Cultivated peanut (Arachis hypogaea), a progeny of the cross between A. duranensis and A. ipaensis, is an important oil and protein crop from South America. To date, at least six Arachis genomes have ...been sequenced. WRKY transcription factors (TFs) play crucial roles in plant growth, development, and response to abiotic and biotic stresses. WRKY TFs have been identified in A. duranensis, A. ipaensis, and A. hypogaea cv. Tifrunner; however, variations in their number and evolutionary patterns across various Arachis spp. remain unclear.
WRKY TFs were identified and compared across different Arachis species, including A. duranensis, A. ipaensis, A. monticola, A. hypogaea cultivars (cv.) Fuhuasheng, A. hypogaea cv. Shitouqi, and A. hypogaea cv. Tifrunner. The results showed that the WRKY TFs underwent dynamic equilibrium between diploid and tetraploid peanut species, characterized by the loss of old WRKY TFs and retention of the new ones. Notably, cultivated peanuts inherited more conserved WRKY orthologs from wild tetraploid peanuts than their wild diploid donors. Analysis of the W-box elements and protein-protein interactions revealed that different domestication processes affected WRKY evolution across cultivated peanut varieties. WRKY TFs of A. hypogaea cv. Fuhuasheng and Shitouqi exhibited a similar domestication process, while those of cv. Tifrunner of the same species underwent a different domestication process based on protein-protein interaction analysis.
This study provides new insights into the evolution of WRKY TFs in Arachis spp.
Images captured during marine engineering operations suffer from color distortion and low contrast. Underwater image enhancement helps to alleviate these problems. Many deep learning models can infer ...multi-source data, where images with different perspectives exist from multiple sources. To this end, we propose a multichannel deep convolutional neural network (MDCNN) linked to a VGG that can target multi-source (multi-domain) underwater image enhancement. The designed MDCNN feeds data from different domains into separate channels and implements parameters by linking VGGs, which improves the domain adaptation of the model. In addition, to optimize performance, multi-domain image perception loss functions, multilabel soft edge loss for specific image enhancement tasks, pixel-level loss, and external monitoring loss for edge sharpness preprocessing are proposed. These loss functions are set to effectively enhance the structural and textural similarity of underwater images. A series of qualitative and quantitative experiments demonstrate that our model is superior to the state-of-the-art Shallow UWnet in terms of UIQM, and the performance evaluation conducted on different datasets increased by 0.11 on average.
Sleep problems are associated with abnormal cardiovascular biomarkers and an increased risk of cardiovascular diseases (CVDs). However, studies investigating associations between sleep problems and ...CVD biomarkers have reported conflicting findings. This study examined the associations between sleep problems and CVD biomarkers in the United States.
Data were from the National Health and Nutrition Examination Survey (NHANES) (2007-2018) and analyses were restricted to adults ≥ 20 years (n = 23,749). CVD biomarkers C-reactive Protein (CRP), low-density lipoproteins, high-density lipoproteins (HDL), triglycerides, insulin, glycosylated hemoglobin (HbA1c), and fasting blood glucose were categorized as abnormal or normal using standardized cut-off points. Sleep problems were assessed by sleep duration (short ≤ 6 h, long ≥ 9 h, and recommended > 6 to < 9 h) and self-reported sleep disturbance (yes, no). Multivariable logistic regression models explored the associations between sleep duration, sleep disturbance, and CVD biomarkers adjusting for sociodemographic characteristics and lifestyle behaviors.
The mean sleep duration was 7.1 ± 1.5 h and 25.1% of participants reported sleep disturbances. Compared to participants with the recommended sleep duration, those with short sleep duration had higher odds of abnormal levels of HDL (adjusted odds ratio aOR = 1.20, 95% confidence interval CI = 1.05-1.39), CRP (aOR = 3.08, 95% CI = 1.18-8.05), HbA1c (aOR = 1.25, 95% CI = 1.05-1.49), and insulin (aOR = 1.24, 95% CI = 1.03-1.51). Long sleep duration was associated with increased odds of abnormal CRP (aOR = 6.12, 95% CI = 2.19-17.15), HbA1c (aOR = 1.54, 95% CI = 1.09-2.17), and blood glucose levels (aOR = 1.45, 95% CI = 1.07-1.95). Sleep disturbance predicted abnormal triglyceride (aOR = 1.18, 95% CI = 1.01-1.37) and blood glucose levels (aOR = 1.24, 95% CI = 1.04-1.49).
