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Type 2 diabetes mellitus is a major risk factor for hepatocellular carcinoma (HCC). Changes in extracellular matrix (ECM) mechanics contribute to cancer development 1 , 2 , and increased stiffness is known to promote HCC progression in cirrhotic conditions 3 , 4 . Type 2 diabetes mellitus is characterized by an accumulation of advanced glycation end-products (AGEs) in the ECM; however, how this affects HCC in non-cirrhotic conditions is unclear. Here we find that, in patients and animal models, AGEs promote changes in collagen architecture and enhance ECM viscoelasticity, with greater viscous dissipation and faster stress relaxation, but not changes in stiffness. High AGEs and viscoelasticity combined with oncogenic β-catenin signalling promote HCC induction, whereas inhibiting AGE production, reconstituting the AGE clearance receptor AGER1 or breaking AGE-mediated collagen cross-links reduces viscoelasticity and HCC growth. Matrix analysis and computational modelling demonstrate that lower interconnectivity of AGE-bundled collagen matrix, marked by shorter fibre length and greater heterogeneity, enhances viscoelasticity. Mechanistically, animal studies and 3D cell cultures show that enhanced viscoelasticity promotes HCC cell proliferation and invasion through an integrin-β1–tensin-1–YAP mechanotransductive pathway. These results reveal that AGE-mediated structural changes enhance ECM viscoelasticity, and that viscoelasticity can promote cancer progression in vivo, independent of stiffness. Structural changes mediated by advanced glycation end-products enhance extracellular matrix viscoelasticity, and that viscoelasticity can promote cancer progression in vivo, independent of stiffness.

Objective Platelets are increasingly considered to play an important role in inflammation and are being regarded as a putative bridge linking mental diseases and inflammatory response. Platelet-associated haematological parameters including mean platelet volume (MPV), platelet distribution width (PDW), plateletcrit (PCT), systemic immune-inflammation index (SII), platelet to lymphocyte ratio (PLR), platelet to albumin ratio (PAR) and red blood cell distribution width (RDW) to platelet ratio (RPR), have been recently investigated as simple, easily available, and inexpensive inflammatory markers. In this study, we aimed is to use large-scale clinical data to study platelet parameters in patients with affective disorders, to further investigate the predictive power of platelet parameters for major depressive disorder (MDD) and bipolar disorder (BD). Methods The retrospective, naturalistic, cross-sectional study analysed the data of 14,007 Chinese affective disorder patients, including 4,801 patients with first-episode MDD, 4,098 patients with recurrent MDD, 3,444 patients with BD manic episodes and 1,664 patients with BD depressive episodes. Meanwhile, 6,847 healthy subjects were served as the control group. The differences in the MPV, PDW, PCT, SII, PLR, PAR, RPR and albumin among different groups were compared, and the contributing factors for the occurrence of MDD or BD were analysed. Results There were significant differences in MPV, PDW, PCT, SII, PLR, RPR and albumin values among the study groups. In the subjects, patients experiencing BD manic episodes had the highest mean values of MPV and SII, patients experiencing BD depressive episodes had the lowest mean values of platelet counts and PAR, and patients with MDD had the highest mean values of PLR and RDW. The levels of MPV, PDW and albumin were independently correlated with MDD and BD, and they are important predictors for differentiating patients with MDD or BD from healthy controls. Conclusions Our study demonstrated that different affective disorders have unique platelet parameter variation patterns, highlighting the role of platelet parameters and systemic inflammation in the pathophysiology of MDD and BD.

To endow the prey with intelligent movement behavior and improve the performance of Golden Jackal Optimization (GJO), a Q-learning Improved Gold Jackal Optimization (QIGJO) algorithm is proposed. This paper introduces five update mechanisms and proposes double-population Q-learning collaborative mechanism to select appropriate update mechanisms to improve GJO performance. Additionally, a new convergence factor is incorporated to enhance convergence capability of GJO. QIGJO demonstrates excellent performance across 23 benchmark functions, CEC2022, and three classical engineering design problems, indicating high convergence accuracy and significantly enhanced global exploration capability. The reliability optimization model of the hydraulic system for concrete pump trucks was established based on a Continuous-time Multi-dimensional T-S dynamic Fault Tree (CM-TSdFT), considering the two-dimensional factors of operating time and number of impacts. Utilizing QIGJO to optimize this model yielded excellent results, providing valuable methodological support for reliability optimization of hydraulic systems.

