Search Results (4,846)

Lakes on the Inner Mongolia–Xinjiang Plateau (IMXP) are increasingly vulnerable to eutrophication under climate change and human pressure, yet long-term monitoring remains limited by sparse field sampling. Here, we reconstruct multi-decadal trophic dynamics across the IMXP using Landsat time series and temporally transferable machine-learning models and further quantify the underlying natural and anthropogenic drivers. We compiled monthly in situ water-quality observations (chlorophyll-a, Chl-a; total phosphorus, TP; total nitrogen, TN; Secchi depth, SD; and permanganate index, COD_Mn;) and calculated the trophic level index (TLI). After rigorous quality control and monthly aggregation, we compiled a dataset of 1345 matched lake–month samples spanning 2000–2024, and divided it into a training set (n = 1076; ≤2019) and an independent test set (n = 269; 2020–2024) to evaluate temporal transferability. We utilized Google Earth Engine to generate monthly surface reflectance composites from Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 OLI-2. Four supervised regression algorithms—ridge regression (RR), support vector regression (SVR), random forest (RF), and eXtreme Gradient Boosting (XGBoost)—were trained to estimate TLI. On the independent test period, XGBoost performed best (R² = 0.780, RMSE = 3.290, MAE = 1.779), followed by RF (R² = 0.770, RMSE = 3.364), SVR (R² = 0.700, RMSE = 3.842), and RR (R² = 0.630, RMSE = 4.267); we then used XGBoost to reconstruct monthly and yearly TLI for 610 perennial grassland lakes from 2000 to 2024. From 2000 to 2024, the annual mean TLI (48–49) across the IMXP exhibited a statistically significant upward trend (slope = 0.0158 TLI yr⁻¹; 95% confidence interval (CI) = 0.0050–0.0267; p = 0.006). Meanwhile, spatial heterogeneity was distinct (TLI: 41.51–59.70). High values concentrated in endorheic and desert–oasis basins (e.g., Eastern Inner Mongolia Plateau, >51), whereas lower values characterized high-altitude regions (e.g., Yarkant River, <45). Overall, trends ranged from −0.49 to 0.51 yr⁻¹, increasing in 54% of lakes (15.6% significantly) and decreasing in 46% (15.4% significantly). Attribution analyses identified NDVI (33.92%) and temperature (21.67%) as dominant drivers (55.59% combined), followed by precipitation (13.99%) and human proxies (30.42% combined: population 10.66%, grazing 10.31%, built-up 9.45%). Across 53 sub-basins, NDVI was the primary driver in 28, followed by temperature (11), population (7), precipitation (3), grazing (3), and built-up land (1); notably, the top two drivers explained 56.6–87.1% of variations. TWFE estimates revealed bidirectional NDVI effects (significant in 31/53): positive associations in 22 basins were linked to nutrient retention, contrasting with negative effects in nine basins associated with agricultural return flows. Temperature effects were significant in 15 basins and predominantly negative (14/15), except for the Qiangtang Plateau. Overall, eutrophication risk across the IMXP lake region reflects the combined influences of climatic conditions, vegetation conditions, and human activities, with their relative contributions varying among basins. Full article

Wildfires at the wildland–urban interface (WUI) have increased in frequency and severity under global warming and intensified human activities. As a representative high-altitude mountainous region in southwestern China, Yunnan features complex topography, steep climatic gradients, and dispersed settlements interwoven with wildlands, making it a fire-prone area where wildfire management is particularly challenging. However, a fine-scale WUI dataset is currently lacking for this region. To address this gap, we refined WUI classification thresholds using a one-factor-at-a-time (OFAT) method and generated the first fine-resolution WUI map of Yunnan. Seasonal wildfire driving factors from 2004 to 2023 were quantified, and machine learning models were applied to produce seasonal susceptibility maps. SHapley Additive exPlanations (SHAP) were employed to interpret the dominant contributing factors. The resulting WUI covers 25,730.67 km², accounting for 6.5% of Yunnan’s land area. Random forest models effectively captured seasonal wildfire susceptibility patterns, with AUC values exceeding 0.83 across all seasons. High susceptibility zones (>0.5) comprised 30.09% of the WUI in spring, 25.74% in winter, 22.61% in autumn, and 13.74% in summer. SHAP analysis revealed that anthropogenic factors consistently drive wildfire occurrence, while climatic conditions in the preceding season influence vegetation status and subsequently affect wildfire likelihood in the current season. By integrating static “where” mapping with dynamic “when” susceptibility analysis, this study establishes a comprehensive “When–Where” framework that supports both long-term WUI planning and short-term seasonal early warning. The integration of fine scale WUI mapping with seasonal susceptibility modeling enhances wildfire risk management in complex high-altitude regions. These findings provide a scientific basis for location-specific, time-sensitive, and full-chain wildfire management in mountainous landscapes and contribute to cross-border ecological security governance in the Indo-China Peninsula. Full article

