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The C-reactive protein(CRP)-triglyceride glucose index (CTI) is a new composite biomarker used to assess inflammation and insulin resistance(IR) severity. Heart failure (HF) poses a substantial epidemiological threat with increasing incidence and mortality worldwide. However, the relationship between CTI and HF has not been extensively investigated. Using cross-sectional data from the National Health and Nutrition Examination Survey (NHANES) 2001–2010, 21,974 participants ≥ 20 years were included. HF diagnosis was based on self-reported medical history. Multivariable logistic regression adjusted for demographic, lifestyle, and clinical covariates. Smooth curve fitting analyzed dose-response relationships, while subgroup analyses explored effect heterogeneity. The research cohort comprised 21,974 individuals (631 HF cases, 21,343 non-HF). HF patients exhibited significantly higher CTI levels ( p  < 0.001), and a positive correlation with HF prevalence was observed ( p  < 0.001). Consistent positive associations were maintained across subgroups, with no significant interactions detected. Logistic regression analysis demonstrated adjusted ORs for HF per 1-unit CTI increase of 1.492 (model 1, unadjusted) and 1.279 (model 3, fully adjusted). Quartile analysis revealed a progressive increase in prevalent HF with higher CTI levels, and model 3 confirmed a nonlinear dose-response relationship ( p  < 0.001) with a threshold at 11.657. CTI is positively associated with the presence of HF in US adults, suggesting its potential as a biomarker for HF prevention and treatment strategies.

Objective Using 2005–2018 NHANES data, this study examined the association between the visceral fat metabolism score (METS-VF) and heart failure (HF) prevalence in U.S. adults, leveraging machine learning (LightGBM/XGBoost) and SHAP for classfication performance evaluation and feature interpretation. Methods After excluding missing data, 30,704 participants were analyzed via survey-weighted statistics, restricted cubic splines (RCS), stratified analyses, and multivariate logistic regression. Ensemble models were compared for HF classification, with SHAP quantifying feature importance. Results HF patients exhibited higher METS-VF (7.35 ± 0.53 vs. 6.79 ± 0.72, P  < 0.001) and worse cardiometabolic profiles. Multivariate adjustment revealed a 2.249-fold increased HF prevalence per 1-unit METS-VF increase (95% CI: 1.503–3.366, P  < 0.001), with a nonlinear threshold effect (inflection point = 7.151; OR = 3.321, 95% CI: 3.464–8.494 for METS-VF ≥ 7.151). Obesity (BMI ≥ 30 kg/m²) amplified the association (OR = 5.857). LightGBM outperformed logistic regression in classification (AUC = 0.964 vs. 0.907), with SHAP identifying METS-VF as the top contributor (importance weight = 18.6%), surpassing hypertension (10.8%) and coronary artery disease (11.7%). Correlations validated METS-VF as a composite index of visceral adiposity and metabolic dysfunction (waist circumference r  = 0.43, high-density lipoprotein cholesterol r  = − 0.38, all P  < 0.001). Conclusion METS-VF is independently and nonlinearly associated with HF prevalence, particularly in obese individuals. Machine learning enhances predictive accuracy by capturing complex interactions, while SHAP-based interpretability establishes METS-VF as a key biomarker integrating metabolic-adipose abnormalities, offering a novel target for personalized HF prevention.

The cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway is critical in cancer immunity. Autophagy is a highly conserved process that is responsible for the degradation of cytoplasmic material and is involved in both innate and adaptive immunity. Recently, cGAS-STING and autophagy have been shown to be interconnected, which may influence the progression of cancer. Although cGAS-STING and autophagy have been shown to be interrelated in innate immunity, little has been reported about cancer immunity. As cancer immunity is key to treating tumors, it is essential to summarize the relationship and interactions between the two. Based on this, we systematically sorted out the recent findings of cGAS-STING and autophagy in cancer immunity and explored the interactions between cGAS-STING and autophagy, although these interactions have not been extensively studied. Lastly, we provide an outlook on how cGAS-STING and autophagy can be combined, with the hope that our research can help people better understand their potential roles in cancer immunity and bring light to the treatment of cancer.

