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"Chan, Liu"
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Disulfidptosis-related gene in acute myocardial infarction and immune microenvironment analysis: A bioinformatics analysis and validation
Disulfidptosis is a newly discovered method of cell death. However, no studies have fully elucidated the role of disulfidptosis-related genes (DSRGs) in acute myocardial infarction (AMI). The potential role of DSRGs in AMI was analyzed through a comprehensive bioinformatics approach. Finally, hub genes were verified in vitro by qPCR. Sixteen DE-DSRGs were in the AMI. Thereafter, seven hub genes were determined by machine learning algorithms, which had potential diagnostic value in AMI. The risk model showed a robust diagnostic value (area under curve, AUC = 0.940). Prognostic analysis revealed the potential prognostic value of INF2 and CD2AP. Immune landscape analysis showed that hub genes were closely related to the immune microenvironment. By predictive analysis, we obtained four miRNAs, thirteen small molecule drugs, and five TFs closely related to hub genes. Experimental verification revealed that Slc3a2 and Inf2 were significantly up-regulated and Dstn was significantly down-regulated in the hypoxic model. Our study demonstrated that DSRGs are disorderedly expressed in AMI and identified seven hub genes through machine learning. In addition, a diagnostic model was constructed based on hub genes, providing a new perspective for the early diagnosis of AMI.
Journal Article
The triglyceride–glucose index and its obesity-related derivatives as predictors of all-cause and cardiovascular mortality in hypertensive patients: insights from NHANES data with machine learning analysis
Background
Hypertension (HTN) is a global public health concern and a major risk factor for cardiovascular disease (CVD) and mortality. Insulin resistance (IR) plays a crucial role in HTN-related metabolic dysfunction, but its assessment remains challenging. The triglyceride–glucose (TyG) index and its derivatives (TyG–BMI, TyG–WC, and TyG–WHtR) have emerged as reliable IR markers. In this study, we evaluated their associations with all-cause and cardiovascular mortality in hypertensive patients using machine learning techniques.
Methods
Data from 9432 hypertensive participants in the National Health and Nutrition Examination Survey (NHANES) 1999–2018 were analysed. Cox proportional hazards models and restricted cubic splines were employed to explore mortality risk and potential nonlinear relationships. Machine learning models were utilized to assess the predictive value of the TyG index and its derivatives for mortality outcomes.
Results
The TyG index and its derivatives were independent predictors of both all-cause and cardiovascular mortality in hypertensive patients. The TyG–WHtR exhibited the strongest association, with each 1-unit increase linked to a 41.7% and 48.1% higher risk of all-cause and cardiovascular mortality, respectively. L-shaped relationships were observed between TyG-related indices and mortality. The incorporation of the TyG index or its derivatives into predictive models modestly improved the prediction performance for mortality outcomes.
Conclusions
The TyG index and its derivatives are significant predictors of mortality in hypertensive patients. Their inclusion in predictive models enhances risk stratification and may aid in the early identification of high-risk individuals in this population. Further studies are needed to validate these findings in external hypertensive cohorts.
Journal Article
Establishment of an Agrobacterium‐mediated genetic transformation and CRISPR/Cas9‐mediated targeted mutagenesis in Hemp (Cannabis Sativa L.)
Summary Hemp (Cannabis sativa L.) is an annual and typically dioecious crop. Due to the therapeutic potential for human diseases, phytocannabinoids as a medical therapy is getting more attention recently. Several candidate genes involved in cannabinoid biosynthesis have been elucidated using omics analysis. However, the gene function was not fully validated due to few reports of stable transformation for Cannabis tissues. In this study, we firstly report the successful generation of gene‐edited plants using an Agrobacterium‐mediated transformation method in C. sativa. DMG278 achieved the highest shoot induction rate, which was selected as the model strain for transformation. By overexpressing the cannabis developmental regulator chimera in the embryo hypocotyls of immature grains, the shoot regeneration efficiency was substantially increased. We used CRISPR/Cas9 technology to edit the phytoene desaturase gene and finally generated four edited cannabis seedlings with albino phenotype. Moreover, we propagated the transgenic plants and validated the stable integration of T‐DNA in cannabis genome.