Maritime Autonomous Surface Ships (MASS) are progressing from proof-of-concept to engineering test and initial application phases due to advancements in intelligent sensing, automatic control, and communication technologies. However, numerous studies have shown that the improvement of automation level does not linearly reduce human factor risks. Instead, it exhibits more complex evolutionary characteristics at the medium automation level. In particular, MASS Level 2 (MASS L2) features a “system-dominated, human-supervised” operational mode, and its human factor risks have become one of the key factors restricting the safe operation, large-scale application and sustainable long-term deployment of autonomous ships. This study employs a systematic literature review to analyze 89 core articles (2020–2025) and summarizes the theoretical basis, risk characteristics, and evolutionary trends of human factor risk research in MASS L2. The review results indicate that the current research consensus has gradually shifted from the traditional “human error”-centered explanatory paradigm to a systematic understanding of “information mismatches, opacity, and coupling failures in the human-machine-shore collaborative system”. Typical human factor risks in MASS L2 are mainly manifested as the degradation of supervisory cognition and situation awareness, imbalance in trust in automation, vulnerability in mode switching and takeover, skill degradation, and structural risks in ship-shore collaboration. Based on these findings, this study constructs a classification system and a comprehensive analysis framework for human factor risks in MASS L2, reveals the interaction relationships and dynamic evolution mechanisms among different risk types from a system-level perspective, and further discusses the limitations of existing research in terms of methods, data, and engineering applicability. Finally, considering the development trends of autonomous ship technology, this study proposes future research directions in human factor theoretical modeling, dynamic risk assessment, system design, and operation management. This study aims to provide a systematic knowledge framework for human factor risk research in MASS L2 and offer references for the safety design, safety management, and development of higher-level automation of autonomous ships, while supporting the sustainable and safe advancement of the global intelligent shipping industry. Full article

The tumor suppressor protein p53, encoded by the TP53 gene, is known as the “Guardian of the Genome”, and alterations in TP53 are common to more than 50% of human cancers. p53 is a critical regulator of cellular responses to several stress conditions, such as DNA damage, oncogene activation, and nutrient starvation. p53 was traditionally described as a single transcription factor; however, now it is recognized as a complex family of isoforms generated through alternative promoter usage, alternative splicing, and alternative initiation of translation. These processes give rise to at least 12 distinct p53 isoforms in humans, including p53α (the canonical full-length isoform), p53β, p53γ, Δ40p53, Δ133p53, and Δ160p53, each with unique structural and functional properties. p53 isoforms differ in the presence or absence of specific and fundamental domains located both at N- and C-terminal ends, determining an altered DNA-binding potential, transcriptional activity, and protein–protein interactions. For instance, Δ133p53 isoforms lack part of the N-terminal domains and can exert dominant-negative effects over full-length p53α or modulate alternative transcriptional programs. Similarly, p53β and p53γ isoforms, which have a unique C-termini, influence cellular senescence. The expression patterns of p53 isoforms are tissue-specific and dynamically regulated under both physiological as well as pathological conditions. Alterations of isoform balance have been involved in tumor progression, metastasis, and therapy resistance. Importantly, specific isoforms can either enhance or limit canonical p53 tumor suppressor functions, thereby contributing to the functional diversity of the p53 network. Overall, the p53 isoform landscape adds a critical layer of complexity to p53 biology. In this review, we summarize the mechanisms underlying the production of p53 isoforms, their functions, and their expression in cancer, with the idea that a better understanding of the differential regulation and functional interplay of p53 isoforms may provide novel biomarkers and therapeutic targets in cancer. Full article

