Search Results (3,305)

Background/Objectives: Eating disorders (EDs) are complex psychopathological conditions involving dysfunctional eating behaviors, excessive body image concerns, and impaired emotional regulation. Among moral emotions, guilt plays a significant role in ED dynamics, influencing both symptomatology and interpersonal relationships. This study examines specific guilt subtypes (normative and altruistic guilt) using a specific psychometric tool. Methods: Forty-three adults with anorexia nervosa (AN), bulimia nervosa (BN), or binge eating disorder (BED) were recruited from the Eating Disorder Center of the University of Campania “Luigi Vanvitelli” or referred by psychotherapists. Diagnoses followed DSM-5 criteria. Participants completed the Moral Orientation Guilt Scale (MOGS), assessing guilt subtypes, and the Eating Disorder Inventory-2 (EDI-2), measuring ED symptomatology. Spearman’s rank correlation and stepwise multiple regression analyses were used to identify relationships between guilt dimensions and ED-related symptoms. Results: MOGS subscales were positively correlated with ED symptomatology. Normative guilt was significantly associated with binging and purging (ρ = 0.26, p < 0.05), while altruistic guilt predicted higher interpersonal distrust (t = 3.4, p < 0.01). Regression analysis revealed that age negatively influenced interpersonal distrust (t = −2.9, p < 0.01). Conclusions: In the population examined, guilt significantly influences ED symptomatology and interpersonal functioning, with specific dimensions linked to distinct behaviors and traits. Therapeutic interventions targeting guilt may enhance treatment outcomes by addressing ED emotional underpinnings. However, the results should be interpreted with caution due to the small sample size and lack of longitudinal data to establish causality. Further research with larger samples and longitudinal designs is necessary to validate these findings. Full article

To effectively mitigate service slope disaster risks in mountainous areas and enhance the overall safety of highway operations, based on the geological and structural characteristics of slopes, considering slope technical conditions, overall stability, and potential disaster consequences, 25 important influencing factors are systematically identified. The identification process integrates insights from the relevant literature, expert opinions, and historical disaster maintenance records of such slopes. An integrated approach combining Interpretive Structural Modeling (ISM) and Bayesian Networks (BNs) is utilized to conduct a quantitative analysis of the interrelationships and impact strength of factors influencing the disaster risk of mountainous service highway slopes. The aim is to reveal the causal mechanism of slope disaster risk and provide a scientific basis for risk assessment and prevention strategies. Firstly, the relationship matrix is constructed based on the relevant prior knowledge. Then, the reachability matrix is computed and partitioned into different levels to form a directed graph from which the Bayesian network structure is constructed. Subsequently, the expert’s subjective judgment is further transformed into a set of prior and conditional probabilities embedded in the BN to perform causal inference to predict the probability of risk occurrence. Real-time diagnosis of disaster risk triggers operating slopes using backward reasoning, sensitivity analysis, and strength of influence analysis capabilities. As an example, the earth excavation slope in the mountainous area of Anhui Province is analyzed using the established model. The results showed that the constructed slope failure risk model for mountainous operating highways has good applicability, and the possibility of medium slope failure risk is high with a probability of 34%, where engineering geological conditions, micro-topographic landforms, and the lowest monthly average temperature are the main influencing factors of slope hazard risk for them. The study not only helps deepen the understanding of the evolutionary mechanisms of slope disaster risk but also provides theoretical support and practical guidance for the safe operation and disaster prevention of mountainous highways. The model offers clear risk information, serving as a scientific basis for managing service slope disaster risks. Consequently, it effectively reduces the likelihood of slope disasters and enhances the safety of highway operation. Full article

