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Epidemiological characteristics of ischemic heart disease: A comparative study between China and the world from 1990 to 2021 and prediction to 2036

Background Ischemic heart disease (IHD) is a major disease that endangers human health. There are relatively few comparative studies on the epidemiological characteristics of IHD. Aims This study aimed to compare and analyze the incidence, prevalence and mortality of IHD in China and the world from 1990 to 2021, predict its change trend from 2022 to 2036, and provide a basis for effective prevention and control of IHD. Methods Data on IHD in China and the world, encompassing age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR), and age-standardized mortality rate (ASMR), was extracted from the Global Burden of Disease Study 2021. The Joinpoint regression model was employed to calculate the average annual percentage change (AAPC). The projected data for 2022–2036 were derived through calculations using the Bayesian age-period-cohort model. Results From 1990 to 2021, the growth rates of China’s ASIR, ASPR, and ASMR of IHD were 15.97%, 20.42%, and 17.81% respectively, with annual percentage changes of 0.49%, 0.60%, and 0.49%, all higher than global levels; the annual change rates of incidence, prevalence, and mortality were 3.17%, 3.23%, and 3.54% respectively, also exceeding the world 1.00%, 1.38%, and 0.43%. In 1990, globally and in China, male incidence, prevalence, and mortality of IHD were generally higher than those of females, except that Chinese female mortality was lower; males had higher mortality but lower prevalence and related annual percentage changes, with the disease burden peaking in people aged 80 years and above. Over the next 15 years, the world and Chinese ASMR of IHD is projected to decline, while the male ASIR and ASPR will decrease, and those of females will increase. Conclusions The burden of IHD and the increase rate in China was higher than global figures. Although ASMR for IHD in China and the world will decline over the next 15 years, IHD remains a public health issue that requires ongoing attention.To reduce the burden of IHD, targeted preventive measures and relevant knowledge popularization should be adopted for populations of different genders and ages.

Ventilation and buffering capacity effects on ocean acidification in low oxygen environments

Physicochemical and typological insights into Aedes albopictus and Aedes aegypti larval habitats in a sub-Saharan African urban gradient setting

Therapeutic effects of skin repair plus ointment on molecular and morphological changes in burn wounds: A rat model

Skin Repair Plus Ointment (Remanco) is an advanced formulation of the traditional Jordanian cream, which has been used for treating burn injuries and has served as an alternative remedy in northern Jordan for several decades. In this study, we sought to investigate the therapeutic effects of Remanco on the healing morphology and molecular alterations associated with burn wounds. This randomized controlled experiment involved 90 Wistar rats (160−170 grams) that were randomly assigned to three groups of 30 rats each. The groups were designated as follows: negative control (burn treated with normal saline), positive control (burn treated with 1% silver sulfadiazine), and tested (burn treated with Remanco cream). Burn injuries were inflicted on the shaved dorsum of the rats using a preheated 30-mm-wide circular copper head device. The burns were treated daily with normal saline, 1% silver sulfadiazine, or Remanco cream for 30 days or until the animals were sacrificed. Gross evaluation, histopathological assessment, and RT-PCR Analysis were conducted to evaluate the efficacy of Remanco cream in promoting wound healing. Although there was no statistically significant difference in wound area measurements or histopathological ratings, the cosmetic appearance of the wound area exhibited a significant improvement in the Remanco cream-treated group. Molecular investigations revealed that the Remanco-treated group demonstrated a significant increase in the levels of two essential growth factors: TGF-beta on day 3 and IGF-1 on day 9, with a p-value less than 0.05. In summary, Remanco cream holds potential for enhancing wound healing in animal models, but further studies are necessary to investigate its potential clinical applications.

Pre-marking chromatin with H3K4 methylation is required for accurate zygotic genome activation and development

Abstract In vertebrate embryos, gene expression is first initiated at zygotic genome activation (ZGA). Maternally expressed transcription factors are essential for this process. However, it is unknown whether active chromatin modifications established in gametes are present in early embryos and contribute to ZGA and embryonic development. Here, we show that in Xenopus laevis , H3K4me3 occurs at common genomic loci in gametes, in transcriptionally quiescent pre-ZGA embryos, and in transcriptionally active ZGA embryos. These loci exhibit high H3K4me3 intensities and breadth, DNA hypomethylation, and elevated CpG content. We show that H3K4 methylation pre-marking is required for successful ZGA and development, including expression of the key ZGA transcription factor Pou5f3.2. We demonstrate that the H3K4 methyltransferase Cxxc1 ensures establishment of H3K4me3 and proper ZGA. These findings reveal a role for H3K4 methylation in defining active chromatin states in Xenopus laevis embryos and highlight its importance for accurate ZGA and embryonic development.