Color vision plays a critical role in Diptera behavior, particularly in the detection of oviposition sites. Necrophagous Diptera, like the Calliphoridae, are of forensic importance because the larvae are commonly used to estimate minimum postmortem intervals of human remains. To better understand which species are present, flies are routinely sampled in different habitats using baited traps; however, the influence of trap color on capture efficiency remains poorly understood. In this study, baited bottle traps painted clear, blue, red, and yellow were deployed in wooded habitats to collect adult dipterans. Overall captures were dominated by Lucilia coeruleiviridis (Diptera: Calliphoridae). Clear traps consistently captured a greater diversity of Calliphoridae, Muscidae, and Sarcophagidae. In contrast, yellow traps captured the fewest individuals overall, while red and blue traps yielded intermediate numbers. Dipteran composition in red and yellow traps, however, differed from those in clear traps. Collectively, these results indicate that clear baited traps are more effective for sampling adult necrophagous Diptera, whereas yellow baited traps may be less suitable. Additional investigation is warranted to characterize the complex interactions between visual and olfactory cues underlying attraction and oviposition site selection in necrophagous dipterans. Full article

Artificial Intelligence (AI) is increasingly embedded in project management within the financial sector, yet existing research remains fragmented and largely focused on isolated technical applications. A systemic understanding of how AI reshapes financial project management as an integrated socio-technical capability is still lacking. This study addresses this gap through a systematic literature review of 62 peer-reviewed articles (2022–2025), combined with BERTopic-based thematic analysis supported by large language model-assisted topic representation. The findings reveal the emergence of Agentic AI as a dominant theme, marking a shift from analytical support tools toward autonomous and collaborative agents embedded in project processes. While predictive analytics and automation are relatively mature, governance-oriented and human-centric dimensions remain underdeveloped and weakly integrated. This study contributes by: (1) presenting a computationally enhanced systematic mapping study that integrates a systematic literature review with BERTopic-based topic modelling to map the evolving research landscape; (2) identifying Agentic AI as a pivotal interface between technical execution and strategic governance; and (3) proposing a socio-technical target architecture that offers a structured roadmap for AI-enabled transformation in financial project management systems. Full article

The cervicovaginal microbiome (CVMB) is pivotal in maintaining the homeostasis of the lower female genital tract and has emerged as a significant modulator of cervical carcinogenesis. Although persistent infection with high-risk human papillomavirus (HR-HPV) is a prerequisite for the development of cervical intraepithelial neoplasia (CIN) and subsequent cervical carcinoma, it remains insufficient alone to drive oncogenesis. Accumulating evidence suggests that alterations in the CVMB composition profoundly impact HPV persistence, local immune responses, and disease progression. A vaginal microbiota dominated by Lactobacillus species, most notably Lactobacillus crispatus, correlates with low microbial diversity, robust immune regulation, and facilitated HPV clearance. Conversely, microbial dysbiosis—characterized by Lactobacillus depletion and a concomitant proliferation of anaerobic taxa, typical of Community State Type (CST) IV and Lactobacillus iners-dominated profiles—is strongly associated with chronic inflammation, oxidative stress, epithelial barrier compromise, and an elevated risk of CIN progression. This review synthesizes current evidence regarding the multifaceted interactions among the cervicovaginal microbiome, HPV pathogenesis, immune dysregulation, and oxidative stress in the etiology of CIN. Elucidating these intricate host–microbiome dynamics may precipitate the discovery of novel microbiome-derived biomarkers, ultimately informing innovative prophylactic and therapeutic interventions for cervical cancer. Full article