To mitigate the risk of hydrogen leakage in ship fuel systems powered by internal combustion engines, a Bayesian network model was developed to evaluate the risk of hydrogen fuel leakage. In conjunction with the Bow-tie model, fuzzy set theory, and the Noisy-OR Gate model, an in-depth analysis was also conducted to examine both the causal factors and potential consequences of such incidents. The Bayesian network model estimates the likelihood of hydrogen leakage at approximately 4.73 × 10⁻⁴ and identifies key risk factors contributing to such events, including improper maintenance procedures, inadequate operational protocols, and insufficient operator training. The Bow-tie model is employed to visualize the causal relationships between risk factors and their potential consequences, providing a clear structure for understanding the events leading to hydrogen leakage. Fuzzy set theory is used to address the uncertainties in expert judgments regarding system parameters, enhancing the robustness of the risk analysis. To mitigate the subjectivity inherent in root node probabilities and conditional probability tables, the Noisy-OR Gate model is introduced, simplifying the determination of conditional probabilities and improving the accuracy of the evaluation. The probabilities of flash or pool fires, jet fires, and vapor cloud explosions following a leakage are calculated as 4.84 × 10⁻⁵, 5.15 × 10⁻⁵, and 4.89 × 10⁻⁷, respectively. These findings highlight the importance of strengthening operator training and enforcing stringent maintenance protocols to mitigate the risks of hydrogen leakage. The model provides a valuable framework for safety evaluation and leakage risk management in hydrogen-powered ship fuel systems. Full article

This paper aims to enhance the sensitivity of fiber-optic surface plasmon resonance (SPR) sensors by innovatively applying TRIZ (Theory of Inventive Problem Solving). To identify the key challenges faced by current SPR sensors, methods such as functional analysis, causal analysis, and the Nine-Window method are employed. Utilizing TRIZ tools, including Technical Contradiction, Physical Contradiction, the Smart Little Man method, and object–field analysis, innovative solutions are proposed, involving transparent indium tin oxide (ITO) thin films, an asymmetric photonic crystal fiber structure with elliptical pores, and titanium dioxide (TiO₂) thin films. Experimental results reveal a significant improvement in sensitivity, with an average of 9961.90 nm/RIU and a peak of 12,503.56 nm/RIU within the refractive index range of 1.33061 to 1.40008, representing a 456% increase compared to the original gold-film fiber-optic SPR sensor. These findings have potential applications in biosensing, environmental monitoring, and food safety. Full article

The high-quality development of specialized, refined, distinctive, and innovative enterprises (SRDIEs) is essential for advancing an innovation-driven strategy. This paper investigates the impact of financial technology (Fintech) on sustainable innovation within SRDIEs that face financing challenges, analyzing it from supply-side, demand-side, and environmental perspectives. We utilize fuzzy-set Qualitative Comparative Analysis (fSQCA) and Necessary Condition Analysis (NCA) to explore the configurational paths and complex causal effects of Fintech in facilitating the innovation of SRDIEs amid financing challenges. By employing a combination of NCA and fsQCA, this study identifies several effective pathways through which Fintech enhances the innovation efficiency of SRDIEs. We develop an integrative model to enhance innovation inputs, outputs, and sustainability. The key findings include the following: (1) Fintech significantly enhances innovation output, supported by business efficiency and digital intelligence; (2) two distinct pathways for achieving high-innovation inputs are identified, driven by Fintech intensity and effective credit allocation, with specialization and financial mismatches serving as auxiliary factors; (3) the core conditions of Fintech intensity and the financing environment, along with competitive banking, promote innovation motivation and sustainability in highly specialized enterprises. The conclusions of this study provide both theoretical and practical insights for SRDIEs to tackle innovation challenges characterized by an “inability to innovate”, a “lack of willingness to innovate”, and “ineffectiveness in innovation”, enabling their transition from merely being “able to innovate” and “daring to innovate” to becoming “proficient in sustainable innovation”. These findings offer differentiated sustainable innovation solutions for enterprises through three avenues: capacity building on the demand side, channel optimization on the supply side, and ecological cultivation on the environmental side. Full article

