The genetic spectrum of familial hypercholesterolemia in South-Eastern Poland

BACKGROUND: Familial hypercholesterolemia (FH) is a common autosomal dominant disorder with a frequency of 1 in 200 to 500 in most European populations. Mutations in LDLR, APOB and PCSK9 genes are known to cause FH. In this study, we analyzed the genetic spectrum of the disease in the understudied Polish population. MATERIALS AND METHODS: 161 unrelated subjects with a clinical diagnosis of FH from the south-eastern region of Poland were recruited. High resolution melt and direct sequencing of PCR products were used to screen 18 exons of LDLR, a region of exon 26 in the APOB gene and exon 7 of PCSK9. Multiplex ligation-dependent probe amplification (MLPA) was performed to detect gross deletions and insertions in LDLR. Genotypes of six LDL-C raising SNPs were used for a polygenic gene score calculation. RESULTS: We found 39 different pathogenic mutations in the LDLR gene with 10 of them being novel. 13 (8%) individuals carried the p.Arg3527Gln mutation in APOB, and overall the detection rate was 43.4%. Of the patients where no mutation could be found, 53 (84.1%) had a gene score in the top three quartiles of the healthy comparison group suggesting that they have a polygenic cause for their high cholesterol. CONCLUSIONS: These results confirm the genetic heterogeneity of FH in Poland, which should be considered when designing a diagnostic strategy in the country. As in the UK, in the majority of patients where no mutation can be found, there is likely to be a polygenic cause of their high cholesterol level

National and sub-national trend of prevalence and burden of dementia in Iran, from 1990 to 2013; Study protocol

Background: Dementia is a disabling syndrome, which generally affects aged population more than any other age groups. This syndrome has a growing prevalence and incidence worldwide. The prevalence and burden of this group of diseases in Iran have not been estimated in a community-based study yet. This paper aims to explain the systematic approach, data sources, research methodology, and statistical analysis that will be used to quantify the prevalence and burden of dementia at national and sub-national levels. Methods: This is the protocol of a secondary data study that explains the design and method of conducting the study. We will use several sources of data that will include a systematic review of articles and gray literature which have reported the prevalence or incidence of dementia and its uncertainty at national and sub-national levels in Iran, in addition to data about dementia-specific drug sales per each year at provincial levels, as well as data extracted from 23 million health insurance prescriptions over 8 years and some data from medical documents of Iranian Alzheimer's Association members. The technical groups of National and Sub-national Burden of Disease will collect some covariate data, such as age and sex structure of population, urbanization status, mean years of schooling, plasma cholesterol, fasting plasma glucose, and systolic and diastolic blood pressure at provincial levels which will be used in our models. Two statistical models, namely spatio-temporal and hierarchical autoregressive models, will be used for interpolation and extrapolation of missing data. Conclusion: It seems that the study of national and subnational burden of dementia could provide more accurate estimation of prevalence and burden of dementia in Iran with an acceptable level of uncertainty than the previous studies

Global Air Quality and COVID-19 Pandemic : Do We Breathe Cleaner Air?

The global spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has challenged most countries worldwide. It was quickly recognized that reduced activities (lockdowns) during the Coronavirus Disease of 2019 (COVID-19) pandemic produced major changes in air quality. Our objective was to assess the impacts of COVID-19 lockdowns on groundlevel PM2.5, NO2, and O-3 concentrations on a global scale. We obtained data from 34 countries, 141 cities, and 458 air monitoring stations on 5 continents (few data from Africa). On a global average basis, a 34.0% reduction in NO2 concentration and a 15.0% reduction in PM2.5 were estimated during the strict lockdown period (until April 30, 2020). Global average O-3 concentration increased by 86.0% during this same period. Individual country and continent-wise comparisons have been made between lockdown and business-as-usual periods. Universally, NO2 was the pollutant most affected by the COVID-19 pandemic. These effects were likely because its emissions were from sources that were typically restricted (i.e., surface traffic and non-essential industries) by the lockdowns and its short lifetime in the atmosphere. Our results indicate that lockdown measures and resulting reduced emissions reduced exposure to most harmful pollutants and could provide global-scale health benefits. However, the increased O-3 may have substantially reduced those benefits and more detailed health assessments are required to accurately quantify the health gains. At the same, these restrictions were obtained at substantial economic costs and with other health issues (depression, suicide, spousal abuse, drug overdoses, etc.). Thus, any similar reductions in air pollution would need to be obtained without these extensive economic and other consequences produced by the imposed activity reductions.Peer reviewe

Global injury morbidity and mortality from 1990 to 2017 : results from the Global Burden of Disease Study 2017

Correction:Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.Peer reviewe

Preclinical Atherosclerosis in Monogenic Familial Hypercholesterolaemia and Polygenic Hypercholesterolaemia