Low-dose ionizing radiation exposure remains a major challenge for long-term health risk assessment, particularly in retrospective cohorts with heterogeneous exposure scenarios and limited biological material. Although next-generation sequencing (NGS) technologies dominate contemporary molecular research, DNA microarrays remain relevant in radiation biology due to their standardization, reproducibility, cost-effectiveness, and compatibility with archived biospecimens. This narrative review examines the contribution of microarray-based transcriptomic and epigenomic profiling to the study of low-dose radiation effects (≤100 mSv, millisievert), with emphasis on human observational studies, radiation epidemiology, and biodosimetric applications. The literature was identified through targeted searches in PubMed and Web of Science (2000–2025). Evidence from experimental models and exposed populations is synthesized to identify recurrent molecular pathways, major sources of variability, and challenges affecting reproducibility and cross-cohort comparability. Based on this evidence, a conceptual framework is proposed to define conditions under which microarray-based analyses remain interpretable and translationally informative. Machine learning approaches are discussed in a supportive role, with emphasis on interpretability and biological plausibility. Overall, DNA microarrays are positioned as a mature, niche technology that complements next-generation sequencing platforms and remains particularly suited for retrospective cohort studies and long-term molecular monitoring in radiation research. Full article

A substantial proportion of wildfires in Mediterranean regions continue to be recorded without information about the cause or source of ignition, limiting our ability to understand ignition drivers and design effective prevention strategies. In this study, we develop a spatially harmonised wildfire database for mainland Spain by integrating ignition records from the Spanish General Fire Statistics (EGIF) with fire perimeters generated from satellite images. We then apply a Random Forest classifier to infer ignition causes for events lacking cause attribution. To interpret model behaviour, we use Shapley Additive Explanation (SHAP) values at both global and local scales. Results indicate that human-caused ignitions are dominant, with intentional and negligence-related fires accounting for 52.13% of all known events, although they are associated with contrasting climatic and land-use settings. Negligence-related fires tend to occur under hot, dry and windy conditions, often in agricultural interfaces, whereas intentional fires are more frequent under cooler and wetter conditions and in areas with higher population density and land-use change. Lightning-caused fires represent a small fraction of total ignitions (3%) but exhibit a distinct climatic signature, occurring primarily in sparsely populated areas, under intermediate moisture conditions, and often leading to larger burned areas. Despite strong overall model performance (F1-score = 0.82), minority classes (e.g., lightning and fire rekindling, 0.17%) remain challenging to classify, reflecting both data imbalance and uncertainty in causal attribution. Overall, the combined use of machine learning and explainable AI provides a coherent spatial characterisation of wildfire ignition drivers across mainland Spain, highlights systematic differences among ignition causes, and identifies key limitations in existing fire cause records. This framework represents a practical step towards improving fire cause information by integrating remote sensing products with field-based fire reports, thereby supporting more targeted and evidence-based fire risk management. Full article

Eutrophication is a pervasive issue in Mediterranean reservoirs, where external nutrient inputs and internal sediment releases interact to impair water quality and ecological stability. This study assessed the trophic condition of the artificial lake Cuga in Sardinia (Italy), mainly used for irrigation and providing potable water, by integrating watershed nutrient load estimates, inter-lake transfers, and internal phosphorus release. Field campaigns between July 2022 and May 2023 provided bi-monthly measurements of physical, chemical, and biological parameters, complemented by GIS-based land cover analysis and export coefficient modeling to quantify spatial nutrient sources. Additional phosphorus inputs from water transfers with a nearby reservoir were calculated, while internal sediment release was estimated using a calibrated mass balance model. Results revealed high nutrient concentrations, with mean total phosphorus of 128 mg P m⁻³, chlorophyll a averaging 9.9 mg m⁻³, and Secchi depth below 1 m, classifying the reservoir as eutrophic to hypertrophic under OECD and Carlson indices. Spatial loads were dominated by agricultural areas, while inter-lake transfers and internal sediment release contributed substantially to the overall phosphorus budget. The predictive Vollenweider model closely matched the observed conditions, confirming the robustness of the combined approach. Maintaining good ecological status in Mediterranean reservoirs is essential for safeguarding human well-being, as eutrophication degrades drinking-water quality, increases treatment costs, and can promote toxin-producing algal blooms with direct implications for public health. These findings highlight the need for integrated management strategies addressing both external and internal nutrient sources to mitigate eutrophication in Mediterranean reservoirs, which affects the ecosystem functioning and the related human needs and well-being. Full article

