Search Results (8,755)

This study examines the dynamics of information dissemination and opinion formation in Indonesian social media through a comprehensive analysis of a high-profile youth violence case. Using social network analysis (SNA), we analyzed 264,155 activities from 83,097 accounts on platform X (formerly Twitter) to understand the patterns of information flow, cluster formation, and inter-group interactions. The analysis revealed four distinct clusters with unique characteristics: a dominant support cluster (40.12%), a context-focused cluster (26.93%), a mainstream media cluster (14.14%), and a peripheral engagement cluster (6.05%). This study found significant patterns in information dissemination, with retweets dominating at 68% of total activities and strategic hashtag usage at 28%. Cross-cluster interactions comprised 20% of total activities, challenging assumptions about echo chambers in digital discourse. The network showed high resilience with 85% path reliability and demonstrated a consistent multiplier effect with a 1:5:15 ratio in message amplification. Bridge nodes (10–15% of accounts) played crucial roles in facilitating cross-cluster dialogue and maintaining network cohesion. The temporal evolution of discourse showed distinct phases, from initial factual reporting to later systemic analysis, with each phase characterized by different engagement patterns and narrative focuses. These findings extend existing theoretical frameworks while highlighting the need for more culturally nuanced approaches to understanding digital discourse in contexts of collectivist cultural dimensions. This study’s results have significant implications for digital literacy education, social media intervention strategies, and youth violence prevention efforts, suggesting the need for sophisticated, network-aware approaches that consider both structural dynamics and cultural contexts. Full article

The urban heat island (UHI) effect has emerged in the literature as a major challenge to urban well-being, primarily driven by increasing urbanization. To address this challenge, this study investigates the spatiotemporal pattern of the UHI in the fast-growing city of Kisangani and within its urban–rural gradient from 2000 to 2024 using land surface temperature (LST) data from the MODIS 11A2 V6.1 product. Inferential and descriptive statistics were applied to examine the patterns of UHI and the relationships between the LST, building volume density (BVD), and vegetation density expressed by the Normalized Difference Vegetation Index (NDVI). The results showed that the spatial extent of the moderate UHI gradually increased from 16 km² to 38 km², while the high UHI increased from 9 km² to 19 km². Furthermore, although high UHI values (0.2 < UHI ≤ 0.3) are observed in urban areas and significant differences in UHI variations are detected across urban, peri-urban, and rural zones, the results indicate that the mean UHI in Kisangani’s urban areas remains below 0.2. Therefore, based on average UHI variations, Kisangani’s urban zones exhibit moderate disparities in LST compared to rural areas. Moreover, the LST variations significantly correlate with the building volume and vegetation densities. However, the influence of vegetation density as a predictor of LST gradually decreases while the influence of building volume density increases over time, suggesting the need to implement a synergistic development pathway to manage the interactions between urbanization, landscape change, and ecosystem service provision. This integrated approach may represent a crucial solution for mitigating the UHI effect in regions categorized as high-temperature zones. Full article

The comparative analysis of the feeding ecology among sympatric small carnivores reveals both differentiation and overlap in resource utilization patterns, which serves as a critical pathway for understanding interspecific interactions and maintaining ecosystem stability. In this study, we collected fecal samples from sympatric Pallas’s cats (Otocolobus manul, n = 26) and red foxes (Vulpes vulpes, n = 13) within the Sanjiangyuan National Park (SNP) in China. Subsequently, DNA barcoding technology was employed to analyze the dietary composition and interspecific differences of these two small carnivores. The results demonstrated that both species primarily prey on plateau pikas (Ochotona curzoniae) and small rodents. Despite a high trophic niche overlap between Pallas’s cats and red foxes (O_jk = 0.81), interspecific competition is mitigated through differentiate feeding proportions of shared prey species. Furthermore, the trophic niche breadth of red foxes (B = 267.89) exceeds that of Pallas’s cats (B = 162.94), reflecting a greater diversity of prey resources utilized by red foxes. Consequently, the two small carnivores achieve sympatric coexistence via differentiated resource utilization. These findings enhance our understanding of the coexistence mechanisms within carnivore communities and provide a scientific basis for the conservation of wildlife in the SNP. Full article