Journal Article
In-Field Tobacco Leaf Maturity Detection with an Enhanced MobileNetV1: Incorporating a Feature Pyramid Network and Attention Mechanism
The maturity of tobacco leaves plays a decisive role in tobacco production, affecting the quality of the leaves and production control. Traditional recognition of tobacco leaf maturity primarily relies on manual observation and judgment, which is not only inefficient but also susceptible to subjective interference. Particularly in complex field environments, there is limited research on in situ field maturity recognition of tobacco leaves, making maturity recognition a significant challenge. In response to this problem, this study proposed a MobileNetV1 model combined with a Feature Pyramid Network (FPN) and attention mechanism for in situ field maturity recognition of tobacco leaves. By introducing the FPN structure, the model fully exploits multi-scale features and, in combination with Spatial Attention and SE attention mechanisms, further enhances the expression ability of feature map channel features. The experimental results show that this model, with a size of 13.7 M and FPS of 128.12, performed outstandingly well on the task of field maturity recognition of tobacco leaves, achieving an accuracy of 96.3%, superior to classical models such as VGG16, VGG19, ResNet50, and EfficientNetB0, while maintaining excellent computational efficiency and small memory footprint. Experiments were conducted involving noise perturbations, changes in environmental brightness, and occlusions to validate the model’s robustness in dealing with the complex environments that may be encountered in actual applications. Finally, the Score-CAM algorithm was used for result visualization. Heatmaps showed that the vein and color variations of the leaves provide key feature information for maturity recognition. This indirectly validates the importance of leaf texture and color features in maturity recognition and, to some extent, enhances the credibility of the model. The model proposed in this study maintains high performance while having low storage requirements and computational complexity, making it significant for in situ field maturity recognition of tobacco leaves.
Journal Article
Mitochondrial DNA in atherosclerosis research progress: a mini review
Atherosclerosis (AS) is a chronic inflammatory disease that primarily affects large and medium-sized arteries and is one of the leading causes of death worldwide. This article reviews the multifaceted role of mitochondrial DNA (mtDNA) in AS, including its structure, function, release, and relationship with inflammation. Damage and release of mtDNA are considered central drivers in the development of AS, as they participate in the progression of AS by activating inflammatory pathways and affecting lipid metabolism. Therefore, therapeutic strategies targeting mtDNA and its downstream effects may provide new avenues to address this global health challenge.
Journal Article
Rapid adaptation of the Irish potato famine pathogen Phytophthora infestans to changing temperature
Temperature plays a multidimensional role in host–pathogen interactions. As an important element of climate change, elevated world temperature resulting from global warming presents new challenges to sustainable disease management. Knowledge of pathogen adaptation to global warming is needed to predict future disease epidemiology and formulate mitigating strategies. In this study, 21 Phytophthora infestans isolates originating from seven thermal environments were acclimated for 200 days under stepwise increase or decrease of experimental temperatures and evolutionary responses of the isolates to the thermal changes were evaluated. We found temperature acclimation significantly increased the fitness and genetic adaptation of P. infestans isolates at both low and high temperatures. Low‐temperature acclimation enforced the countergradient adaptation of the pathogen to its past selection and enhanced the positive association between the pathogen's intrinsic growth rate and aggressiveness. At high temperatures, we found that pathogen growth collapsed near the maximum temperature for growth, suggesting a thermal niche boundary may exist in the evolutionary adaptation of P. infestans. These results indicate that pathogens can quickly adapt to temperature shifts in global warming. If this is associated with environmental conditions favoring pathogen spread, it will threaten future food security and human health and require the establishment of mitigating actions.