Our retrospective cohort study (3-9 years) describes the progression and regression patterns among working adults aged 18-65 with normoglycemia, prediabetes, and diabetes, providing evidence for diabetes prevention and management strategies in this population. 15,765 subjects received baseline examinations between 2014 and 2018, with 14,623 (92.7%) completing follow-up, representing a follow-up period of 3-9 years for analysis. Chi-square tests were used to compare prediabetes and diabetes incidence, as well as rates of glycemic normalization among different age groups and genders in working populations. Cox proportional hazard regression models were used to estimate hazard ratios (HRs) and 95% confidence interval (CI). Among participants with baseline normoglycemia, 23.9% progressed to prediabetes, and 2.3% developed diabetes. Among prediabetic individuals, 28.0% progressed to diabetes, and 18.7% reverted to normoglycemia. Younger adults (18-40 years) exhibited significantly lower progression rates from normoglycemia to both prediabetes and diabetes compared to middle-aged adults (40-65 years) (prediabetes: 15.8% vs. 37.8%; diabetes: 1.2% vs. 4.2%; P < 0.001). Cox models revealed that young prediabetic individuals had a significantly higher risk of developing diabetes than middle-aged prediabetic individuals, showing a pronounced age-dependent risk pattern: prediabetic individuals aged 18-40 had an adjusted hazard ratio (HR) of 22.1 (95% CI: 14.9-32.7), compared to HR = 9.12 (7.45-11.2) in those aged 40-65. Prediabetes among working-age adults, particularly in younger individuals (18-40 years), carries an exceptionally elevated risk of progression to diabetes. The observed sex disparities in progression among young adults highlight the need for age- and sex-specific prevention strategies.

Cells can sense and respond to mechanical forces in fibrous extracellular matrices (ECMs) over distances much greater than their size. This phenomenon, termed long-range force transmission, is enabled by the realignment (buckling) of collagen fibers along directions where the forces are tensile (compressive). However, whether other key structural components of the ECM, in particular glycosaminoglycans (GAGs), can affect the efficiency of cellular force transmission remains unclear. Here we developed a theoretical model of force transmission in collagen networks with interpenetrating GAGs, capturing the competition between tension-driven collagen fiber alignment and the swelling pressure induced by GAGs. Using this model, we show that the swelling pressure provided by GAGs increases the stiffness of the collagen network by stretching the fibers in an isotropic manner. We found that the GAG-induced swelling pressure can help collagen fibers resist buckling as the cells exert contractile forces. This mechanism impedes the alignment of collagen fibers and decreases long-range cellular mechanical communication. We experimentally validated the theoretical predictions by comparing the intensity of collagen fiber alignment between cellular spheroids cultured on collagen gels versus collagen–GAG cogels. We found significantly lower intensities of aligned collagen in collagen–GAG cogels, consistent with the prediction that GAGs can prevent collagen fiber alignment. The role of GAGs in modulating force transmission uncovered in this work can be extended to understand pathological processes such as the formation of fibrotic scars and cancer metastasis, where cells communicate in the presence of abnormally high concentrations of GAGs.

The extracellular matrix (ECM) is a complex mixture composed of fibrillar collagens as well as additional protein and carbohydrate components. Proteoglycans (PGs) contribute to the heterogeneity of the ECM and play an important role in its structure and function. While the small leucine rich proteoglycans (SLRPs), including decorin and lumican, have been studied extensively as mediators of collagen fibrillogenesis and organization, the function of large matrix PGs in collagen matrices is less well known. In this study, we showed that different matrix PGs have distinct roles in regulating collagen behaviors. We found that versican, a large chondroitin sulfate PG, promotes collagen fibrillogenesis in a turbidity assay and upregulates cell-mediated collagen compaction and reorganization, whereas aggrecan, a structurally-similar large PG, has different and often opposing effects on collagen. Compared to versican, decorin and lumican also have distinct functions in regulating collagen behaviors. The different ways in which matrix PGs interact with collagen have important implications for understanding the role of the ECM in diseases such as fibrosis and cancer, and suggest that matrix PGs are potential therapeutic targets.

Bearings are core components in many types of industrial equipment, and their operating environment is often accompanied by strong background noise. This results in a low Signal-to-Noise Ratio (SNR) in the collected vibration signals, making it difficult for traditional methods to extract fault information effectively. Given that bearing failures often manifest as periodic impact signals, a Feature Mode Decomposition (FMD) method has been proposed by researchers which optimizes filter design through correlated kurtosis to enhance the ability to capture fault impact components. However, the decomposition performance of FMD is significantly affected by its parameters (mode number and filter length), and relies on manual settings, resulting in insufficient stability of the results. Therefore, this paper proposes a Dual-domain Impulse Complexity Index (DICI) that combines time-domain impulse characteristics and frequency-domain complexity as an evaluation criterion for FMD parameter optimization. Further, the projection-iterative-methods-based optimizer (PIMO) is adopted to achieve adaptive optimization of parameters. Subsequently, sensitive components are selected based on the maximum Fault Frequency Correlation (FFC) criterion, and their envelope spectra are calculated to recognize bearing fault modes. Simulation and real-signal verification show that the proposed method outperforms several established signal-processing approaches under low SNR conditions.