The COVID-19 pandemic has highlighted the need for a comprehensive understanding of the factors influencing disease severity and progression. Emerging research indicates that the human microbiota, particularly beneficial bacteria, significantly impacts immune responses and health outcomes in COVID-19 patients. While existing studies provide general insights into the relationship between the microbiota and probiotics with COVID-19, they often lack a detailed exploration of how specific bacterial taxa might be used as adjunctive treatments. This review aims to address this gap by focusing on ten key genera of beneficial bacteria, discussing their roles in COVID-19 and evaluating their potential as probiotics for prevention and treatment. The review covers the impact of these microbes on human health, their population alterations in COVID-19 patients, and their interactions with other viral infections. Among these microbes, several exhibit distinct patterns of abundance in COVID-19 patients, influencing disease outcomes and highlighting their potential roles in infection dynamics. In COVID-19 patients, populations of Akkermansia, Ruminococcus, and Roseburia are consistently reduced, while those of Faecalibacterium show a significant decline in more severe cases. Bacteroides presents varying effects depending on the species involved. Alterations in the abundance of Blautia and Lachnospiraceae are associated with increased inflammation and disease severity. Likewise, the depletion of Lachnospira and Coprococcus populations, both linked to anti-inflammatory effects, may exacerbate symptom severity. Oscillospira, though less studied, is connected to overall health and could have implications for viral infections. This review synthesizes the current understanding of these beneficial microbes to highlight the importance of maintaining a healthy microbiota to alleviate the impact of COVID-19 and contribute to the development of novel therapeutic strategies involving microbiota modulation. Full article

In the mid-1970s, it was revealed that the 5′ end of the RNA genome of poliovirus (PV) was covalently linked to a peptide called VPg (viral protein, genome-linked). Subsequently, VPgs have been found attached to many other viruses and even phages. This review summarizes the patterns of physicochemical properties that are conserved within the VPgs of plus-strand RNA viruses where short-peptide VPgs have been identified. Mutagenesis and structural data indicate the importance of a 5 aa conserved motif at the N-termini of picornaviral VPgs (around the tyrosine 3 residue, which forms a covalent bond to UMP and the RNA). Hidden Markov models have been used to find motifs and VPgs in additional genera of picornaviruses, as well as dicistroviruses in insects and comoviruses in plants. These latter VPgs are bound to the RNA termina through linkages to serine or threonine. The role of free VPg and VPgpU needs clarification, especially in light of multiple genome copies in many of the viruses. Lysine and other positively charged side chains are hallmarks of VPgs. These may contribute to interactions with the viral RNA, polymerase, membranes and cellular proteins. The larger protein VPgs from potyviruses and noroviruses/caliciviruses may also show some areas of similar properties to these small peptides. Full article

Background: Gut microbiota play a critical role in mediating the bidirectional association between cancer and depression. Emerging evidence indicates that adjusting the dietary component intake can significantly alter gut microbiota composition, thereby influencing the host’s metabolism and immune function. Changes in gut microbiota and their metabolites may represent key factors in preventing cancer–depression comorbidity. Methods: English publications were searched in databases including the Web of Science, Scopus, and PubMed using a series of keywords: “cancer”, “depression”, “gut microbiota”, “dietary components”, and related terms, individually or in combination. The search focused on preclinical and clinical studies describing the regulatory effects of dietary component interventions. Results: This narrative review summarizes the associations among gut microbiota, cancer, and depression, and synthesizes current evidence on the modulatory effects and mechanisms of specific dietary component interventions, including dietary patterns, probiotics, prebiotics, and diet-derived phytochemicals, on gut microbiota. On the one hand, these interventions inhibit abnormal proliferation signals in the tumor microenvironment and enhance anticancer immune responses; on the other hand, they modulate neurotransmitter homeostasis, suppress neuroinflammation, and improve mood behaviors through the gut–brain axis interactions mediated by microbial metabolites. Conclusions: The complex associations among cancer, depression, and gut microbiota require further clarification. Modulating gut microbiota composition through dietary components represents a novel therapeutic strategy for improving cancer–depression comorbidity. Regulated gut microbiota enhance immune homeostasis and intestinal barrier function, while their metabolites bidirectionally modulate one another via systemic circulation and the gut–brain axis, thereby improving both the tumor microenvironment and depressive-like behaviors in cancer patients while reducing the adverse effects of cancer. Full article