Short and long sleep durations were positively associated with abnormal CRP, HDL, HbA1c, blood glucose, and insulin levels, while sleep disturbance was associated with abnormal triglyceride and blood glucose levels. Since sleep is a modifiable factor, adopting healthy sleeping habits may create a balanced metabolism and reduce the risk of developing a CVD. Our study may provide insights into the relationship between sleep duration, sleep disturbance, and CVD risk.
Background: Research indicates potential cardiometabolic benefits of energy consumption earlier in the day. This study examined the association between fasting duration, timing of first and last ...meals, and cardiometabolic endpoints using data from the National Health and Nutrition Examination Survey (NHANES). Methods: Cross-sectional data from NHANES (2005–2016) were utilized. Diet was obtained from one to two 24-h dietary recalls to characterize nighttime fasting duration and timing of first and last meal. Blood samples were obtained for characterization of C-reactive protein (CRP); glycosylated hemoglobin (HbA1c %); insulin; glucose; and high-density lipoprotein (HDL), low-density lipoprotein (LDL), and total cholesterol. Survey design procedures for adjusted linear and logistic regression were performed. Results: Every one-hour increase in nighttime fasting duration was associated with a significantly higher insulin and CRP, and lower HDL. Every one-hour increase in timing of the last meal of the day was statistically significantly associated with higher HbA1c and lower LDL. Every one-hour increase in first mealtime was associated with higher CRP (β = 0.044, p = 0.0106), insulin (β = 0.429, p < 0.01), and glucose (β = 0.662, p < 0.01), and lower HDL (β = −0.377, p < 0.01). Conclusion: In this large public health dataset, evidence for the beneficial effect of starting energy consumption earlier in the day on cardiometabolic endpoints was observed.
Cognitive impairment has multiple risk factors spanning several domains, but few studies have evaluated risk factor clusters. We aimed to identify naturally occurring clusters of risk factors of poor ...cognition among middle-aged and older adults and evaluate associations between measures of cognition and these risk factor clusters.
We used data from the National Health and Nutrition Examination Survey (NHANES) III (training dataset, n = 4074) and the NHANES 2011-2014 (validation dataset, n = 2510). Risk factors were selected based on the literature. We used both traditional logistic models and support vector machine methods to construct a composite score of risk factor clusters. We evaluated associations between the risk score and cognitive performance using the logistic model by estimating odds ratios (OR) and 95% confidence intervals (CI).
Using the training dataset, we developed a composite risk score that predicted undiagnosed cognitive decline based on ten selected predictive risk factors including age, waist circumference, healthy eating index, race, education, income, physical activity, diabetes, hypercholesterolemia, and annual visit to dentist. The risk score was significantly associated with poor cognitive performance both in the training dataset (OR Tertile 3 verse tertile 1 = 8.15, 95% CI: 5.36-12.4) and validation dataset (OR Tertile 3 verse tertile 1 = 4.31, 95% CI: 2.62-7.08). The area under the receiver operating characteristics curve for the predictive model was 0.74 and 0.77 for crude model and model adjusted for age, sex, and race.
The model based on selected risk factors may be used to identify high risk individuals with cognitive impairment.
To quantify the associations between dietary fats and their major components, as well as serum levels of cholesterol, and liver cancer risk, we performed a systematic review and meta-analysis of ...prospective studies. We searched PubMed, Embase, and Web of Science up to October 2020 for prospective studies that reported the risk estimates of dietary fats and serum cholesterol for liver cancer risk. We carried out highest versus lowest intake or level and dose-response analyses. Higher intake of dietary saturated fatty acids (SFA) was associated with a higher liver cancer risk in both category analysis (relative risk RR
= 1.34, 95% confidence interval CI: 1.06, 1.69) and dose-response analysis (RR
= 1.04, 95%CI: 1.01, 1.07). Higher serum total cholesterol was inversely associated with liver cancer but with large between-studies variability (RR
= 0.72, 95%CI: 0.69, 0.75, I
= 75.3%). The inverse association was more pronounced for serum high-density lipoprotein (HDL) cholesterol (RR
= 0.42, 95%CI: 0.27, 0.64). Higher intake of dietary SFA was associated with higher risk of liver cancer while higher serum levels of cholesterol and HDL were associated with a lower risk of liver cancer with high between-studies variability.
