PLoS ONE最新文献

Objective: Explore the causes and mechanisms of bladder cancer-induced Cardiovascular diseases (CVD) death.

Method: We acquired bladder cancer patient data from the SEER database to evaluate CVD death risk. Cross-WGCNA was employed to identify comorbidity genes linking bladder cancer and heart failure. Functional phenotypes of bladder cancer cell lines were analyzed using cell culture, transaction, CCK-8, and Transwell assays, while ELISA determined extracellular target protein concentrations. Myocardial cell function was assessed by examining cell proliferation, collagen I levels, and mitochondrial membrane potential.

Result: Our study, analyzing 140,760 bladder cancer patients from the SEER database, revealed that CVD is a major cause of death, increasing risk by 18%. Cross-WGCNA and Lasso regression identified SFRP1 and CAPG as key serum proteins linked to bladder cancer and heart failure. Regulating these proteins' mRNA levels significantly impacts cancer proliferation, migration, and invasion. CAPG, in particular, suppresses myocardial cell function. We discovered SB525334 as a strong CAPG inhibitor in bladder cancer cells, potentially enhancing cisplatin's effectiveness by targeting CAPG.

Conclusion: Bladder cancer patients face an elevated CVD death risk due to high CAPG protein expression, which can raise serum CAPG levels and harm cardiomyocytes.

[This corrects the article DOI: 10.1371/journal.pone.0320632.].

Accurately predicting the dynamic thermal rating of power lines is the core of overcoming the bottleneck in the engineering application of line dynamic capacity - increase technology. In response to the limitations of DTR data decomposition caused by the existing methods relying on manual experience to set the hyperparameters of the Variational Mode Decomposition algorithm, and the problems of single models, such as their inability to accurately extract multi - scale time - series features of DTR data and poor generalization ability, this paper proposes a transmission line DTR prediction method driven by an improved VMD and based on a time - varying multi - model ensemble. First, by constructing a fitness function based on the minimum envelope entropy of DTR data components, a mathematical mapping relationship between the hyperparameter space and the VMD decomposition effect is established. This transforms the traditional experience - oriented hyperparameter selection into a quantifiable optimization problem for solution. Subsequently, the global search ability of the slime mold algorithm is utilized to iteratively search for the optimal hyperparameters of VMD in the hyperparameter space. Second, by integrating the dynamic recursive characteristics of Elman and the multi - scale convolutional feature extraction advantages of TCN, a time - varying ensemble model is constructed to accurately extract the long - and short - term time - series features of DTR data. In particular, a dynamic weighting mechanism based on grey relational coefficients is designed. By quantifying the local correlation between the predicted values of the Elman model and the TCN model and the real values point - by - point, the weights can be adaptively allocated, effectively solving the problem of insufficient generalization ability of single models. Experimental results show that the proposed method maintains a prediction accuracy of over 95% in different datasets, which is 5.7% higher than that of the best traditional methods. It provides more theoretical support for the safe capacity increase of power lines and has significant engineering application value.

North-Western Europe heated greenhouses need to address their high fossil energy dependency while they start to face with climate change. In this context, physics-based greenhouses dynamic models can be used for prospective assessments of innovative shapes, equipment, control, etc. A prerequisite for such model-based evaluation is a review of existing implementations, the improvement and development of suitable sub-models in a generic and modular approach that do not require calibration, and the evaluation of a use case global model with a solid experimental dataset. First, this paper details contributions to existing models regarding several aspects: solar gain, boundaries effects, airflows and leakages, heat and mass transfer. The second part is dedicated to the evaluation of an experimental tomato greenhouse global model for an 11-month period. Its assessment is multiphysics: indoor climate, utilities consumptions, yield and Leaf Area Index. The resulting 5 min sampling indoor air climate Root Mean Square Error is 1.3 °C (temperature) and 8.1%RH (relative humidity). The tomato yield Mean Absolute Error is 1.1 kg m-2. Mass balances also quantify the losses and potentials for water and CO2. The global model outputs are compared with literature, and it is demonstrated that assessing the accuracy of models based only on statistical indicators is questionable. This approach is compatible with assessments of prospective solutions, it increases the confidence for scaling results from small to large commercial greenhouses, and it constitutes a base from which simpler and black box models can be derived for other applications such as predictive control.

