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Leaf rust caused by Puccinia triticina Eriks. is a serious threat to wheat production worldwide. Exploiting wild relatives can effectively help to improve the genetic resistance of wheat against rust. This study aimed to evaluate the responses of 34 Aegilops triuncialis accessions to seven Pt pathotypes and to analyse expression of genes associated with resistance at the seedling stage. Following multipathotype testing, two accessions with contrasting resistance were analysed at 0, 6, 12 and 24 h post‐inoculation for the expression profile of genes related to PR1, PR2, PR4, PR9, phenylalanine ammonia‐lyase and ATP‐binding cassette transporter. Of the accessions tested, eight showed high infection types of "3" to at least one Pt pathotype, while the remaining accessions had low ITs ("0;=" to "2+") against all pathotypes. The relative expressions of all candidate genes increased at all‐time points, but the expression level in the incompatible interaction was significantly higher than that of the compatible. The close relationship between PR proteins, PAL, salicylic acid‐ and jasmonic acid‐responsive proteins, as well as the proteins involved in the production of reactive oxygen species and lignin, could point to the specific recognition of the pathogen followed by the timely and intense induction of the expression of PR genes as the main reasons for resistance in incompatible interaction. In conclusion, the present study identified potentially new sources of resistance in this Ae. triuncialis population, which can be exploited in wheat breeding programs. [ABSTRACT FROM AUTHOR]

Background: For the past three years, the pandemic has had a major effect on global public health, mainly on those with underlying medical conditions, such as people living with Multiple Sclerosis. Vaccination among this group is of great importance, and the long-term impacts of vaccination and its safety on the health of these patients will continue to be revealed. Therefore, risks related to vaccination and immune response need to be assessed. The objective here was to characterize the immune response, short-term safety, and the effects of multiple variables on these factors after COVID-19 vaccination (mainly Sinopharm) among people with Multiple Sclerosis. We assessed the short-term safety and humoral SARS-COV-2 anti-RBD IgG response using a data collection form and Immunoassay, respectively. Results: No severe adverse events or MS relapse was observed. Myalgia/body pain (26.7%), low-grade fever (22.2%), and mild headache (15.6%) were the most common adverse events. The use and type of vaccine influenced the frequency of side effects with a p-value < 0.0001. Regarding immune response, patients on rituximab and fingolimod had a lower antibody titer compared to other medications. With a significant difference, hybrid immunity (p-value: 0.047) and type of DMTs (p-value: 0.017) affected the humoral response. Conclusion: There is a low incidence of serious adverse effects, MS worsening or relapse after COVID-19 vaccination, and mainly, side effects are similar to that of the general population. It appears that treatment with various disease-modifying therapies does not induce or worsen the post-vaccination side effects, although some, including Rituximab and fingolimod, may affect the immunity induced after vaccination. [ABSTRACT FROM AUTHOR]

Background: The aim was to establish a 10-year dyslipidemia incidence model, investigating novel anthropometric indices using exploratory regression and data mining. Methods: This data mining study was conducted on people who were diagnosed with dyslipidemia in phase 2 (n = 1097) of the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) study, who were compared with healthy people in this phase (n = 679). The association of dyslipidemia with several novel anthropometric indices including Conicity Index (C-Index), Body Roundness Index (BRI), Visceral Adiposity Index (VAI), Lipid Accumulation Product (LAP), Abdominal Volume Index (AVI), Weight-Adjusted-Waist Index (WWI), A Body Shape Index (ABSI), Body Mass Index (BMI), Body Adiposity Index (BAI) and Body Surface Area (BSA) was evaluated. Logistic Regression (LR) and Decision Tree (DT) analysis were utilized to evaluate the association. The accuracy, sensitivity, and specificity of DT were assessed through the performance of a Receiver Operating Characteristic (ROC) curve using R software. Results: A total of 1776 subjects without dyslipidemia during phase 1 were followed up in phase 2 and enrolled into the current study. The AUC of models A and B were 0.69 and 0.63 among subjects with dyslipidemia, respectively. VAI has been identified as a significant predictor of dyslipidemias (OR: 2.81, (95% CI: 2.07, 3.81)) in all models. Moreover, the DT showed that VAI followed by BMI and LAP were the most critical variables in predicting dyslipidemia incidence. Conclusions: Based on the results, model A had an acceptable performance for predicting 10 years of dyslipidemia incidence. Furthermore, the VAI, BMI, and LAP were the principal anthropometric factors for predicting dyslipidemia incidence by LR and DT models. [ABSTRACT FROM AUTHOR]