Journal Article
Integrated microRNA and whole-transcriptome sequencing reveals the involvement of small and long non-coding RNAs in the fiber growth of ramie plant
Background
MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are the two main types of non-coding RNAs that play crucial roles in plant growth and development. However, their specific roles in the fiber growth of ramie plant (
Boehmeria nivea
L. Gaud) remain largely unknown.
Methods
In this study, we performed miRNA and whole-transcriptome sequencing of two stem bark sections exhibiting different fiber growth stages to determine the expression profiles of miRNAs, lncRNAs, and protein-encoding genes.
Results
Among the identified 378 miRNAs and 6,839 lncRNAs, 88 miRNAs and 1,288 lncRNAs exhibited differential expression. Bioinformatics analysis revealed that 29 and 228 differentially expressed protein-encoding genes were targeted by differentially expressed miRNAs and lncRNAs, respectively, constituting eight putative competing endogenous RNA networks. lncR00022274 exhibited downregulated expression in barks with growing fibers. It also had an antisense overlap with the MYB gene,
BntWG10016451
, whose overexpression drastically increased the xylem fiber number and secondary wall thickness of fibers in the stems of transgenic
Arabidopsis
, suggesting the potential association of lncR00022274-
BntWG10016451
expression with fiber growth.
Conclusions
These findings provide insights into the roles of ncRNAs in the regulation of fiber growth in ramie, which can be used for the biotechnological improvement of its fiber yield and quality in the future.
Journal Article
Children with COVID-19 behaving milder may challenge the public policies: a systematic review and meta-analysis
Background
The emerging virus is rampaging globally. A growing number of pediatric infected cases have been reported. Great efforts are needed to cut down the transmission.
Methods
A single-arm meta-analysis was conducted. We searched PubMed, Google Scholar, Web of Science, and several Chinese databases for studies presenting characteristics of children confirmed with Coronavirus Disease 2019 (COVID-19) from December 12, 2019 to May 10, 2020. Quality Appraisal of Case Series Studies Checklist was used to assess quality and publication bias was analyzed by Egger’s test. Random-effect model was used to calculate the pooled incidence rate (IR) or mean difference (MD) with 95% confidence intervals (CI), or a fixed model instead when I
2
< 50%. We conducted subgroup analysis according to geographic region. Additionally, we searched United Nations Educational Scientific and Cultural Organization to see how different countries act to the education disruption in COVID-19.
Results
29 studies with 4300 pediatric patients were included. The mean age was 7.04 (95% CI: 5.06–9.08) years old. 18.9% of children were asymptomatic (95% CI: 0.121–0.266), 37.4% (95% CI: 0.280–0.474) had no radiographic abnormalities. Besides, a proportion of 0.1% patients were admitted to intensive care units (0, 95% CI: 0.000–0.013) and four deaths were reported (0, 95% CI: 0.000–0.000). Up to 159 countries have implemented nationwide school closures, affecting over 70% of the world’s students.
Conclusion
Children were also susceptible to SARS-CoV-2, while critical cases or deaths were rare. Characterized by mild presentation, the dilemma that children may become a potential spreader in the pandemic, while strict managements like prolonged school closures, may undermine their well-beings. Thus, the public policies are facing challenge.
Journal Article
Education and Atrial Fibrillation: Mendelian Randomization Study
Low social-economic status is associated with atrial fibrillation (AF), but the extent of any causative effect is unclear. In the present study, we evaluated the causal role of educational attainment (EA) on AF using Mendelian randomization (MR) analysis. Results from traditional single-variable MR indicated a modest causal effect of EA on AF. Sensitivity analyses using different MR methods yielded consistent results. Multi-variable MR and mediation analysis revealed that the protective effect of higher EA on AF was partially mediated by reducing cardiometabolic risk factors and smoking behavior. Our findings suggest that extending education, for example increasing school-leaving age, could lower the global burden of AF.
Journal Article