Enhancing demarcation in regionalization in the eastern Qinghai-Xizang Plateau through geographically weighted

How similar should collaborators be in inter-organizational learning: Optimal cognitive proximity and knowledge complexity

Effective knowledge exchange is critical for innovation in knowledge-intensive sectors, yet the relationship between cognitive proximity and collaborative innovation remains underexplored in complex knowledge environments. While prior studies confirm a non-linear, inverted U-shaped relationship where moderate similarity balances absorptive capacity and novelty, how this relationship changes with increasing knowledge complexity is poorly understood. This study investigates how knowledge complexity moderates the cognitive proximity-innovation relationship in the U.S. biotechnology sector using a comprehensive dataset of over 650,000 patents from over 57,000 unique assignee organizations spanning 1976 to 2024. We distinguish between two dimensions of collaborative innovation: collaboration volume and collaboration quality. Cognitive proximity was measured through CPC-based Jaccard similarity, while knowledge complexity was operationalized using a structural complexity framework based on knowledge combination networks. Negative binomial regressions reveal that knowledge complexity moderates the proximity-innovation relationship differently across the two dimensions. For collaboration volume, higher complexity shifts the optimal proximity point rightward and flattens the curve while maintaining the inverted U-shape. For collaboration quality, complexity produces a leftward shift and, remarkably, leads to a complete breakdown of the curvilinear relationship at high complexity levels, where the relationship becomes nearly horizontal. These contrasting patterns indicate that cognitive proximity operates through fundamentally different mechanisms in partner selection versus innovation realization. While absorptive capacity considerations dominate partnership decisions even under high complexity, novelty-generating mechanisms become disconnected from proximity effects as complexity rises. The findings refine proximity theory by demonstrating that knowledge complexity serves as a structural moderator and offer actionable insights for partner selection strategies in advanced innovation ecosystems.

Single-molecule microtubule dynamics measurements reveal an intermediate state and clarify the role of nucleotide

Clostridium leptum attenuates allergic airway inflammation via tDC‒Treg axis activation in a murine model of gut dysbiosis-associated asthma

Impact of adherence and stringency on the effectiveness of lockdown measures: A modelling study

During the COVID-19 pandemic, lockdowns were a widely used strategy to reduce disease transmission. However, there was much debate about the optimal level of strictness and duration of lockdowns. This study considers how lockdowns impact public health opinions, which in turn influence adherence to and effectiveness of these measures. We developed an agent-based simulation model to theoretically explore the impact of health-related opinions on the effectiveness of lockdowns in controlling disease spread. We simulated these dynamics within a hypothetical population connected via a simplified contact network (Watts-Strogatz), incorporating feedback loops between disease prevalence, opinions, and behaviour, including ‘lockdown fatigue’. We explored different scenarios of lockdown implementation in our hypothetical population network by varying a threshold value of prevalence when a lockdown is initiated and the stringency of the lockdown. Our qualitative findings imply that quickly imposing a lockdown with high stringency is the most effective at reducing infection spread, provided that there is a certain degree of adherence to the lockdown among the population. Furthermore, stricter lockdowns minimize fatigue with respect to the imposed measures, since the duration of a lockdown is shorter on average in this scenario. These theoretical results imply that such lockdown policies might therefore be a beneficial, high-impact tool in containing epidemic spread, especially when supplemented by information interventions maintaining the adherence to lockdown measures.

Hammerhead: a compact 300 kV vacuum bushing

Exploring potential of Turing pattern classification through convolution maps

Adverse event reporting of mirtazapine: A disproportionality analysis of FDA adverse event reporting system (FAERS) database from 2004–2024

Background Mirtazapine is a pharmacological agent commonly utilized as a first-line treatment for major depressive disorder, exhibiting both noradrenergic and selective serotonergic activity. Currently, there is an absence of a comprehensive and systematic review of the adverse events (AEs) associated with mirtazapine. Consequently, this study aims to assess the safety profile of mirtazapine in real-world clinical practice by performing an in-depth analysis of data from the Food and Drug Administration’s Adverse Event Reporting System (FAERS). Methods This study collected all real-world adverse event data related to mirtazapine from the FAERS database spanning from Q1 2004 to Q4 2024. Disproportionality analysis methods were employed, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-Item Gamma Poisson Shrinker (MGPS), to assess the associations between mirtazapine and major medical events. Results Our study identified a total of 14,237 adverse event reports related to mirtazapine from the FAERS database, of which 2,954 had available data. The results identified several previously unreported adverse events, including prolonged QT interval on electrocardiogram, insomnia, coma, falls, and drug toxicity. AEs related to mirtazapine occurred across 27 system organ classes (SOCs), primarily including Nervous System Disorders, Investigations, and Surgical and Medical Procedures. The onset of adverse events typically occurred within one month of mirtazapine administration, though it is important to note that the risk of AEs persists even in the following year. Conclusion Our research findings are consistent with clinical observations. Additionally, we have identified new adverse reactions related to mirtazapine. These results provide valuable evidence for further guiding safety research on mirtazapine. They also help clinicians place greater emphasis on monitoring its AEs during use.

