Synopsis of the genus Alyssum in Iran

A complete, up to date checklist of Alyssum species reported from Iran is presented in this review. The distribution of these species was considered in Iran and in the adjacent countries, too. Additional records were obtained from Flora Iranica, Flora of Turkey and other references. In Iran some species (e. g., Alyssum hezarmasjedensis, A. mozaffarianii, A. persicum, A. polycladum, A. stipitatum, A. turgidum) have very restricted distribution. Iran is the second important locality for the following species: A. anatolicum, A. contemptum, A. filiforme, A. iranicum, A. lycaonicum, A. niveum, A. penjwinense. The other Alyssum species are widespread in Iran and in the adjacent countries

Sex-related differences in coronary and carotid vessel geometry, plaque composition and shear stress obtained from imaging

Atherosclerosis manifests itself differently in men and women with respect to plaque initiation, progression and plaque composition. The observed delay in plaque progression in women is thought to be related to the hormonal status of women. Also features associated with the vulnerability of plaques to rupture seem to be less frequently present in women compared to men. Current invasive and non-invasive imaging modalities allow for visualization of plaque size, composition and high risk vulnerable plaque features. Moreover, image based modeling gives access to local shear stress and shear stress-related plaque growth. In this review, current knowledge on sex-related differences in plaque size, composition, high risk plaque features and shear stress related plaque growth in carotid and coronary arteries obtained from imaging are summarized.</p

Water safety in drought: An indigenous knowledge-based qualitative study

The indigenous knowledge of our ancestors provides valuable information on how to prevent negative health impacts on water hygiene in the event of drought. The present study aimed to explore the role of indigenous knowledge in maintaining water safety in drought conditions. A qualitative content analysis method using in-depth semi-structured interviews was used to collect and analyze the data. The current research was carried out from April 2017 to June 2018. A purposive sampling method was used to select 15 participants. Trustworthiness was applied with the Lincoln and Guba approach and data were analyzed using Graneheim and Lundman's method. Two categories including drinking water storage and water collection were extracted from the data. Each category includes different strategies to deal with water. Water storage includes water quantity and water quality. Water collection consists of collection methods and rules. Indigenous knowledge is an indispensable component of community disaster resilience. It can be transferred to other communities and employed to empower affected communities. But using the knowledge without scientific considerations cannot guarantee peoples' health throughout the drought periods. © IWA Publishing 2020 Journal of Water and Healt

Metabolically healthy obesity and the risk of cardiovascular disease in the elderly population

Background Whether being metabolically healthy obese (MHO)-defined by the presence of obesity in the absence of metabolic syndrome-is associated with subsequent cardiovascular disease (CVD) remains unclear and may depend on the participants' age. We examined the association of being MHO with CVD risk in the elderly. Methods and Findings This study included 5,314 individuals (mean age 68 years) from the prospective populationbased Rotterdam Study.We categorized our population in groups according to body mass index (BMI) and presence and absence of metabolic syndrome, and estimated the hazard ratio (HR) and 95% confidence interval (95%CI) for every group by using Cox proportional hazard models. Among 1048 (19.7%) obese individuals we identified 260 (24.8%) MHO subjects. Over 14 years of follow-up there were 861 incident CVD cases. In the multivariable adjusted analysis, we did not observe an increased CVD risk in MHO individuals (HR 1.07, 95%CI 0.75-1.53), compared to normal weight individuals without metabolic syndrome. CVD risk was increased by the presence of metabolic syndrome in normal weight (HR 1.35, 95%CI 1.02-1.80), overweight (HR 1.32, 95%CI 1.09-1.60) and obese (HR 1.33, 95%CI 1.07-1.66) individuals, compared to those with normal weight without metabolic syndrome. In a mediation analysis, 71.3% of the association between BMI and CVD was explained by the presence of metabolic syndrome. Conclusions In our elderly population, we found that the presence of obesity without metabolic syndrome did not confer a higher CVD risk. However, metabolic syndrome was strongly associated with CVD risk, and was associated with an increased risk in all BMI categories. Therefore, preventive interventions targeting cardiometabolic risk factors could be considered in elderly, regardless of weight status

The retinal microcirculation in migraine: The Rotterdam Study

Background: To explore the role of microvascular pathology in migraine, we investigated the association between migraine and retinal microvascular damage. Methods: We included 3270 participants (age ≥ 45 years, 63% women) from the population-based Rotterdam Study (2006–2009). Participants with migraine were identified using a validated questionnaire based on ICHD-II criteria (n = 562). Retinopathy signs were graded on fundus photographs. Retinal arteriolar and venular caliber were measured by semi-automatic assessment of fundus photographs. Associations of migraine with retinopathy and retinal microvascular calibers were examined using logistic and linear regression models, respectively, adjusting for age, sex, and cardiovascular risk factors. Results: Migraine was not associated with the presence of retinopathy (odds ratio (OR): 1.09, 95% confidence interval (CI) 0.62; 1.92). In the fully adjusted model, adjusting for the companion vessel, persons with migraine did not differ in retina