Background and objectives: Accurate anatomical knowledge of the transverse dural venous sinuses (TS) is essential for safe neurosurgical procedures, particularly in resource-limited settings where advanced imaging modalities may be unavailable. Despite the TS’s clinical importance, detailed cadaveric studies focusing solely on its morphology are scarce. This study investigated the length, width, and shape of the TS in adult human cadavers, assessing anatomical dominance and morphological variations relevant to surgical planning. Methods: A descriptive, cross-sectional study was conducted on 32 formalin-fixed adult cadavers (20 male, 12 female) at the University of Pretoria in South Africa. The TS was examined bilaterally within the dura mater and the corresponding transverse sulcus. Lengths were measured using a string and a ruler to accommodate curvature, while widths at the origin, midpoint, and termination were measured using digital calipers. Statistical analyses included Shapiro–Wilk tests, paired t-tests, and intra-class correlation to determine significance and reliability. Results: The average TS length was 72.54 mm (left) and 70.23 mm (right), with no statistically significant differences between sides. Right-sided dominance in TS width was observed in 71.88% of cases. A significant narrowing at the midpoint, followed by widening at the termination, was consistently noted, especially in males. Differences between dural and bony groove widths suggested that sulcal impressions may not accurately reflect TS dimensions. Conclusions: The TS demonstrates significant morphological variability, including asymmetry and abrupt dimensional changes. These findings underscore the importance of direct anatomical reference for surgical navigation, particularly in low-resource settings lacking advanced imaging. Full article

Humans face environmental deterioration. Scholars have identified carbon dioxide as one of the culprits, and they emphasize carbon offset. Researchers are investigating carbon offset investments. Some researchers have encouragingly deployed multivariate variational mode decomposition methods, but they have not fully optimized them. Some researchers have opportunely assessed capital asset pricing models, but they have not fully justified them. We devise multiple-objective portfolio selection models, fully optimize them, and dominate carbon offset indexes. We extend the classical methodology of advancing from portfolio selection to capital asset pricing models into the methodology of advancing from multiple-objective portfolio selection to multiple-objective capital asset pricing models. Specifically, we explore multiple-objective capital asset pricing models by numerically verifying many tangent lines (instead of the traditionally singular tangent line) and suggesting a tangent plane (instead of tangent lines). For multiple-objective zero-covariance capital asset pricing models, we numerically compute a set of zero-covariance portfolios (instead of the traditionally singular zero-covariance portfolio) and suggest picking an advantageous zero-covariance portfolio. We consider the second-level indicators of carbon offset and generalize three-objective portfolio selection to k-objective portfolio selection. As for contributions, first, this paper’s methodology is to logically advance from multiple-objective portfolio selection to multiple-objective capital asset pricing models, whereas the literature typically covers multiple-objective portfolio selection alone and barely covers multiple-objective capital asset pricing models. Second, this paper numerically demonstrates some difficulties and proposes hypothetical solutions in the process of obtaining multiple-objective capital asset pricing models. Full article

