Volume 138

Meditative states provide a unique window into intrinsic neural activity, yet the spectral and spatial dynamics of resting-state EEG during meditation remain incompletely understood. This study examined how gender, age, and meditation experience influence EEG band power and spatial coherence during eyes-closed meditation. Twenty-four participants (12 experienced meditators, 12 novices) completed a resting meditation task while 64-channel EEG data were recorded. Epochs preceding self-report prompts were extracted, and power spectral density (PSD) was computed for five canonical frequency bands (delta, theta, alpha, beta, gamma). Analyses revealed that gender consistently predicted band power—males showed elevated beta, whereas females exhibited higher gamma and delta—while age and meditation experience had minimal effects. Inter-channel correlation matrices indicated strong inter-hemispheric synchrony and local coherence. Segment-wise one-sample t-tests across five temporal blocks demonstrated robust and temporally stable gamma-band enhancement, particularly in frontal and parietal regions; beta activity was selectively enhanced in males, and delta increases appeared in females and older adults. Meditation experience influenced only minor topographic patterns without significantly altering power. These results suggest that high-frequency gamma activity is a stable marker of resting-state cortical dynamics during meditation, modulated by gender and age but not substantially by prior training. The consistent spatial and temporal patterns highlight the stability and individuality of intrinsic brain states, contributing to mapping resting-state neural signatures and informing future research on attention, self-referential processing, and mindfulness-based interventions.

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Diabetes mellitus and heart failure are two common chronic conditions that frequently coexist, producing outcomes worse than either disease alone. This paper investigates how diabetes directly impairs the myocardium, leading to a distinct syndrome often termed diabetic cardiomyopathy, and examines the reciprocal influence of both disorders. Evidence from clinical and experimental studies highlights altered myocardial metabolism, oxidative stress, glycation pathways, calcium dysregulation, mitochondrial injury, inflammatory signaling, and autonomic imbalance as contributors to structural and functional decline. Analysis of pharmacological data shows that sodium–glucose cotransporter-2 inhibitors consistently improve outcomes across heart failure phenotypes, while glucagon-like peptide-1 receptor agonists offer benefits mainly in obesity-related HFpEF. By contrast, several older glucose-lowering drugs may worsen congestion or remain neutral in prognosis. The review concludes that diabetes and heart failure form a complex, self-reinforcing network, and that targeted treatment strategies grounded in mechanistic understanding are critical for advancing patient care and clinical outcomes.

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DNA replication, as the foundation of genetic information transmission and the continuity of life, relies on high fidelity and dynamic regulatory mechanisms that are central to maintaining genome stability. Through literature analysis, this review systematically summarizes the core molecular mechanisms of DNA replication initiation, elongation, proofreading, and repair, while comparing the commonalities and differences between prokaryotic and eukaryotic systems. Comparative analysis demonstrates that while prokaryotic and eukaryotic DNA replication share conserved high-fidelity principles, they exhibit fundamental mechanistic divergences. Advances in technologies such as cryo-electron microscopy have uncovered the structure and dynamics of the replication machinery and its coupling with epigenetic regulation. Future research should employ integrative multi-omics approaches to decipher the spatiotemporal regulation of replication, facilitating therapeutic interventions for replication-associated pathologies including cancer.

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Meiosis is a pivotal biological process essential for the generation of haploid gametes and the preservation of genomic integrity across generations. Caenorhabditis elegans has emerged as a powerful model for dissecting the molecular and cellular mechanisms of meiosis due to its unique combination of genetic tractability, optical transparency, and synchronized gonad architecture. This review summarizes the key advantages of Caenorhabditis elegans, including its compact and well-annotated genome, versatile genetic manipulation tools (e.g., RNAi, CRISPR/Cas9), and in vivo imaging capabilities that enable high-resolution observation of meiotic events. We highlight recent insights into homolog pairing, synapsis, crossover control, spindle assembly, and meiotic checkpoint regulation, emphasizing the coordinated actions of conserved and nematode-specific factors such as pairing centers, synaptonemal complex components, and regulatory networks involving CHK-2, MAD-1/MAD-2, and PCH-2. While limitations exist—such as its self-fertilizing reproductive mode and holocentric chromosome structure—ongoing advancements in imaging, multi-omics, and synthetic biology continue to enhance its applicability. Caenorhabditis elegans thus remains a valuable and forward-looking system for unraveling the principles of meiosis with implications for fertility, genome maintenance, and developmental biology.

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Crocetin is a natural carotenoid compound with biological activities such as antioxidant, antiviral and anticancer, but its poor water solubility limits its application. To improve the solubility and bioavailability of crocetin and enable it to be more active, researchers have developed a variety of different crocetin solubilization techniques. This article reviews the research on crocetin solubilization techniques in recent years, with the aim of laying the foundation for the development and industrial application of crocetin.

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Safe water is essential for public health, but environmental waters frequently contain viral contaminants. Molecular detection methods, particularly Polymerase Chain Reaction (PCR)-based approaches, have transformed water quality monitoring by providing rapid and sensitive analysis without the need for cultivation. This review focuses on two major technologies: quantitative PCR (qPCR) and digital PCR (dPCR). qPCR remains widely used for virus surveillance, source tracking, and infectivity assessments, while dPCR offers absolute quantification, improved tolerance to inhibitors, and greater precision for low-level targets. Both methods require quantitative criteria for performance evaluation and face some challenges, including matrix inhibition, lack of viability confirmation, and the need for standardized workflows. Future progress is expected through improved robustness, more efficient sample processing, enhanced multiplexing, and integration with risk modeling and viability assays. Continued reductions in cost and gains in throughput may broaden access to dPCR, and the complementary use of qPCR and dPCR can further strengthen water quality surveillance and public health protection.

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Culex tritaeniorhynchus is a primary vector of Japanese encephalitis and other diseases, with population dynamics highly sensitive to climatic conditions. Predicting its distribution relies on understanding the correlation between mosquito density and meteorological factors. In this study, the Random Forest model, an innovative machine learning approach for classification and regression, was used to simulate monthly variations in mosquito density around key future time points (2030 and 2090). Simulations integrated four CMIP6 scenarios (SSP126, SSP245, SSP370, and SSP585). Results indicated an overall increase in peak mosquito density over time, accompanied by a delayed seasonal peak. Significant density variations were observed across scenarios, with the highest radiative forcing scenario (SSP585) exhibiting the most pronounced increase: by August 2090, mean density reached 0.51 ± 0.01 mosquitoes/(lamp·hour), and the maximum monthly density rose to 1.09 mosquitoes/(lamp·hour). Under the SSP370 scenario, the mean density in August 2090 was also elevated, at 0.52 ± 0.01 mosquitoes/(lamp·hour). These findings suggest that climate change will substantially increase the density of Culex tritaeniorhynchus and shift its seasonal peak, potentially exacerbating public health and ecological risks. This study represents a methodological advance from traditional vector distribution forecasting to quantitative density prediction, providing a critical foundation for precise early warning and control of mosquito-borne diseases in high-risk regions. It offers practical implications for safeguarding public health.

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