The importance of CDC27 in cancer: molecular pathology and clinical aspects

Background: CDC27 is one of the core components of Anaphase Promoting complex/cyclosome. The main role of this protein is defined at cellular division to control cell cycle transitions. Here we review the molecular aspects that may affect CDC27 regulation from cell cycle and mitosis to cancer pathogenesis and prognosis. Main text: It has been suggested that CDC27 may play either like a tumor suppressor gene or oncogene in different neoplasms. Divergent variations in CDC27 DNA sequence and alterations in transcription of CDC27 have been detected in different solid tumors and hematological malignancies. Elevated CDC27 expression level may increase cell proliferation, invasiveness and metastasis in some malignancies. It has been proposed that CDC27 upregulation may increase stemness in cancer stem cells. On the other hand, downregulation of CDC27 may increase the cancer cell survival, decrease radiosensitivity and increase chemoresistancy. In addition, CDC27 downregulation may stimulate efferocytosis and improve tumor microenvironment. Conclusion: CDC27 dysregulation, either increased or decreased activity, may aggravate neoplasms. CDC27 may be suggested as a prognostic biomarker in different malignancies. © 2021, The Author(s)

World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions

© 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Background: To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk prediction charts that have been adapted to the circumstances of 21 global regions. Methods: In this model revision initiative, we derived 10-year risk prediction models for fatal and non-fatal cardiovascular disease (ie, myocardial infarction and stroke) using individual participant data from the Emerging Risk Factors Collaboration. Models included information on age, smoking status, systolic blood pressure, history of diabetes, and total cholesterol. For derivation, we included participants aged 40–80 years without a known baseline history of cardiovascular disease, who were followed up until the first myocardial infarction, fatal coronary heart disease, or stroke event. We recalibrated models using age-specific and sex-specific incidences and risk factor values available from 21 global regions. For external validation, we analysed individual participant data from studies distinct from those used in model derivation. We illustrated models by analysing data on a further 123 743 individuals from surveys in 79 countries collected with the WHO STEPwise Approach to Surveillance. Findings: Our risk model derivation involved 376 177 individuals from 85 cohorts, and 19 333 incident cardiovascular events recorded during 10 years of follow-up. The derived risk prediction models discriminated well in external validation cohorts (19 cohorts, 1 096 061 individuals, 25 950 cardiovascular disease events), with Harrell\u27s C indices ranging from 0·685 (95% CI 0·629–0·741) to 0·833 (0·783–0·882). For a given risk factor profile, we found substantial variation across global regions in the estimated 10-year predicted risk. For example, estimated cardiovascular disease risk for a 60-year-old male smoker without diabetes and with systolic blood pressure of 140 mm Hg and total cholesterol of 5 mmol/L ranged from 11% in Andean Latin America to 30% in central Asia. When applied to data from 79 countries (mostly low-income and middle-income countries), the proportion of individuals aged 40–64 years estimated to be at greater than 20% risk ranged from less than 1% in Uganda to more than 16% in Egypt. Interpretation: We have derived, calibrated, and validated new WHO risk prediction models to estimate cardiovascular disease risk in 21 Global Burden of Disease regions. The widespread use of these models could enhance the accuracy, practicability, and sustainability of efforts to reduce the burden of cardiovascular disease worldwide. Funding: World Health Organization, British Heart Foundation (BHF), BHF Cambridge Centre for Research Excellence, UK Medical Research Council, and National Institute for Health Research

Development and external validation of a deep learning algorithm for prognostication of cardiovascular outcomes

Background and Objectives: We aim to explore the additional discriminative accuracy of a deep learning (DL) algorithm using repeated-measures data for identifying people at high risk for cardiovascular disease (CVD), compared to Cox hazard regression. Methods: Two CVD prediction models were developed from National Health Insurance Service-Health Screening Cohort (NHIS-HEALS): A Cox regression model and a DL model. Performance of each model was assessed in the internal and 2 external validation cohorts in Koreans (National Health Insurance Service-National Sample Cohort; NHIS-NSC) and in Europeans (Rotterdam Study). A total of 412,030 adults in the NHIS-HEALS; 178,875 adults in the NHIS-NSC; and the 4,296 adults in Rotterdam Study were included. Results: Mean ages was 52 years (46% women) and there were 25,777 events (6.3%) in NHIS-HEALS during the follow-up. In internal validation, the DL approach demonstrated a C-statistic of 0.896 (95% confidence interval, 0.886-0.907) in men and 0.921 (0.908-0.934) in women and improved reclassification compared with Cox regression (net reclassification index [NRI], 24.8% in men, 29.0% in women). In external validation with NHIS-NSC, DL demonstrated a C-statistic of 0.868 (0.860-0.876) in men and 0.889 (0.876-0.898) in women, and improved reclassification compared with Cox regression (NRI, 24.9% in men, 26.2% in women). In external validation applied to the Rotterdam Study, DL demonstrated a C-statistic of 0.860 (0.824-0.897) in men and 0.867 (0.830-0.903) in women, and improved reclassification compared with Cox regression (NRI, 36.9% in men, 31.8% in women). Conclusions: A DL algorithm exhibited greater discriminative accuracy than Cox model approaches