High-intensity interval training (HIIT) is an effective intervention for improving metabolic health and mitigating metabolic dysfunction-associated steatotic liver disease (MASLD). Nonetheless, the stability of these benefits throughout detraining periods and upon weight regain remains inadequately characterized. This study aimed to evaluate whether hepatic improvements induced by HIIT are sustained during detraining, even after body weight regain. Eighty male C57BL/6 mice were fed either a control (10% fat) or a high-fat (HF) diet (50% fat) for 12 weeks. Following this period, the animals were allocated to groups subjected to continuous HIIT or intermittent training cycles (each lasting 3 weeks). The outcomes assessed included body mass (BM), glucose tolerance, lipid profiles, liver enzyme levels (aspartate aminotransferase and alanine aminotransferase), hepatic steatosis, and the expression profiles of genes associated with lipogenesis (Srebf1, Mlxpl, and Fas), β-oxidation (Ppara and Cpt1a), and endoplasmic reticulum (ER) stress (Atf4, Ddit3, and Gadd45). Compared with the sedentary HF-NT condition, continuous HIIT reduced BM and improved glucose tolerance. Intermittent training (HF-TNT, HF-NTN) preserved metabolic benefits and reduced triglyceride and cholesterol levels. Notably, hepatic steatosis was significantly alleviated in all training groups but persisted even after detraining. Additionally, HIIT downregulated the expression of lipogenic genes and upregulated the expression of genes involved in β-oxidation. The levels of markers indicating ER stress were attenuated by HIIT, with a sustained reduction during periods of detraining. HIIT-induced metabolic and hepatic improvements persist partially during detraining, despite weight regain. These findings underscore the therapeutic value of continued or periodically repeated physical training in mitigating the adverse effects of an HF diet and preventing the progression of metabolic disorders such as MASLD.

[This corrects the article DOI: 10.1371/journal.pone.0313285.].

Purpose: In today's highly dynamic environment, the ability of entrepreneurs to accurately recognize and quickly respond to opportunities plays an important role in their entrepreneurial performance. Entrepreneurial improvisation has gained wide attention. Based on the Stimulus-Organism-Response Theory, this study aims to examine the influence mechanism and boundary conditions of exploratory learning on entrepreneurial improvisation.

Design/methodology/approach: Based on a two-wave survey of 303 members from five entrepreneurial platforms in mainland China, the dual moderating effects of environmental dynamism and risk-taking propensity on the relationship between exploratory learning and entrepreneurial improvisation were validated. Data analysis was conducted using SPSS 26.0, Amos 26.0, and Process 4.0 software, covering mediation effects, moderation effects, and moderated mediation effects.

Findings: Opportunity identification mediated the relationship between exploratory learning and entrepreneurial improvisation. Environmental dynamism positively moderated the relationship between exploratory learning and entrepreneurial improvisation. Risk-taking propensity negatively moderated the relationship between exploratory learning and entrepreneurial improvisation.

Research implications: Exploratory learning can facilitate entrepreneurial improvisation by enhancing opportunity identification. In a high dynamic environment, individuals with low risk-taking propensity are more likely to show higher entrepreneurial improvisation due to exploratory learning and opportunity identification.

Originality: The study can contribute to a more comprehensive understanding of the formation and boundary conditions of entrepreneurial improvisational behaviors. It can also provide further empirical support for research on improvisation in entrepreneurship.

[This corrects the article DOI: 10.1371/journal.pone.0057724.].

[This corrects the article DOI: 10.1371/journal.pone.0327157.].

Trypsin, a canonical serine protease in crustaceans, plays a crucial role in ontogeny and antibacterial defense. Whether these biological functions correlate with its catalytic characteristics remains unresolved in the freshwater shrimp Neocaridina denticulata sinensis. To address this gap, we characterized a trypsin gene from N. denticulata sinensis (NdTryp) and assessed both its biological roles and its prospective utility. NdTryp was predominantly expressed in the hepatopancreas, where it localized to storage cells (R-cells) and tubule-lining epithelial cells (ECTs). Across development, NdTryp transcripts were essentially absent during early embryogenesis but rose sharply at late stages, temporally coincident with hatching and the onset of feeding. After a challenge with Vibrio parahaemolyticus, the expression of NdTryp was induced, with the expression level significantly increased relative to the baseline expression level. RNA interference-mediated knockdown rendered shrimp more susceptible to infection and was accompanied by extensive hepatopancreatic injury, including epithelial detachment and disruption of the basement membrane. Biochemically, recombinant NdTryp (rNdTryp) displayed proteolytic activity over a broad temperature and pH span. Activity was differentially tuned by metal ions, with several divalent cations producing marked enhancement, whereas ferric iron exerted strong inhibition. Overall, our results showed that NdTryp functions as a multifunctional protease involved in both late embryonic development and innate antimicrobial defense. Furthermore, the robust stability of rNdTryp underscores its potential as an aquafeed additive and candidate for enzymatic biotransformation.