Placental development plays a pivotal role in ensuring successful pregnancy outcomes, yet its molecular regulatory mechanisms in sheep remain poorly characterized. This study aimed to systematically investigate stage-specific proteomic dynamics and functional adaptations in ovine placental tissues across gestation to elucidate molecular drivers of placental maturation. Using data-independent acquisition proteomics, we identified 7774 proteins in Hu sheep placental tissues at gestational days 50, 80, and 120. Comparative analysis revealed 1450, 1026, and 1964 differentially expressed proteins (DEPs) in the 50 d vs. 80 d, 80 d vs. 120 d, and 50 d vs. 120 d comparisons, respectively. DEPs were functionally enriched in biological processes including cell proliferation, apoptosis, angiogenesis, nutrient transport, and steroid synthesis, with prominent involvement of the PI3K-Akt, MAPK, and estrogen signaling pathways. Protein interaction networks identified SRC, MAP3K1, KRAS, and TJP1 as central regulators exhibiting dynamic expression patterns across gestation. Temporal expression trends showed progressive upregulation of tight junction, immune response, and glucose metabolism proteins, contrasting with downregulation of endoplasmic reticulum protein processing and proteasome components. Validation experiments confirmed elevated proliferation/transport gene expression at 80 d versus 50 d, followed by increased apoptosis/transport genes and decreased proliferation markers at 120 d. This comprehensive proteomic profiling reveals stage-specific regulatory networks governing placental development in sheep, highlighting coordinated shifts in proliferative, metabolic, and structural remodeling processes. These findings advance our understanding of placental adaptation mechanisms and provide valuable insights for improving reproductive management in livestock species. Full article

Autism spectrum disorder (ASD) is a neurodevelopmental condition that affects social interactions, communication, and behavior. Prompt and precise diagnosis is essential for prompt support and intervention. In this study, a deep learning-based framework for diagnosing ASD using facial images has been proposed. The methodology begins with logarithmic transformation for image pre-processing, enhancing contrast and making subtle facial features more distinguishable. Next, feature extraction is performed using NasNetMobile and DeiT networks, where NasNetMobile captures high-level abstract patterns, and the DeiT network focuses on fine-grained facial characteristics relevant to ASD identification. The extracted features are then fused using attentional feature fusion, which adaptively assigns importance to the most discriminative features, ensuring an optimal representation. Finally, classification is conducted using bagging with a support vector machine (SVM) classifier employing a polynomial kernel, enhancing generalization and robustness. Experimental results validate the effectiveness of the proposed approach, achieving 95.77% recall, 95.67% precision, 95.66% F1-score, and 95.67% accuracy, demonstrating its strong potential for assisting in ASD diagnosis through facial image analysis. Full article