Reversing the hypoxic microenvironment of tumors is an important method to enhance the synergistic effect of tumor treatment. In this work, we developed the nanoparticles called Ce6@HGMOF, which consists of a photosensitizer (Ce6), glucose oxidase (GOX), chemotherapy drugs (HCPT) and an iron-based metal-organic framework (MOF). Ce6@HGMOF can consume glucose in tumor cells through “starvation therapy”, cut off their nutrition source, and produce gluconic acid and hydrogen peroxide (H 2 O 2 ). Utilizing this feature, Ce6@HGMOF can produce oxygen through catalase-like catalytic activity, thereby reversing the hypoxic microenvironment of tumors. This strategy of changing the hypoxic environment can help to slow down the growth of tumor blood vessels and improve the drug-resistant microenvironment to some extent. Meanwhile, increasing the supply of oxygen can enhance the effect of photodynamic therapy (PDT) and enhance the oxidative stress damage caused by reactive oxygen species (ROS) in tumor cells. On the other hand, cancer cells usually produce higher levels of glutathione (GSH) to adapt to high oxidative stress and protect themselves. The Ce6@HGMOF we designed can also consume GSH and induce ferroptosis of tumor cells through Fenton reaction with H 2 O 2 , while enhancing the effect of PDT. This innovative synergistic strategy, the combination of PDT/ferroptosis /starvation therapy, can complement each other and enhance each other. It has great potential as a powerful new anti-tumor paradigm in the future.

Background Somatic embryogenesis (SE) is a process of somatic cells that dedifferentiate to totipotent embryonic stem cells and generate embryos in vitro. Longan SE has been established and wildly used as model system for studying embryogenesis in woody plants, SE-related genes had been characterized. In spite of that, a comprehensive overview of SE at a molecular level is still absent. To understand the molecular mechanisms during longan SE, we examined the transcriptome changes by using Illumina HiSeq from the four distinct developmental stages, including non-embryogenic callus (NEC), embryogenic callus (EC), incomplete compact pro-embryogenic cultures (ICpEC), globular embryos (GE). Results RNA-seq of the four samples generated a total of 243.78 million high quality reads, approximately 81.5% of the data were mapped to longan genome. The cDNA libraries of NEC, EC, ICpEC and GE, generated 22,743, 19,745, 21,144, 21,102 expressed transcripts, 1935, 1710, 1816, 1732 novel transcripts, 2645, 366, 505, 588 unique genes, respectively. Comparative transcriptome analysis showed that a total of 10,642, 4180, 5846 and 1785 genes were differentially expressed in the pairwise comparisons of NEC_ vs _EC, EC_ vs _ICpEC, EC_ vs _GE, ICpEC_ vs _GE, respectively. Among them, plant hormones signalling related genes were significantly enriched, especially the auxin and cytokinin signalling components. The transcripts of flavonoid biosynthesis related genes were mainly expressed in NEC, while fatty acid biosynthesis related genes mainly accumulated in early SE. In addition, the extracelluar protein encoding genes LTP , CHI , GLP , AGP , EP1 were related to longan SE. Combined with the FPKM value of longan nine tissues transcription, 27 SE specific or preferential genes ( LEC1 , LEC1-like , PDF1.3 , GH3.6 , AGL80 , PIN1 , BBM , WOX9 , WOX2 , ABI3 , et al.) and 28 NEC preferential genes ( LEA5 , CNOT3 , DC2.15 , PR1–1 , NsLTP2 , DIR1 , PIP1 , PIP2.1 , TIP2–1 , POD-P7 and POD5 et al.) were characterized as molecular markers for longan early SE. qRT-PCR validation of SE-related genes showed a high correlation between RNA-seq and qRT-PCR data. Conclusion This study provides new insights into the role of the transcriptome during early SE in longan. Differentially expressed genes reveal that plant hormones signalling, flavonoid and fatty acid biosynthesis, and extracelluar protein related genes were involved in longan early SE. It could serve as a valuable platform resource for further functional studies addressing embryogenesis in woody plants.

The core of cross-modal hashing methods is to map high dimensional features into binary hash codes, which can then efficiently utilize the Hamming distance metric to enhance retrieval efficiency. Recent development emphasizes the advantages of the unsupervised cross-modal hashing technique, since it only relies on relevant information of the paired data, making it more applicable to real-world applications. However, two problems, that is intro-modality correlation and inter-modality correlation, still have not been fully considered. Intra-modality correlation describes the complex overall concept of a single modality and provides semantic relevance for retrieval tasks, while inter-modality correction refers to the relationship between different modalities. From our observation and hypothesis, the dependency relationship within the modality and between different modalities can be constructed at the object level, which can further improve cross-modal hashing retrieval accuracy. To this end, we propose a Visual-textful Correlation Graph Hashing (OVCGH) approach to mine the fine-grained object-level similarity in cross-modal data while suppressing noise interference. Specifically, a novel intra-modality correlation graph is designed to learn graph-level representations of different modalities, obtaining the dependency relationship of the image region to image region and the tag to tag in an unsupervised manner. Then, we design a visual-text dependency building module that can capture correlation semantic information between different modalities by modeling the dependency relationship between image object region and text tag. Extensive experiments on two widely used datasets verify the effectiveness of our proposed approach.