In order to test the feasibility of computer simulation in field maize planting, the selection of the method of single seed precise sowing in maize is studied based on the quadratic function model Y ...= A×(D-Dm)2+Ym, which depicts the relationship between maize yield and planting density. And the advantages and disadvantages of the two planting methods under the condition of single seed sowing are also compared: Method 1 is optimum density planting, while Method 2 is the ideal seedling emergence number planting. It is found that the yield reduction rate and yield fluctuation of Method 2 are all lower than those of Method 1. The yield of Method 2 increased by at least 0.043 t/hm2, and showed more advantages over Method 1 with higher yield level. Further study made on the influence of seedling emergence rate on the yield of maize finds that the yields of the two methods are both highly positively correlated with the seedling emergence rate and the standard deviations of their yields are both highly negatively correlated with the seedling emergence rate. For the study of the break-up problem of sparse caused by the method of single seed precise sowing, the definition of seedling missing spots is put forward. The study found that the relationship between number of hundred-dot spot and field seedling emergence rate is as the parabola function y = -189.32x2 + 309.55x - 118.95 and the relationship between number of spot missing seedling and field seedling emergence rate is as the negative exponent function y = 395.69e-6.144x. The results may help to guide the maize seeds production and single seed precise sowing to some extent.
It is unclear whether diet-associated inflammation is related to the development of anxiety disorders. We aimed to investigate the association between energy-adjusted dietary inflammatory index ...(E-DII) scores and the incidence of anxiety disorders, and explore the joint effects of E-DII scores with other inflammatory lifestyles in enhancing anxiety risk. In the UK Biobank Study of 96,679 participants, baseline E-DII scores were calculated from the average intake of at least two 24 h dietary recalls. Multivariable-adjusted Cox models were used to evaluate the associations between E-DII scores and the incidence of total anxiety disorders, and primary types and subtypes; additive and multiplicative interactions of a pro-inflammatory diet and seven inflammatory lifestyles were examined. After a median follow-up of 9.4 years, 2785 incident cases of anxiety disorders occurred. Consuming a pro-inflammatory diet was significantly associated with a higher risk of total anxiety disorders (HR
= 1.12, 95% CI = 1.00-1.25), and positive associations were consistently identified for primary types and subtypes of anxiety disorders, with HRs ranging from 1.08 to 1.52, and were present in women only. Both additive and multiplicative interactions of current smoking and a proinflammatory diet on total anxiety risk were identified. A proinflammatory diet was associated with a higher incidence of anxiety disorders, and current smoking may synergize with a proinflammatory diet to promote anxiety risk, particularly among women.
The aim of the study was to develop and evaluate a novel dietary index for gut microbiota (DI-GM) that captures dietary composition related to gut microbiota profiles. We conducted a literature ...review of longitudinal studies on the association of diet with gut microbiota in adult populations and extracted those dietary components with evidence of beneficial or unfavorable effects. Dietary recall data from the National Health and Nutrition Examination Survey (NHANES, 2005-2010,
= 3812) were used to compute the DI-GM, and associations with biomarkers of gut microbiota diversity (urinary enterodiol and enterolactone) were examined using linear regression. From a review of 106 articles, 14 foods or nutrients were identified as components of the DI-GM, including fermented dairy, chickpeas, soybean, whole grains, fiber, cranberries, avocados, broccoli, coffee, and green tea as beneficial components, and red meat, processed meat, refined grains, and high-fat diet (≥40% of energy from fat) as unfavorable components. Each component was scored 0 or 1 based on sex-specific median intakes, and scores were summed to develop the overall DI-GM score. In the NHANES, DI-GM scores ranged from 0-13 with a mean of 4.8 (SE = 0.04). Positive associations between DI-GM and urinary enterodiol and enterolactone were observed. The association of the novel DI-GM with markers of gut microbiota diversity demonstrates the potential utility of this index for gut health-related studies.
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