of deSUMOylation is regulated by SUMO‐specific protease 1 (SENP1). Lysine 173 is an essential site for TEAD1 SUMOylation, which affects the protein stability, nuclear localization, and DNA‐binding ability of TEAD1 and enhances the interaction between TEAD1 and its transcriptional co‐activator yes‐associated protein 1 in the Hippo pathway. Finally, adeno‐associated virus serotype 9 is used to construct TEAD1 wild‐type and KR mutant mice and demonstrated that the deSUMOylation of TEAD1 markedly exacerbated cardiomyocyte enlargement in vitro and in a mouse model of cardiac hypertrophy. The results provide novel evidence that the SUMOylation of TEAD1 is a promising therapeutic strategy for hypertrophy‐related heart failure.

In recent years, the potent influence of tocotrienol (T3) on diminishing blood glucose and lipid concentrations in both Mus musculus (rats) and Homo sapiens (humans) has been established. However, the comprehensive exploration of tocotrienol’s hypolipidemic impact and the corresponding mechanisms in aquatic species remains inadequate. In this study, we established a zebrafish model of a type 2 diabetes mellitus (T2DM) model through high-fat diet administration to zebrafish. In the T2DM zebrafish, the thickness of ocular vascular walls significantly increased compared to the control group, which was mitigated after treatment with T3. Additionally, our findings demonstrate the regulatory effect of T3 on lipid metabolism, leading to the reduced synthesis and storage of adipose tissue in zebrafish. We validated the expression patterns of genes relevant to these processes using RT-qPCR. In the T2DM model, there was an almost two-fold upregulation in pparγ and cyp7a1 mRNA levels, coupled with a significant downregulation in cpt1a mRNA (p < 0.01) compared to the control group. The ELISA revealed that the protein expression levels of Pparγ and Rxrα exhibited a two-fold elevation in the T2DM group relative to the control. In the T3-treated group, Pparγ and Rxrα protein expression levels consistently exhibited a two-fold decrease compared to the model group. Lipid metabolomics showed that T3 could affect the metabolic pathways of zebrafish lipid regulation, including lipid synthesis and decomposition. We provided experimental evidence that T3 could mitigate lipid accumulation in our zebrafish T2DM model. Elucidating the lipid-lowering effects of T3 could help to minimize the detrimental impacts of overfeeding in aquaculture.