Primary liver cancer (PLC) is one type of cancer with high incidence rate and high mortality rate in the worldwide. Systemic therapy is the major treatment for PLC, including surgical resection, immunotherapy and targeted therapy. However, mainly due to the heterogeneity of tumors, responses to the above drug therapy differ from person to person, indicating the urgent needs for personalized treatment for PLC. Organoids are 3D models derived from adult liver tissues or pluripotent stem cells. Based on the ability to recapitulate the genetic and functional features of in vivo tissues, organoids have assisted biomedical research to make tremendous progress in understanding disease origin, progression and treatment strategies since their invention and application. In liver cancer research, liver organoids contribute greatly to reflecting the heterogeneity of liver cancer and restoring tumor microenvironment (TME) by co-organizing tumor vasculature and stromal components in vitro . Therefore, they provide a promising platform for further investigation into the biology of liver cancer, drug screening and precision medicine for PLC. In this review, we discuss the recent advances of liver organoids in liver cancer, in terms of generation methods, application in precision medicine and TME modeling.

Background As one of the most promising monomers of biobased polyamides, cadaverine has wide industrial application prospects. However, in microbial cadaverine fermentation with glucose as the sole carbon source, the impaired coordination between precursor (lysine) utilization and cytotoxic cadaverine accumulation has been identified as the primary bottleneck limiting high-yield biosynthesis. Here, we developed a lysine biosensor in Escherichia coli to dynamically regulate cadaverine biosynthesis. Results In this study, we developed a lysine biosensor based on the lysine transporter protein LysP, the transcription activator CadC, and the GFPuv gene under the control of the P cad promoter. However, the engineered lysine biosensor system had a low dynamic range and a narrow pH operating range. Therefore, a multilevel optimization strategy, which included the introduction of key point mutations and engineered promoter modifications, were introduced to improve the performance of the biosensor, resulting in significant improvements in the dynamic range and lysine response. Moreover, we engineered a cadaverine-producing E. coli strain by increasing the supply of the lysine precursor, overexpressing key cadaverine synthesis genes, and knocking out genes related to metabolic bypass. The lysine biosensor was subsequently implemented to dynamically regulate cadaverine biosynthesis, resulting in a 48.10% increase in the production titre (33.19 g/L) and a 21.2% increase in cell growth compared with those resulting from the strain with constitutive expression. Conclusion This is the first report in which a lysine biosensor constructed in E. coli could dynamically regulate cadaverine synthesis to improve its yield and biomass. This strategy provides new insights into the metabolic engineering of lysine and its derivatives in E. coli.

The ubiquitous pathogen Toxoplasma gondii has a complex lifestyle with different metabolic activities at different stages that are intimately linked to the parasitic environments. Here we identified the eukaryotic regulator of cellular homeostasis AMP-activated protein kinase (AMPK) in Toxoplasma and discovered its role in metabolic programming during parasite’s lytic cycle. The catalytic subunit AMPKα is quickly phosphorylated after the release of intracellular parasites to extracellular environments, driving energy-producing catabolism to power parasite motility and invasion into host cells. Once inside host cells, AMPKα phosphorylation is reduced to basal level to promote a balance between energy production and biomass synthesis, allowing robust parasite replication. AMPKγ depletion abolishes AMPKα phosphorylation and suppresses parasite growth, which can be partially rescued by overexpressing wildtype AMPKα but not the phosphorylation mutants. Thus, through the cyclic reprogramming by AMPK, the parasites’ metabolic needs at each stage are satisfied and the lytic cycle progresses robustly. Efficient metabolic regulation is key for parasite growth. Here, the authors report that Toxoplasma alters its AMPK phosphorylation during the lytic cycle, which reprograms parasite’s metabolism to ensure metabolic needs at different stages are met.

This review underscores the role of natural products in inducing immunogenic cell death (ICD) as a key strategy in tumor immunotherapy. It reveals that natural products can activate ICD through multiple pathways—apoptosis, autophagy, pyroptosis, and necroptosis—leading to the release of danger-associated molecular patterns (DAMPs), dendritic cell activation, and improved antigen presentation, which together stimulate a potent anti-tumor immune response. The study also demonstrates the enhanced therapeutic potential of combining natural products with immune checkpoint inhibitors. With a focus on translating preclinical findings into clinical practice, this review consolidates recent discoveries and suggests future research paths, offering both theoretical insights and practical guidance for advancing cancer immunotherapy.