Molecular basis of ApoER2-mediated Semliki Forest virus entry

AI-assisted identification of innovative phytochemicals from Aizoon canariense aimed at brachyury protein in chordoma: a computational strategy

Fecal microbiota composition and function are associated with anxiety and depression in patients with inflammatory bowel disease

Background and aims Increasing prevalence of anxiety and depression are found in patients with inflammatory bowel disease (IBD). Altered gut microbiome may affect the brain, resulting in psychiatric symptoms. We aimed to analyze the feature of gut microbiota in IBD patients with anxiety or depression. Methods Anxiety and depression symptoms were assessed by the Hospital Anxiety and Depression Scale (HADS). Stool samples were collected from IBD patients, and the 16S rRNA sequencing was used to detect fecal microbiota. Metabolites were detected by Liquid Chromatography-Mass Spectrometry (LC-MS). Results Among the involved IBD patients (n = 59), 28.81% had anxiety and 33.90% had depression. Linear discriminant analysis Effect Size (LEfSe) (LDA > 3.0) revealed that 4 genera ( Klebsiella, Alloprevotella, Barnesiella, Bacillus ) were enriched, while Sellimonas was depleted in the anxiety group. Enrichment of 2 genera ( Ruminococcus, Barnesiella ) were found in the depression group. In the anxiety group, valine, leucine and isoleucine degradation was enriched in fecal microbiota, with upregulation of 3-methyl-2-oxobutanoic acid involved in the above pathway. In the depression group, butanoate metabolism was enriched in fecal microbiota, with alpha-ketoglutaric acid involved. Lysine degradation were enriched in fecal microbiota, with pipecolic acid involved. Primary bile acid biosynthesis was depleted in fecal microbiota, with glycocholic acid involved. Pearson correlation analysis revealed a positive correlation between Alloprevotella and 3-methyl-2-oxobutanoic acid in the anxiety group. In patients with both anxiety and depression, four genera ( Subdoligranulum, Alloprevotella, Christensenellaceae R-7 group, Barnesiella ) were positively correlated with alpha-ketoglutaric acid. Conclusion In this study, the alteration of composition of fecal microbiota was identified, and differential genus associated with IBD patients with anxiety or depression or both were explored. Change in function of microbiota was also discovered by the detection of differential pathways and fecal metabolites, which were associated with IBD patients with anxiety or depression or both.

Endothelial glycosylation and its emerging role in pulmonary vascular health and disease

Quantum coherence in three-level systems under the combined effect of stark effect and non-linear Kerr medium

Machine learning-based risk prediction model for cognitive dysfunction in elderly individuals

Background With the advancement of globalization, the prevalence of cognitive dysfunction in the elderly population has risen significantly. Early intervention may dramatically alleviate the disease burden and reduce economic costs associated with cognitive impairment. This study aims to construct a risk prediction model for cognitive dysfunction based on machine learning (ML) algorithms, providing healthcare professionals and patients with a more accurate and effective tool for risk assessment. Methods This study included 1,325 elderly participants who completed cognitive assessments and comprehensive laboratory blood tests. Risk factors for cognitive dysfunction were identified through univariate analysis, multivariate logistic regression, LASSO regression, and the Boruta algorithm. Nine ML methods—Random Forest (RF), Light Gradient Boosting Machine (LightGBM), Extreme Gradient Boosting (XGBoost), Logistic Regression, K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Artificial Neural Network (ANN), Decision Tree, and Elastic Net—were employed to construct the prediction models. The Shapley Additive Explanations (SHAP) algorithm was utilized to interpret the final model. Results The Random Forest model exhibited the highest predictive performance, with an AUC value exceeding those of other models. SHAP analysis identified age, race, education level, diabetes, and depression as the primary predictors of cognitive dysfunction in the elderly. The calibration curve indicated a strong alignment between the model’s predictions and actual outcomes, while the decision curve confirmed the model’s clinical applicability. Conclusion Age, race, education level, diabetes, and depression are significant influencing factors of cognitive dysfunction in the elderly. Among the ML algorithms evaluated, the Random Forest model exhibited the best predictive performance.

Global coral genomic vulnerability explains recent reef losses

Abstract The dramatic decline of reef-building corals calls for a better understanding of coral adaptation to ocean warming. Here, we characterize genetic diversity of the widespread genus Acropora by building a genomic database of 595 coral samples from different oceanic regions—from the Great Barrier Reef to the Persian Gulf. Through genome-environment associations, we find that different Acropora species show parallel evolutionary signals of heat-adaptation in the same genomic regions, pointing to genes associated with molecular heat shock responses and symbiosis. We then project the present and the predicted future distribution of heat-adapted genotypes across reefs worldwide. Reefs projected with low frequency of heat-adapted genotypes display higher rates of Acropora decline, indicating a potential genomic vulnerability to heat exposure. Our projections also suggest a transition where heat-adapted genotypes will spread at least until 2040. However, this transition will likely involve mass mortality of entire non-adapted populations and a consequent erosion of Acropora genetic diversity. This genetic diversity loss could hinder the capacity of Acropora to adapt to the more extreme heatwaves projected beyond 2040. Genomic vulnerability and genetic diversity loss estimates can be used to reassess which coral reefs are at risk and their conservation.