Neurodegenerative disorders such as Alzheimer’s disease (AD), the most common form of dementia, represent a growing global health crisis, yet current treatment strategies remain primarily palliative. Recent studies have shown that neurodegeneration through complex interactions within the gut–brain axis largely depends on the gut microbiota and its metabolites. This review explores the intricate molecular mechanisms linking gut microbiota dysbiosis to cognitive decline, emphasizing the impact of microbial metabolites, including short-chain fatty acids (SCFAs), bile acids, and tryptophan metabolites, on neuroinflammation, blood–brain barrier (BBB) integrity, and amyloid-β and tau pathology. The paper highlights major microbiome signatures associated with Alzheimer’s disease, detailing their metabolic pathways and inflammatory crosstalk. Dietary interventions have shown promise in modulating gut microbiota composition, potentially mitigating neurodegenerative processes. This review critically examines the influence of dietary patterns, such as the Mediterranean and Western diets, on microbiota-mediated neuroprotection. Bioactive compounds like prebiotics, omega-3 fatty acids, and polyphenols exhibit neuroprotective effects by modulating gut microbiota and reducing neuroinflammation. Furthermore, it discusses emerging microbiome-based therapeutic strategies, including probiotics, prebiotics, postbiotics, and fecal microbiota transplantation (FMT), as potential interventions for slowing Alzheimer’s progression. Despite these advances, several knowledge gaps remain, including interindividual variability in microbiome responses to dietary interventions and the need for large-scale, longitudinal studies. The study proposes an integrative, precision medicine approach, incorporating microbiome science into Alzheimer’s treatment paradigms. Ultimately, cognizance of the gut–brain axis at a mechanistic level could unlock novel therapeutic avenues, offering a non-invasive, diet-based strategy for managing neurodegeneration and improving cognitive health. Full article

High-mobility group box 1 (HMGB1) is a nuclear protein that can be secreted or released into the extracellular environment during cellular stress, functioning as a damage-associated molecular pattern molecule. This study investigates the role of HMGB1 in adipocyte development and metabolism, explicitly examining its interaction with β3-adrenergic receptor-mediated lipolysis and caveolin-1 (CAV1) regulation, which may influence cardiovascular risk factors. Using 3T3-L1 preadipocytes and mouse embryonic fibroblasts, we demonstrated that HMGB1 expression increases progressively during adipogenesis, reaching peak levels in mature adipocytes. While exogenous HMGB1 treatment did not affect preadipocyte proliferation or differentiation, it inhibited lipolysis in mature adipocytes. Mechanistically, HMGB1 suppressed β3-adrenergic receptor agonist CL-316,243-induced hormone-sensitive lipase activation by reducing protein kinase A-mediated phosphorylation and attenuating extracellular signal-regulated kinase signaling without affecting upstream cyclic AMP levels. We discovered a novel regulatory mechanism wherein CAV1 physically interacts with HMGB1 in mature adipocytes, with c-Src-dependent CAV1 phosphorylation functioning as a negative regulator of HMGB1 secretion. This finding was confirmed in CAV1-deficient models, which displayed increased HMGB1 secretion and diminished lipolytic activity both in vitro and in vivo. Furthermore, administering HMGB1-neutralizing antibodies to wild-type mice enhanced fasting-induced lipolysis, establishing circulating HMGB1 as a crucial antilipolytic factor. These findings reveal HMGB1’s previously uncharacterized role in adipose tissue metabolism as a negative regulator of lipolysis through CAV1-dependent mechanisms. This work provides new insights into adipose tissue metabolism regulation and identifies potential therapeutic targets for obesity-related metabolic disorders and cardiovascular diseases. Full article

The interaction between rural household livelihood strategies and land use behavior constitutes the core of the human–land relationship in a region, especially in protected area villages with high ecological sensitivity that require the integration of social–economic and ecological benefits. This study, grounded in the concept of sustainable livelihoods, utilizes survey data from 399 households in the Chang-Zhu-Tan Green Heart Ecological Protection Zone. By employing the entropy method to calculate indicator weights, a coupling coordination degree model is constructed to analyze the coupling degree, coordination degree, and spatial differentiation patterns between household livelihood strategies and land use behavior. The findings reveal that (1) there is a coupling relationship between household livelihood strategies and land use behavior in the protected area, characterized by moderate coupling coordination. (2) Agricultural sideline households exhibit the highest degree of coupling coordination. The sideline activities of these households not only enhance income but also exert positive impacts on the ecological environment while they are engaged in agricultural production. (3) There is a significant spatial differentiation in the coupling coordination degree of different types of households in the protected area: it increases with the distance from the urban center, with higher values in the central areas than in the peripheral regions. The results of this study provide a basis for understanding micro-level land use changes and guiding household land use behavior, as well as offering theoretical and practical references for improving sustainable livelihoods of households in the study area, promoting rural revitalization, and implementing ecological protection policies. Full article

