Double base mismatches mediated catalytic hairpin assembly for enzyme-free single-base mutation detection: integrating signal recognition and amplification in one.

Single nucleotide polymorphism (SNP) biosensors are emerging rapidly for their promising applications in human disease prevention diagnosis, treatment, and prognosis. However, it remains a bottleneck in equipping simple and stable biosensors with the traits of high sensitivity, non-enzyme, and low cost. Double base mismatches mediated chain displacement reactions have attracted fascinating advantages of tailorable thermodynamics stability, non-enzyme, and excellent assembly compliance to involvement in SNP identification. As the base mismatch position and amount in DNA sequence can be artificially adjusted, it provides plenty of selectivity and specificity for exploring perfect biosensors. Herein, a biosensor with double base mismatches mediated catalytic hairpin assembly (CHA) is designed via one base mismatch in the toehold domain and the other base mismatch in the stem sequence of hairpin 1 (H1) by triggering CHA reaction to achieve selective amplification of the mutation target (MT) and fluorescence resonance energy transfer (FRET) effect that is composed of Cy3 and Cy5 terminally attached H1 and hairpin 2 (H2). Depending on the rationally designed base mismatch position and toehold length, the fabricated biosensors show superior SNP detection performance, exhibiting a good linearity with high sensitivity of 6.6 fM detection limit and a broad detection abundance of 1%. The proposed biosensor can be used to detect the KRAS mutation gene in real samples and obtain good recoveries between 106 and 116.99%. Remarkably, these extendible designs of base mismatches can be used for more types of SNP detection, providing flexible adjustment based on base mismatch position and toehold length variations, especially for their thermodynamic model for DNA-strand displacement reactions.

Association between physical activity and allostatic load among pregnant women.

Allostatic load (AL) in pregnant women is associated with maternal and infant health outcomes. Whether physical activity (PA) is a modifiable factor associated with AL during pregnancy is unknown. In this cross-sectional study, including 725 pregnant women in 3 different trimesters, 8 biomarkers were included, and the high-risk quartile approach based on sample distribution was used to construct AL index (ALI). ALI <2 was defined as a low level and ≥2 as a high level. Student's t-test or Mann-Whitney U test and chi-squared test or Fisher exact test were used to compare differences in AL with different demographic characteristics among pregnant women. The relationship between PA and AL in pregnant women was analyzed using a binary logistic regression model. The results show that the detection rate of high-risk AL during pregnancy was 47.3%. In the adjusted model, sufficient PA was related to a lower AL than insufficient PA (OR = .693, 95%CI:.494,.971; p = .033). Compared with low- and high-intensity PAs, moderate-intensity PA was associated with lower AL (OR = .645, 95%CI:.447,.930; p = .019). The results suggest that PA is a modifiable factor related to AL, and intervention is recommended to be carried out in the first trimester to prevent the increased likelihood of high AL as pregnancy progresses. In addition, health care personnel should encourage pregnant women to participate in PA, especially moderate-intensity PA, in order to obtain lower AL and promote maternal and child health.

Rationally Designed Dual Base Pair Mismatch Enables Toehold-Mediated Strand Displacement to Efficiently Recognize Single-Nucleotide Polymorphism without Enzymes.

The efficiency of the enzyme-free toehold-mediated strand displacement (TMSD) technique is often insufficient to detect single-nucleotide polymorphism (SNP) that possesses only single base pair mismatch discrimination. Here, we report a novel dual base pair mismatch strategy enabling TMSD biosensing for SNP detection under enzyme-free conditions when coupled with catalytic hairpin assembly (CHA) and fluorescence resonance energy transfer (FRET). The strategy is based on a competitive strand displacement reaction mechanism, affected by the thermodynamic stability originating from rationally designed dual base pair mismatch, for the specific recognition of mutant-type DNA. In particular, enzyme-free nucleic acid circuits, such as CHA, emerge as a powerful method for signal amplification. Eventually, the signal transduction of this proposed biosensor was determined by FRET between streptavidin-coated 605 nm emission quantum dots (605QDs, donor) and Cy5/biotin hybridization (acceptor, from CHA) when incubated with each other. The proposed biosensor displayed high sensitivity to the mutant target (MT) with a detection concentration down to 4.3 fM and led to high discrimination factors for all types of mismatches in multiple sequence contexts. As such, the application of this proposed biosensor to investigate mechanisms of the competitive strand displacement reaction further illustrates the versatility of our dual base pair mismatch strategy, which can be utilized for the creation of a new class of biosensors.

Associations of Socioeconomic Factors and Unhealthy Lifestyles with Allostatic Load: A Meta-analysis.

BACKGROUND: Allostatic load (AL) is a biological tool for objectively assessing chronic stress and has been discussed inconsistently for its correlation with socioeconomic factors and unhealthy lifestyles. Therefore, this meta-analysis was performed to explore the impact of socioeconomic factors and unhealthy lifestyles on AL. METHOD: Different databases, including Web of Science, PubMed, EBSCOhost, Embase, CNKI, VIP, SinoMed, and Wanfang, were searched from inception to June 6, 2023. A total of 25 studies, reporting the correlations of seven socioeconomic factors and three unhealthy lifestyles with AL, were finally included. The pooled odds ratios (OR) and 95% confidence intervals (CIs) were examined using random-effect and fixed-effect models. Literature quality, heterogeneity, and publication bias were evaluated. RESULTS: The meta-analysis showed a significantly increased risk of high AL in the older individuals as compared to the younger ones (OR = 1.05, 95% CI 1.04-1.06), in the individual with low education as compared to those with high education (OR = 1.25, 95% CI 1.05-1.48), and in the individuals with low physical activities as compared to those with high physical activities (OR = 1.44, 95% CI 1.26-1.64). This meta-analysis also showed a significantly decreased risk of high AL in the individuals with high income as compared to those with low income (OR = 0.77, 95% CI 0.71-0.83) and in women as compared to men (OR = 0.80, 95% CI 0.80-0.81). CONCLUSION: This meta-analysis showed older people, men, and people having low physical activity, low income, and low education were more likely to have a high AL. TRIAL REGISTRATION: This meta-analysis was registered on the PROSPERO database with trial registration number CRD42022326105. Instead of providing information at registration, we added an author (Tingyu Mu), who provided critical revisions to the paper in this meta-analysis.

Physical activity is associated with allostatic load: Evidence from the National Health and Nutrition Examination Survey.

We determined the associations between physical activity and allostatic load, and whether it is a modifiable factor related to allostatic load. We obtained data from the National Health and Nutrition Examination Survey (NHANES) database collected between 2017 and March 2020. The relationship between physical activity and allostatic load was examined using a logistic regression model. In the unadjusted model, physical activity level was associated with allostatic load index (odds ratio [OR] = 0.664, 95% confidence interval [CI]: 0.550, 0.802, P＜0.001), with this relationship being retained in the adjusted model (OR = 0.739, 95%CI: 0.603, 0.907; P = 0.004). Sedentary behaviour was also related to allostatic load index (OR = 1.236, 95%CI: 1.005, 1.520; P = 0.044). Our findings indicated that sufficient physical activity is associated with a lower allostatic load index, and sedentary behaviour is associated with a higher allostatic load index. Physical activity is a modifiable factor related to allostatic load.