Genetic variants increase the risk of neurocognitive disorders in later life, including vascular dementia (VaD) and Alzheimer’s disease (AD), but the precise relationships between genetic risk factors and underlying disease etiologies are not well understood. Transcriptome-wide association studies (TWASs) can be leveraged to better characterize the genes and biological pathways underlying genetic influences on disease. To date, almost all existing TWASs on VaD and AD have been conducted using expression studies from individuals of a single genetic ancestry, primarily European. Using the joint likelihood-based inference framework in Multi-ancEstry TRanscriptOme-wide analysis (METRO), we leveraged gene expression data from European ancestry (EA) and African ancestry (AA) samples to identify genes associated with general cognitive function, white matter hyperintensity (WMH), and AD. Regions were fine-mapped using Fine-mapping Of CaUsal gene Sets (FOCUS). We identified 266, 23, 69, and 2 genes associated with general cognitive function, WMH, AD (using EA GWAS summary statistics), and AD (using AA GWAS), respectively (Bonferroni-corrected alpha = p < 2.9 × 10⁻⁶), some of which had been previously identified. Enrichment analysis showed that many of the identified genes were in pathways related to innate immunity, vascular dysfunction, and neuroinflammation. Further, the downregulation of ICA1L was associated with a higher WMH and with AD, indicating its potential contribution to overlapping AD and VaD neuropathology. To our knowledge, our study is the first TWAS on cognitive function and neurocognitive disorders that used expression mapping studies for multiple ancestries. This work may expand the benefits of TWASs beyond a single ancestry group and help to identify gene targets for pharmaceuticals or preventative treatments for dementia. Full article

Background: Prostate cancer, as an androgen-dependent malignant tumor in older men, has attracted the attention of a wide range of clinicians. BCR remains a significant challenge following early prostate cancer treatment. Methods: The specific expression pattern of the Anoikis gene set in prostate cancer cells was first explored by single-cell and spatial transcriptomics analysis. Genes causally associated with prostate cancer were screened using Summary-data-based Mendelian Randomization (SMR). Subsequently, we explored the role and mechanism of CASP8 in prostate cancer cells and defined a new cell type: the CASP8 T cell. We constructed a prediction model that can better predict the BCR of prostate cancer, and explored the differences in various aspects of clinical subgroups, tumor microenvironments, immune checkpoints, drug sensitivities, and tumor-immune circulations between high- and low-risk groups. The results of SMR analysis indicated that CASP8 could increase the risk of prostate cancer. Based on the differential genes of CASP8-positive and -negative T cells, we constructed a four-gene prognostic model with a 5-year AUC of 0.713. Results: The results revealed that high-risk prostate cancer BCR patients had various characteristics such as higher tumor purity, higher BCR rate, downregulated SIRPA immune checkpoints, and unique drug sensitivity. Conclusions: In summary, CASP8 may be a potential biomarker for prostate cancer. Full article

Viral infections have been a severe challenge for global public health, and viral pneumonia is becoming increasingly critical in the post-pandemic era. Observational and basic studies have demonstrated a strong link between host nutrient status and anti-viral immune responses, and nutritional supplements were shown to improve the prognosis of viral infectious diseases. However, there is limited research on the relationship between essential micronutrients and the susceptibility to viral pneumonia. In addition, current studies are often confounded by biases and reverse causality, undermining their reliability. In this study, to fill the gap, we employed Mendelian randomization to investigate the causal relationship between supplementation of vitamins and minerals and the susceptibility to viral pneumonia. Our analysis found that vitamin B6 is a protective factor against viral pneumonia, while selenium supplementation is a risk factor. These findings provide insights for the use of dietary supplements and the prevention and control of viral pneumonia, especially when micronutrient supplementation is used as an adjunctive therapy for viral infections. Full article

This study investigated the relationships between air pollutants (PM₁₀, SO₂, NO₂, O₃, CO) and meteorological parameters (wind speed, relative humidity, ambient temperature) across urban, suburban, and industrial areas in Malaysia from 2017 to 2021. Using data from six monitoring stations, this research employed descriptive analysis, trend analysis, and Granger causality testing to uncover complex interactions. The results revealed distinct patterns: suburban areas showed strong ambient temperature-ozone (p-value = 0.0063) and relative humidity–nitrogen dioxide relationships (p-value = 0.0411); industrial zones exhibited bidirectional causality between SO₂ and PM₁₀ and had a strong nitrogen dioxide–PM₁₀ relationship (p-value = 0.0292); urban areas exhibited complex multi-pollutant interactions. Notably, the 2020 Movement Control Order significantly improved air quality. This research provides crucial insights for targeted air quality management strategies, contributing to public health improvements and aligning with global sustainability goals. Full article

