Scientific Reports最新文献

Sunflower (Helianthus annuus L.) is a valuable oilseed crop with significant economic importance. Enhancing breeding strategies in this species heavily relies on genetic diversity and molecular tools. Among these tools, SNP-based genotyping has proven to be an effective method for exploring genomic variation and understanding population structure in plants. This study aimed to evaluate the genetic diversity, population structure, and identify genomic regions under selection within a panel of sunflower inbred lines. A 10 K SNP (single-nucleotide polymorphism) array was employed to examine genetic variation among 94 sunflower inbred lines. The results showed that SNPs were unevenly distributed across the 17 sunflower chromosomes, with a higher density observed in telomeric regions. The average transition-to-transversion ratio was 3.75, confirming the reliability and quality of the genotypic data. Analysis of population structure revealed two distinct subgroups, as supported by the results from STRUCTURE, PCoA, and WPGMA methods. AMOVA revealed that 16% of total genetic variance occurred among populations (Fst = 0.156), and overall genetic diversity was moderate to high (PPL = 92.94%). A total of 283 potential genes were linked to genomic areas that were under selection. Functional enrichment analysis revealed significant involvement of these genes in proteasome activity and pyruvate metabolism pathways. The findings validate the presence of considerable genetic diversity and moderate genetic differentiation within the studied sunflower germplasm. This study reports, for the first time, the use of the Fst statistic to identify pathways that contribute to population differentiation and are under selection pressure in a panel of sunflower inbred lines. These results provide valuable insights that could inform future sunflower breeding efforts through marker-assisted selection and offer insights into the genetic mechanisms underlying adaptation and population divergence in sunflower.

Caviar/roe, widely valued in modern cuisine, is little characterized regarding its complete metabolite composition. Existing studies focused primarily on specific classes e.g., lipids and proteins. This study represents the first extensive GC-MS metabolite profiling of 48 caviar/roe samples from 10 commercially important taxa, including male and female aquatic animals. One hundred thirty-nine primary and secondary metabolites were identified and quantified belonging to fatty, amino, and organic acids, sugars, nitrogenous compounds, and steroids/terpenoids. Multivariate data analysis further uncovered clear interspecies and gender-specific metabolic differences. OPLS-DA highlighted palmitic acid and cholesterol as discriminative markers for sturgeon caviar, while serine and urea distinguished salmon roe. Gender differences were evident in Charybdis natator roe, with males enriched in amino acids and females in fatty metabolites. This comprehensive caviar/roe metabolite map proposes male gilt-head bream Sparus aurata and female common cuttlefish Sepia officinalis for further investigation of their potential functional food applications, driven by their rich omega-3 PUFA levels. Specifically, S. officinalis roe presents good fat source being rich in γ-tocopherol, with favorable n-3/n-6 ratio. The rich content of pyroglutamic acid in S. aurata may contribute to its characteristic umami taste encouraging further sensory analysis. The findings strengthen the molecular basis for improved quality assessment and nutritional labeling of caviar/roe products.

Earthquakes are measured using well-defined seismic parameters such as seismic moment ([Formula: see text]), moment magnitude ([Formula: see text]), and released elastic energy (E). However, the mechanism by which this tremendous energy accumulates deep within the Earth's crust remains unclear and is one of the most fundamental open questions in seismological research. We investigate a quantitative link between earthquake radiated energy and the generalized Pourbaix electrochemical potential. This analysis forms the basis of a theoretical electrochemical framework for assessing whether electrical processes may contribute to earthquake nucleation. An intriguing similarity has been found between the released energy in an earthquake and Pourbaix potential in a redox reaction at an oxide-aqueous interface. A mathematical equivalence is established to strengthen this connection. This provides new insights into the possible electrochemical mechanism underlying seismic processes. Hydrated smectite, a clay mineral with a distinctive layered structure, is a dominant source of electrochemical potential generation in the Earth's crust. Observations of significant smectite abundance in various deep drilling projects indirectly support this assertion. The layered arrangement of these hydrated clay minerals enables the formation of multiple electrochemical cells, leading to substantial accumulation of electrochemical potential. This observation indicates the presence of electrical potential in the earthquake preparation zone, which may offer a more comprehensive explanation for earthquake lights, negative anomalies in atmospheric electric fields, ionospheric perturbations, and other associated phenomena observed before or during an earthquake.

For cardiovascular diseases, diabetes, and asthma, the positive effects of dog ownership are shown. Cancer is a leading cause of death, but the influence of dogs on cancer incidence and survival is not well examined. As modifiable lifestyle factors gain importance in cancer survivorship research, the potential protective role of dog ownership warrants systematic investigation. We retrospectively analyzed clinical data from a federated global health research network, focusing on patients diagnosed with cancer (International Classification of Diseases (ICD-10): C00-D49). From these, we generated two cohorts with contact with dogs (cohort 1) and one without (cohort 2). After propensity score matching for age and sex, a total of about 55,000 patients were included. Analysis of the matched cohort demonstrated that dog ownership was significantly associated with reduced 5-year all-cause mortality in cancer patients compared to non-owners (RR = 0.44). Survival analysis revealed a significantly higher 5-year cumulative survival rate among dog-owning patients versus non-owners, with a hazard ratio (HR) of 0.36. Contact with dogs is associated with a 64% relative risk reduction in cancer mortality, potentially mediated by increased physical activity, psychosocial support, and microbiome modulation. While retrospective design precludes causal inference, this first large-scale matched cohort study provides compelling epidemiological evidence warranting prospective validation.

Accurate classification of cancer-related biomedical abstracts is critical for advancing cancer informatics and supporting decision-making in healthcare research. Yet progress in this domain is often constrained by limited availability of labeled corpora and the high computational demands of transformer-based approaches. To address these challenges, we propose a Residual Graph Attention Network (R-GAT) that integrates multi-head attention with residual connections to capture semantic and relational dependencies in biomedical texts. Evaluated on a curated dataset of 1,875 PubMed abstracts spanning thyroid, colon, lung, and generic cancer topics, R-GAT achieves stable and competitive performance (macro-F1: 0.96 ± 0.01), comparable to transformer-based models such as BioBERT and BioClinicalBERT and strong classical baselines like Logistic Regression, while requiring significantly fewer computational resources. Ablation studies confirm the importance of attention and residual connections in ensuring robustness under limited-data conditions. To support reproducibility and facilitate future research, we also release the curated dataset. Together, these contributions demonstrate the value of lightweight graph-based architectures as reliable and resource-efficient alternatives to computationally intensive transformers in biomedical NLP.