A strategy to build a library of oil tracers by oleophilic silica-encapsulated DNA nanoparticles.

Artificially synthesized DNA is involved in the construction of a library of oil tracers due to their unlimited number and no-biological toxicity. The strategy of the construction is proposed by oleophilic Silica-encapsulated DNA nanoparticles, which offers fresh thinking in developing novel tracers, sensors, and molecular machines in engineering & applied sciences based on artificially synthesized DNA blocks.

Microbial regulation of plant secondary metabolites: Impact, mechanisms and prospects.

Plant secondary metabolites possess a wide range of pharmacological activities and play crucial biological roles. They serve as both a defense response during pathogen attack and a valuable drug resource. The role of microorganisms in the regulation of plant secondary metabolism has been widely recognized. The addition of specific microorganisms can increase the synthesis of secondary metabolites, and their beneficial effects depend on environmental factors and plant-related microorganisms. This article summarizes the impact and regulatory mechanisms of different microorganisms on the main secondary metabolic products of plants. We emphasize the mechanisms by which microorganisms regulate hormone levels, nutrient absorption, the supply of precursor substances, and enzyme and gene expression to promote the accumulation of plant secondary metabolites. In addition, the possible negative feedback regulation of microorganisms is discussed. The identification of additional unknown microbes and other driving factors affecting plant secondary metabolism is essential. The prospects for further analysis of medicinal plant genomes and the establishment of a genetic operation system for plant secondary metabolism research are proposed. This study provides new ideas for the use of microbial resources for biological synthesis research and the improvement of crop anti-inverse traits for the use of microbial resources.

Difference in the Effect of Applying Bacillus to Control Tomato Verticillium Wilt in Black and Red Soil.

In practical applications, the effectiveness of biological control agents such as Bacillus is often unstable due to different soil environments. Herein, we aimed to explore the control effect and intrinsic mechanism of Bacillus in black soil and red soil in combination with tomato Verticillium wilt. Bacillus application effectively controlled the occurrence of Verticillium wilt in red soil, reducing the incidence by 19.83%, but played a limited role in black soil. Bacillus colonized red soil more efficiently. The Verticillium pathogen decreased by 71.13% and 76.09% after the application of Bacillus combinations in the rhizosphere and bulk of the red soil, respectively, while there was no significant difference in the black soil. Additionally, Bacillus application to red soil significantly promoted phosphorus absorption. Furthermore, it significantly altered the bacterial community in red soil and enriched genes related to pathogen antagonism and phosphorus activation, which jointly participated in soil nutrient activation and disease prevention, promoting tomato plant growth in red soil. This study revealed that the shaping of the bacterial community by native soil may be the key factor affecting the colonization and function of exogenous Bacillus.

Effects of Ninjurin 2 polymorphisms on susceptibility to coronary heart disease.

OBJECTIVE: The aim of this study was to explore the effects of Ninjurin 2 (NINJ2) polymorphisms on susceptibility to coronary heart disease (CHD). METHODS: We conducted a case-control study with 499 CHD cases and 505 age and gender-matched controls. Five single nucleotide polymorphisms (SNPs) in NINJ2 (rs118050317, rs75750647, rs7307242, rs10849390, and rs11610368) were genotyped by the Agena MassARRAY platform. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using logistic regression analysis to assess the association of NINJ2 polymorphisms and CHD risk-adjusted for age and gender. What's more, risk genes and molecular functions were screened via protein-protein interaction (PPI) network and functional enrichment analysis. RESULTS: Rs118050317 in NINJ2 significantly increased CHD risk in people aged more than 60 years and women. Rs118050317 and rs7307242 had strong relationships with hypertension risk in CHD patients. Additionally, rs75750647 exceedingly raised diabetes risk in cases under multiple models, whereas rs10849390 could protect CHD patients from diabetes in allele, homozygote, and additive models. We also observed two blocks in NINJ2. Further interaction network and enrichment analysis showed that NINJ2 played a greater role in the pathogenesis and progression of CHD. CONCLUSION: Our results suggest that NINJ2 polymorphisms are associated with CHD risk.

Genetic and phenotypic associations of frailty with cardiovascular indicators and behavioral characteristics.

INTRODUCTION: Frailty Index (FI) is a common measure of frailty, which has been advocated as a routine clinical test by many guidelines. The genetic and phenotypic relationships of FI with cardiovascular indicators (CIs) and behavioral characteristics (BCs) are unclear, which has hampered ability to monitor FI using easily collected data. OBJECTIVES: This study is designed to investigate the genetic and phenotypic associations of frailty with CIs and BCs, and further to construct a model to predict FI. METHOD: Genetic relationships of FI with 288 CIs and 90 BCs were assessed by the cross-trait LD score regression (LDSC) and Mendelian randomization (MR). The phenotypic data of these CIs and BCs were integrated with a machine-learning model to predict FI of individuals in UK-biobank. The relationships of the predicted FI with risks of type 2 diabetes (T2D) and neurodegenerative diseases were tested by the Kaplan-Meier estimator and Cox proportional hazards model. RESULTS: MR revealed putative causal effects of seven CIs and eight BCs on FI. These CIs and BCs were integrated to establish a model for predicting FI. The predicted FI is significantly correlated with the observed FI (Pearson correlation coefficient = 0.660, P-value = 4.96 × 10-62). The prediction model indicated "usual walking pace" contributes the most to prediction. Patients who were predicted with high FI are in significantly higher risk of T2D (HR = 2.635, P < 2 × 10-16) and neurodegenerative diseases (HR = 2.307, P = 1.62 × 10-3) than other patients. CONCLUSION: This study supports associations of FI with CIs and BCs from genetic and phenotypic perspectives. The model that is developed by integrating easily collected CIs and BCs data in predicting FI has the potential to monitor disease risk.