Midlife males with obstructive sleep apnea (OSA) bear a high risk for cardiovascular diseases. However, the association of OSA and hearing impairment is controversial. Our objective was to observe the incidence of hearing loss in middle-aged males with different risks for OSA. 794 men aged 40-65 who participated in health examination and pure tone hearing screening between January and June 2021 were recruited in the study. Medical history was collected. Height, weight and blood pressure were tested, and biochemical test including blood lipids and blood glucose was performed. According to the STOP-BANG score, the observed subjects were divided into low, intermediate and high groups for OSA risk. Hearing impairment was defined as failure in responding to any pure tone of 25 dB HL in any ear at the frequencies: 4 kHz for high frequency range and 0.5k, 1k, 2 kHz for low/medium frequency range. The incidence of hearing loss in those groups was compared after adjusting the cardiovascular risk factors. The incidence of hearing impairment in the groups of intermediate, high, and intermediate/high risk for OSA (46.9%, 45.2%, 46.3%, respectively) were higher than that in the group of low risk for OSA (33.3%, P<0.001). After adjusting cardiovascular risk factors, the risk of hearing impairment in the group of high risk for OSA is 1.64 times of the group of low risk for OSA (95%CI: 1.02-2.69, P<0.05). The risk of hearing impairment at high frequency(4kHz) in the group of intermediate/high risk for OSA is 1.43 times of the group of low-risk for OSA (95%CI: 1.00-2.06, P<0.05). The risk of hearing impairment in midlife men with high, intermediate/high risk for OSA is significantly increased, especially at high frequency of 4 kHz.

In real-world industrial settings, obtaining class-balanced fault data is often difficult. Imbalanced data across categories can degrade diagnostic accuracy. Time-series Generative Adversarial Network (TimeGAN) is an effective tool for addressing one-dimensional data imbalance; however, when dealing with multiple fault categories, it faces issues such as unstable training processes and uncontrollable generation states. To address this issue, from the perspective of data augmentation and classification, a gradient-penalized Conditional Time-series Generative Adversarial Network with a Multi-Scale Importance-aware Network (CTGAN-MSIN) is proposed in this paper. Firstly, a gradient-penalized Conditional Time-Series Generative Adversarial Network (CTGAN) is designed to alleviate data imbalance by controllably generating high-quality fault samples. Secondly, a Multi-scale Importance-aware Network (MSIN) is constructed for fault classification. The MSIN consists of the Multi-scale Depthwise Separable Residual (MDSR) and Scale Enhanced Local Attention (SELA): the MDSR network can efficiently extract multi-scale features, while the SELA network is capable of screening out the most discriminative scale features from them. Finally, the proposed method is validated using the HUST bearing dataset and the axial piston pump dataset. The results show that under the data imbalance ratio of 15:1, the CTGAN-MSIN achieves diagnostic accuracies of 98.75% and 96.50%, respectively, on the two datasets and outperforms the comparison methods under different imbalance ratios.

Background/Objectives: The X-inactivation specific transcript (XIST) is a long noncoding RNA playing a crucial regulatory role in X chromosome inactivation (XCI)—a transcriptional regulatory process that silences one of the two X chromosomes in females to ensure proper dosage compensation between male and female mammals. The transcription of XIST is maintained throughout a female’s lifespan in all somatic cells, where XIST RNA binds to the X chromosome in cis and ensures chromosome-wide gene silencing. Disrupting XIST expression can lead to transcriptional reactivation of X-linked genes and epigenetic changes affecting cell development. The prevalence of XIST regulatory effects on mammalian transcription, however, remains unclarified. Methods: Here we performed a comparative expression analysis using RNA-sequencing datasets from recently published studies and examined the consequences of XIST-deletion on transcription at the whole genome, individual chromosome, and specific gene levels. We investigated the common differentially expressed genes (DEGs) and biological pathways following XIST loss across cell types, together with differential transcriptional analysis comparing the X chromosome and autosomes using cumulative distribution fractions. We analyzed the distribution of DEGs along the X chromosome with scatterplots and correlation analysis incorporating gene density and transposable elements. Results: Our findings indicate that the loss of XIST causes transcriptional changes in the X chromosome and autosomes that differ depending on cell type and state. XIST-deletion results in differential expression of genes subject to XCI-silencing as well as genes escaping XCI. In all the cell types we analyzed, X-linked genes show differential expression across the entire X chromosome in a cluster-like pattern according to gene density and, in certain cell types, correlate strongly with short interspersed nuclear element (SINE) distributions. Conclusions: Our results demonstrate that transcriptional roles of XIST can be highly associated with cell state: stem cells have different transcriptional responses compared to differentiated cells following XIST loss.