Familial Hypercholesterolaemia (FH) is an autosomal dominant disorder with a frequency of 1 in 250 to 500 in most European populations. It is characterised by a raised low density lipoprotein-cholesterol (LDL-C) and a high incidence of premature coronary heart disease (CHD). There are three genes where mutations are known to cause FH: the low-density lipoprotein receptor (LDLR) gene, the apolipoprotein B (APOB) gene and the pro-protein convertase subtilisin/kexin type 9 (PCSK9) gene. An FH-causing mutation can be found in around 40% of patients with a possible diagnosis of FH. It has been suggested that the patients with a clinical diagnosis of FH where no mutation were found might have a polygenic cause for their raised LDL-C. FH disorder is an under-diagnosed condition in many countries such as Poland. An analysis of a Polish FH cohort in this thesis, demonstrated the heterogeneous aetiology of FH. We found 39 different pathogenic mutations in the LDLR gene with 10 of them being novel and an overall detection rate of 43.4%. The aim of this thesis was to compare preclinical atherosclerosis between patients with monogenic FH and subjects with polygenic hypercholesterolaemia by means of a neck ultrasound to measure carotid Intima Media Thickness and a cardiac CT scan to assess coronary artery calcification. This study showed that preclinical atherosclerosis was greater in patients with monogenic FH. Lipoprotein(a) [Lp(a)] is a well-known biomarker for CHD risk prediction. The Lp(a) concentration and its association with two LPA single nucleotide polymorphisms (rs3798220 and rs6919346) were assessed in FH patients participating in the Simon Broome registry and a group of the general population participating in the Northwick Park Heart Study II. The results showed that the Lp(a) concentration and the frequency of rs3798220 was significantly higher in the FH patients compared to the general population

Modelling and Assessment of an Autonomous Ride-Sharing Service’s Urban Utilization: Case Study - Rotterdam

Increasing demand for passenger services in densely populated urban environments, are currently covered overwhelmingly by private vehicles. Their impact on CO2 emission, present a serious obstacle to the reduction objectives, in the Netherlands alone the target of 45% by 2030, for limiting the global warming to 1.5°C degrees. Autonomous Vehicles (AV) and Ride-Sharing services are believed to be offering a crucial technological and perception shifts to reducing emission. In this work, a methodology for assessing the impact of a large-scale AV fleet ride-sharing system to replace the one-two passenger vehicle traffic using Rotterdam as the case study is designed and proposed. The approach includes three stages: 1. Building and finetuning a traffic model using publicly available data 2. Designing and implementing a trip merging component, in the form of two distinct heuristic greedy algorithms and a variation of the second one, using Python programming language. 3. Evaluating the impact of each merging scenario on the network in SUMO. The system’s influence and results are driven from the deployment of the ride-sharing service on the 2016 traffic model. The decrease in total number of trips, vehicle kilometres travels, and subsequent improvements in traffic flow resulted in 39% reduction in CO2 emission with the third algorithm. This result not only establishes the extent of AV ride-sharing service’s potential for emission reduction and traffic quality improvement. This adaptable methodology also operates as a proof of concept for a preliminary step for policy makers when considering implementing such service in any urban setting. Two of the major elements not included in this research are multimodal travel, like combination with public transport, and changes in demand for each mode choice based on traveller’s behaviour. These elements thus remain open for future consideration.Engineering and Policy Analysi

Determining the status of activity of daily living (ADL) and instrumental activity of daily living (IADL) in healthy and cognitive impaired elderlies

Background & Objective: Dementia is associated with serious effects on memory, cognition and ability to carry out daily activities. There is evidence that impairment in activity of daily living (ADL) is even reported among elder patients who suffer from mild cognitive disorders. Therefore, we aimed to determine the status of ADL and instrumental activity of daily living (IADL) in healthy and cognitive impaired elderlies (MCI, Mild, and Moderate dementia). Methods: In this cross-sectional study which was conducted in 2016, 300 elderlies (60 years and above) were selected using a classified cluster sampling in four groups (each group of 75 individuals). These groups comprised of healthy old people and elderlies with mild cognitive impairment (MCI) and mild to moderate dementia that were residing in rural areas of Isfahan and Tehran and were classified between stages of 1 to 5 according to the Global Deterioration Scale (GDS). All individuals in four groups were assessed by ADL and IADL evaluation tools. The geriatric depression scale (GDS-15) and DSM-IV scale were performed on healthy elderlies by a physician to confirm the lack of mild dementia or depression. Data were analyzed by SPSS 20 software and using descriptive statistics, analysis of variance and independent samples T-test. Results: According to the cognitive impairment screening results by GDS, 76 elderlies were healthy, 75 were in MCI group, 72 individuals were diagnosed with mild dementia and 77 were suffering from moderate dementia. The mean scores of ADL tool on the basis of different cognitive stages of elderlies were statistically significant (p<0.001). The ADL scores among elderlies were lowered by increasing the severity of cognitive impairment. Moreover, the average scores of IADL among elderlies with different cognitive status were significantly different (p<0.001). The IADL scores in cases with moderate dementia were markedly declined in comparison to healthy subjects and elderlies with MCI and mild dementia. Conclusion: Although applying the ADL and IADL tools are not considered as gold standards in rapid assessment of cognitive impairments among elderlies, they could be considered as useful and user friendly tools to detect performance alterations in elderlies with dementia to provide healthcare by geriatric teams

Data underlying the master thesis: Modelling and Assessment of an Autonomous Ride-Sharing Service’s Urban Utilization

This collection represents the empirical portion of the author’s MSc thesis research, which involved modelling the private vehicle traffic flow for the city of Rotterdam and the simulation of an autonomous ride-sharing service's impact on CO2 emission using that model on SUMO. It has four subfolders: net_files, python_code_files, sim_runs, and output_excel_files. The folder contains Rotterdam's processed road network configuration, zonal data, and edge specifications along with the entirety of the written python code files for the construction of the traffic model and the trip merging component of the ride-sharing service. Three separate scenarios were simulated for this project and compared to the baseline simulation for determining the emission reduction rates, and all ten iterations of these simulations are also included in this zip file. Finally, here are several excel sheets detailing the results and calculations for zonal attraction ranking.  The code contains extensive comments that can be easily used to replicate or build on the published work. The readers may refer to the related thesis document for further explanations. </p