Background/Objective: Child health serves as a foundational part of human development. Inequities in access to key health services remain high in Sub-Saharan Africa (SSA), most notably among children from disadvantaged, racially, or ethnically marginalized groups. The objective of this structured narrative review is to evaluate and aggregate the available evidence on racial/ethnic disparities in childhood healthcare access in SSA. Methods: A comprehensive search on African Index Medicus (AIM), Web of Science and PubMed for studies published between 2010 and 2025 was executed using relevant MeSH terms and Boolean operators. Studies on healthcare access inequalities among racial or ethnic groups in SSA were included. This study was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: Ten articles were included. Ethnicity was an independent contributor to inequities in childhood healthcare across four domains: vaccination coverage (lower for Hausa/Fulani in Nigeria and Somali/Luhya in Kenya compared to dominant groups), timeliness of vaccination, child mortality (higher in economically and ethnically marginalized groups), and nutritional status (elevated stunting and underweight odds in certain ethnic minorities). Conclusions: Racial and ethnic inequalities in child healthcare access across SSA are driven by multi-factor structural, geographical, and cultural barriers. Although socioeconomic improvement reduces some disparities, it does not eradicate them, highlighting that ethnic identity continues to shape health outcomes independently. Addressing these disparities requires strengthening culturally inclusive healthcare delivery, improving access in underserved regions, and integrating ethnicity-disaggregated monitoring into national health systems. Full article

Background: Chromophobe renal cell carcinoma (ChRCC) is characterized by the accumulation of abnormal mitochondria, a high rate of mitochondrial DNA (mtDNA) mutations, and altered oxidative metabolism. There are no existing circulating biomarkers to distinguish metastatic ChRCC from clear cell renal cell carcinoma (ccRCC). Methods: High-throughput plasma proteomic profiling using the SomaScan platform was performed in 18 ChRCC (including 16 metastatic ChRCC) and 197 metastatic ccRCC patients. Data were harmonized to generate a unified 7K-protein matrix. Results: Differential expression analysis was performed using limma (version 3.62.2). Of 7272 quantified human plasma proteins, 209 were differentially expressed between ChRCC and ccRCC. Upregulated proteins in ChRCC included essential β-oxidation enzymes such as ECH1 (enoyl-CoA hydratase 1) and ECI1 (enoyl-CoA delta-isomerase 1), suggesting increased long-chain fatty acid degradation. Creatine and energy-buffering pathways were also represented, with increased CKMT1A (Creatine Kinase, Mitochondrial 1A) in ChRCC. KIM-1 (Kidney Injury Molecule-1) and leptin were lower in ChRCC, consistent with the known upregulation of these proteins in ccRCC. Pathway enrichment analyses revealed an overrepresentation of mitochondrial protein degradation, fatty acid β-oxidation, and respiratory electron transport in ChRCC, suggesting that ChRCC sheds a unique mitochondrial signature into the peripheral circulation. A bootstrap-based LASSO logistic regression restricted to upregulated mitochondrial proteins in ChRCC vs. ccRCC consistently selected ECI1 and CKMT1A. The LASSO model achieved an AUROC of 0.964. Conclusions: Compared to ccRCC, the plasma proteome of metastatic ChRCC is dominated by mitochondrial metabolic enzymes, revealing a systemic metabolic phenotype strikingly aligned with the known histologic accumulation of abnormal mitochondria in ChRCC cells. Full article

Early life represents a critical developmental programming window during which nutrition and microbial exposures shape long-term physiological function. Feeding mode is a major determinant of infant gut microbiota assembly and metabolic activity. This narrative review synthesizes current evidence comparing breastfeeding (BF) and formula feeding in relation to microbial composition, functional capacity, and immune programming during the preweaning and early postweaning periods. BF may support a relatively stable, bifidobacteria-dominated microbiota enriched in pathways involved in carbohydrate utilization, vitamin biosynthesis, and immune modulation. Human milk oligosaccharides, secretory IgA, lactoferrin, and milk-associated microbes collectively guide microbial succession, enhance barrier integrity, and support immune tolerance. In contrast, formula-fed infants typically exhibit greater microbial diversity, earlier transition toward adult-like profiles, and increased abundance of facultative anaerobes, alongside the enrichment of pathways related to bile acid and amino acid metabolism. Microbiota patterns in formula-fed infants are further influenced by formula composition, including protein load, lipid structure, and supplementation with prebiotics, probiotics, and human milk oligosaccharide analogues. Although advances in formula design have reduced compositional gaps, functional differences in microbial stability and immune programming persist. Recognizing early infancy as a sensitive programming window underscores the need for microbiome-informed nutritional strategies and longitudinal, multi-omics research to clarify causal mechanisms and optimize early-life interventions. Full article