Chloroplast biogenesis is a crucial biological process in plants. Endoribonuclease E (RNase E) functions in the RNA metabolism of chloroplast and plays a vital role for chloroplast development in Arabidopsis. However, despite sharing 44.7% of its amino acid sequence identity with Arabidopsis RNase E, the biological function of rice OsRNE (Oryza sativa RNase E) remains unknown. Here, we identified a white leaf and lethal 1 (wll1) mutant that displayed white leaves and died at the seedling stage. The causal gene OsRNE was isolated by MutMap+ method. CRISPR/Cas9-mediated knockout of OsRNE resulted in white leaves and seedling lethality, confirming OsRNE as the causal gene for the wll1 phenotype. The albino phenotype of osrne mutant was associated with decreased chlorophyll content and abnormal thylakoid morphology in the chloroplast. The absence of OsRNE led to a significant reduction in the Rubisco large subunit (RbcL), and the 23S and 16S chloroplast rRNAs were nearly undetectable in the osrne mutant. OsRNE transcripts were highly expressed in green tissues, and the protein was localized to chloroplasts, indicating its essential role in photosynthetic organs. Furthermore, transcriptome analysis showed that most of the genes associated with photosynthesis and carbohydrate metabolism pathways in the osrne mutant were significantly down-regulated compared with those in WT. Chlorophyll- and other pigment-related genes were also differentially expressed in the osrne mutant. Our findings demonstrated that OsRNE plays an important role in chloroplast development and chlorophyll biosynthesis in rice. Full article

This study investigated market efficiency across 20 major commodity assets, including crude oil, utilizing fractal analysis. Additionally, a rolling window approach was employed to capture the time-varying nature of efficiency in these markets. A Granger causality test was applied to assess the influence of crude oil on other commodities. Key findings revealed significant inefficiencies in RBOB(Reformulated Blendstock for Oxygenated Blending) Gasoline, Palladium, and Brent Crude Oil, largely driven by geopolitical risks that exacerbated supply–demand imbalances. By contrast, Copper, Kansas Wheat, and Soybeans exhibited greater efficiency because of their stable market dynamics. The COVID-19 pandemic underscored the time-varying nature of efficiency, with short-term volatility causing price fluctuations. Geopolitical events such as the Russia–Ukraine War exposed some commodities to shocks, while others remained resilient. Brent Crude Oil was a key driver of market inefficiency. Our findings align with Fractal Fractional (FF) concepts. The MF-DFA method revealed self-similarity in market prices, while inefficient markets exhibited long-memory effects, challenging the Efficient Market Hypothesis. Additionally, rolling window analysis captured evolving market efficiency, influenced by external shocks, reinforcing the relevance of fractal fractional models in financial analysis. Furthermore, these findings can help traders, policymakers, and researchers, by highlighting Brent Crude Oil as a key market indicator and emphasizing the need for risk management and regulatory measures. Full article

The effects of certain abilities on financial outcomes have been debated for several years. Some argue that financial knowledge is key to financial success, while others have found financial skill and self-assessed knowledge are more important. This study contributes to this debate by providing a descriptive analysis, whereby regression is used to study the simultaneous effects of financial knowledge, financial skill, and self-assessed knowledge on financial well-being, financial behavior, and objective financial situation. Although our methodology does not allow us to determine if relationships are causal, we show that self-assessed knowledge has little to no relationship with financial well-being, may have contrasting relationships with components of objective financial situation, and is weakly associated with good financial behaviors. Financial skill has the strongest relationship with financial well-being and financial behaviors, as well as some components of objective financial situation. Despite having a relatively weak (compared to financial skill) association with financial well-being and financial behaviors, financial knowledge has the strongest relationship with many components of objective financial situation. Full article