Over the past two decades, research on residential segregation and environmental justice has evolved from spatial assimilation models to include class theory and social stratification. This study leverages recent advances in machine learning to examine how environmental, economic, and demographic factors contribute to ethnic segregation, using Las Vegas as a case study with broader urban relevance. By integrating traditional econometric techniques with machine learning and deep learning models, the study investigates (1) the correlation between housing prices, environmental quality, and segregation; (2) the differentiated impacts on various ethnic groups; and (3) the comparative effectiveness of predictive models. Among the tested algorithms, LGBM (Light Gradient Boosting) delivered the highest predictive accuracy and robustness. To improve model transparency, the SHAP (SHapley Additive exPlanations) method was employed, identifying key variables influencing segregation outcomes. This interpretability framework helps clarify variable importance and interaction effects. The findings reveal that housing prices and poor environmental quality disproportionately affect minority populations, with distinct patterns across different ethnic groups, which may reinforce these groups’ spatial and economic marginalization. These effects contribute to persistent urban inequalities that manifest themselves in racial segregation and unequal environmental burdens. The methodology of this study is generalizable, offering a reproducible framework for future segregation studies in other cities and informing equitable urban planning and environmental policy. Full article

In recent years, rapid urbanization in China has significantly altered land use patterns and surface properties, exacerbating the urban heat island (UHI) effect. This study investigates the microclimatic regulation potential of small lakes and their interaction with three distinct underlying surfaces (granite roads, lawns, and woodlands). Hourly measurements of air temperature and relative humidity were conducted from 15 July to 15 August 2024, at Tianlai Lake. The results demonstrate that granite roads exhibited the highest daytime air temperatures due to their low albedo and specific heat capacity. In contrast, lawns and woodlands can reduce surrounding temperatures via latent heat dissipation. The lake’s cooling influence extended approximately 30 m from its boundary, with the air temperature decreasing by up to 2 °C near the shoreline. Relative humidity showed a negative correlation with distance from the lake, declining rapidly within 30 m. These findings highlight the role of small lakes in mitigating UHI effects and provide actionable insights for optimizing lakeside underlying surface planning in urban areas. Full article

Rural livability is the essence of people’s well-being and rural revitalization, in which social networks in daily life play important roles. However, the role of social interactions has long been ignored. This study aims to develop an index system for rural livability evaluation considering social interactions. We chose Ezhou city as an example, and two potential social networks were constructed, and the multi-scale characteristics of social networks at the village level and patch level were used as the proxy indicator of social convenience, then together with ecological livability and economic vitality to comprehensively evaluate rural livability. The empirical results showed a heterogeneous spatial distribution in two social networks. It also presented a tendency of “poor social convenience, general economic vitality and benign ecological livability” of rural areas in each dimension, and a complex pattern of stripped and concentric distribution in the spatial distribution of the total rural livability. It further verified that the social interactions had a direct impact on rural livability by a comparison of two evaluation results. This study advances our understanding of the role of social interactions in rural livability evaluation and provide reasonable suggestions for policymakers in future construction of livable countryside. Full article

Urban activities are a significant source of global carbon emissions. Balancing economic development and environmental protection during urban construction and development has become a common concern worldwide. The urban form structure, as the spatial foundation of urban activities, is critical for both current and future urban development. In this study, an urban economic activities perspective is taken to examine the relationship between the urban form structure and carbon emission efficiency in 63 prefecture-level cities within China’s three major urban agglomerations from 2013 to 2022. Two dimensions are considered: land resource development and the urban spatial layout. The research findings indicate that (1) the built-up areas of the three major urban agglomerations in China generally exhibit a pattern of “core cities expanding outwards and peripheral cities emerging sporadically”. (2) Various urban form structure indicators have different effects on carbon emission efficiency, with interaction detection via geographic detectors showing a dual-factor enhancement effect. (3) Urban form structure influences carbon emission efficiency through the mediating pathway of economic agglomeration. This study enriches empirical research on the impact of the urban form structure on carbon emission efficiency from an economic activities perspective and provides empirical evidence for urban spatial planning and achieving sustainable development. Full article