The average daily gain (ADG) is a critical index for evaluating growth rates in cattle and is closely linked to the economic benefits of the cattle industry. Heredity is one of the factors affecting the daily gain of cattle. However, the molecular mechanisms regulating ADG remain incompletely understood. This study aimed to systematically unravel the molecular mechanisms underlying the divergence in ADG between high average daily gain (HADG) and low average daily gain (LADG) Angus cattle through integrated multi-omics analyses (microbiome, metabolome, and transcriptome), hypothesizing that the gut microbiota–host gene–metabolism axis is a key regulatory network driving ADG divergence. Thirty Angus cattle were classified according to their HADG and LADG. Fecal and serum samples were collected for 16S, fecal metabolome, and blood transcriptome analysis. The results showed that compared with the LADG group, the abundance of Firmicutes increased in the HADG group, while the abundance of Bacteroidetes and Proteobacteria decreased. Metabolomics and transcriptomic analysis revealed that KEGG pathways associated with differentially expressed genes (DEGs) and differentially abundant metabolites (DAMs) were enriched in bile acid metabolism. Spearman correlation analysis showed that Oscillospira was positively correlated with ZBTB20 and negatively correlated with RADIL. ZBTB20 was negatively correlated with dgA-11_gut_group. This study analyzed the regulatory mechanism of average daily gain of beef cattle from genetic, metabolic, and microbial levels, providing a theoretical basis for analyzing the mechanism of differential daily gain of beef cattle, and has important significance for improving the production performance of beef cattle. The multi-omics network provides biomarker foundations for machine learning-based ADG prediction models, offering potential applications in precision breeding. While these biomarkers show promise for precision breeding, their causal roles require further validation. The conclusions are derived from a single breed (Angus) and gender (castrated males). Future studies should include females and diverse breeds to assess generalizability. Full article

Background/Objectives: Despite substantial research, the causal relationships between gut microbiota (GM) and age-related macular degeneration (AMD) remain unclear. We aimed to explore these causal associations using Mendelian randomization (MR) and elucidate the potential mechanisms mediated by blood metabolites. Methods: We utilized the 211 GM dataset (n = 18,340) provided by the MiBioGen consortium. AMD outcome data were sourced from the MRC Integrated Epidemiology Unit (IEU) OpenGWAS Project. We performed bidirectional MR, two mediation analyses, and two-step MR to assess the causal links between GM and different stages of AMD (early, dry, and wet). Results: Our findings indicate that the Bacteroidales S24.7 group and genus Dorea are associated with an increased risk of early AMD, while Ruminococcaceae UCG011 and Parasutterella are linked to a higher risk of dry AMD. Conversely, Lachnospiraceae UCG004 and Anaerotruncus are protective against dry AMD. In the case of wet AMD, Intestinimonas and Sellimonas increase risk, whereas Anaerotruncus and Rikenellaceae RC9 reduce it. Additionally, various blood metabolites were implicated: valine, arabinose, creatine, lysine, alanine, and apolipoprotein A1 were associated with early AMD; glutamine and hyodeoxycholate—with a reduced risk of dry AMD; and androsterone sulfate, epiandrosterone sulfate, and lipopolysaccharide—with a reduced risk of wet AMD. Notably, the association between family Oxalobacteraceae and early AMD was mediated by valine, accounting for 19.1% of the association. Conclusions: This study establishes causal links between specific gut microbiota and AMD, mediated by blood metabolites, thereby enhancing our understanding of the gut–retina axis in AMD pathophysiology. Full article

Soybean is particularly known for accumulating saponins in its seeds. This study aimed to identify a causal gene to control an increase in Ab-γg saponin in PE1607 from an EMS-treated population of the soybean cultivar Pungsannamul. Segregation analysis in F₂ seeds verified that a single recessive allele controlled the increased Ab-γg saponin in PE1607. Bulk segregant analysis and mutant individuals identified the candidate region, containing the previously reported Sg-3 (Glyma.10G104700) gene, encoding a glucosyltransferase responsible for conjugating glucose as the third sugar at the C-3 position of the aglycone. NGS identified SNPs in the upstream of the Sg-3 gene, designated as the sg-3b allele. Expression analysis revealed that PE1607 exhibited a threefold decrease in Sg-3 expression in the hypocotyls compared to the Pungsannamul. Moreover, Sg-3 expressions significantly differed between the hypocotyls and cotyledons in developing seeds, with relatively low expression observed in the cotyledons. The results conclude that sg-3b allele may contribute to the reduced Sg-3 expression, resulting in an increase in Ab-γg saponin in PE1607. In addition, in the cotyledons, DDMP-βg and DDMP-βa saponins are present, containing rhamnose instead of glucose as the third sugar at the C-3 position of aglycone. This suggests that Sg-3, known as glucosyltransferase, does not significantly contribute to saponin biosynthesis in cotyledons. Full article