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Preeclampsia (PE) is a hypertensive complication of pregnancy that affects 2–8% of women worldwide and is one of the leading causes of maternal deaths and premature birth. PE can occur early in pregnancy (34 weeks gestation). Whilst the placenta is clearly implicated in early onset PE (EOPE), late onset PE (LOPE) is less clear with some believing the disease is entirely maternal whilst others believe that there is an interplay between maternal systems and the placenta. In both types of PE, the syncytiotrophoblast (STB), the layer of the placenta in direct contact with maternal blood, is stressed. In EOPE, the STB is oxidatively stressed in early pregnancy (leading to PE later in gestation- the two-stage model) whilst in LOPE the STB is stressed because of villous overcrowding and senescence later in pregnancy. It is this stress that perturbs maternal systems leading to the clinical manifestations of PE. Whilst some of the molecular species driving this stress have been identified, none completely explain the multisystem nature of PE. Syncytiotrophoblast membrane vesicles (STB-EVs) are a potential contributor to this multisystem disorder. STB-EVs are released into the maternal circulation in increasing amounts with advancing gestational age, and this release is further exacerbated with stress. There are good in vitro evidence that STB-EVs are taken up by macrophages and liver cells with additional evidence supporting endothelial cell uptake. STB-EV targeting remains in the early stages of discovery. In this review, we highlight the role of STB-EVs in PE. In relation to current research, we discuss different protocols for ex vivo isolation of STB-EVs, as well as specific issues involving tissue preparation, isolation (some of which may be unique to STB-EVs), and methods for their analysis. We suggest potential solutions for these challenges.

The work presented in this thesis describes research towards design, and novel means of fabrication of distance-based microfluidic paper-based analytical devices (˜í¬¿PADs), and development of selected applications for (bio)chemical point-of-care analysis. Chapter 1 provides insights into the principles and evolution of ˜í¬¿PADs, particularly those based on the distance-based detection method. Chapter 2 introduces a new facile fabrication technique for (distance-based) ˜í¬¿PADs using a low-cost desktop electronic craft plotter/cutter. This simple approach enabled rapid prototyping of ˜í¬¿PADs by coupling a wax printer with a plotter/cutter, enabling the desired cutting and reagent deposition steps being performed in a fully integrated and geometrically aligned manner along with the wax-printing step. Chapter 3 extends the development of this fabrication method and further investigates the deposition characteristics and performance of this novel approach, demonstrating its capability for deposition of in-house formulated reagents upon ˜í¬¿PADs with various designs, while the deposition volume could be precisely quantified gravimetrically. Chapter 4 demonstrates the effect of the ˜í¬¿PAD device geometry on the distance signal obtained from the fabricated distance-based ˜í¬¿PADs. It is shown that implementation of asymmetrical geometry microfluidic paper channels (varying width instead of the typical rectangular channels) improved analytical parameters significantly. This is demonstrated with the instrumentation-free determination of chloride via trapezoidal distance-based ˜í¬¿PADs from as little as 5 ˜í¬¿L sample volume, a key requirement for analysis of chloride in sweat as a basis of diagnosis of cystic fibrosis. In chapter 5, the stable immobilization of chromogenic reagents upon paper, being a significant issue in regard to distance-based detection, is addressed. Herein, anion exchange filter paper is introduced as a new substrate for fabrication of ˜í¬¿PADs, providing immobilization of water-soluble anionic reagents upon the paper surface and consequently allowing the development of distance-based assays without being compromised by the sample fluid washing away effect, otherwise limiting the choice of reagents to only water-insoluble ones. This extends the applicability of the distance-based detection method to assays which involve water-soluble anionic chromogenic reagents, not readily immobilized on the standard filter paper. Finally, Chapter 6 of this thesis discusses the limitations of (distance-based) ˜í¬¿PADs and provides further insight and direction for future research.

Soheila Habibi Ghahfarokhi, 1 Mehrdad Mosadegh, 1 Ali Ahmadi, 2 Mohammad Reza Pourmand, 1 Mohammad Azarsa, 3 Mohammad Rahbar, 4 Bahram Nikmanesh 5 1Department of Pathobiology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran; 2Molecular Biology Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran; 3Department of Microbiology, Khoy University of Medical Sciences, Khoy, Iran; 4Department of Microbiology, Reference Health Laboratories Research Center, Ministry of Health and Medical Education, Tehran, Iran; 5Department of Medical Laboratory Sciences, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, IranCorrespondence: Mohammad Reza PourmandDepartment of Pathobiology, School of Public Health, Tehran University of Medical Sciences, Poursina St., Keshavarz Blvd., Tehran 1417613151, IranTel/Fax +98 21-88-95-4910Email mpourmand@tums.ac.irIntroduction: Encapsulated Streptococcus pneumoniae strains cause high morbidity and mortality, mainly in countries with no pneumococcal conjugate vaccines (PCVs) immunization program. This study investigated the epidemiological changes of S. pneumoniae isolates including serotype distribution and antimicrobial susceptibility in Tehran, Iran.Methods: A total of 80 S. pneumoniae samples were collected from patients admitted to Shariati hospital over two periods. Half of the isolates were collected from February to September 2017 and the other half from July 2018 to March 2019. The antimicrobial susceptibility testing and PCV-13 serotype coverage of S. pneumoniae isolates were evaluated among patients with invasive and non-invasive infections.Results: The most common serotypes were 23F (17.5%), 14 (16.3%), 3 (16.3%) 19F (12.5%), and 19A (12.5%) in the present study. The vaccine coverage rates of PCV-7, PCV-10 and PCV-13 were 52.6%, 52.6%, and 83.7%, respectively. S. pneumoniae isolates with the serotype of the PCV-13 showed an increasing trend during the study. Nearly half of the S. pneumoniae strains were MDR, while MDR serotype 19A increased (40%) during the study periods. A small minority of isolates (16%) belonged to non-vaccine serotypes, 65% of which were assigned to MDR. In general, the frequency of penicillin resistant and MDR strains were estimated about 27.5% and 51%, respectively. An increase was observed in resistance to erythromycin and co-trimoxazole.Conclusion: The results showed that majority of the circulating serotypes in our study are related to PCV-13 serotypes. The use of conjugate vaccine in the immunization program and surveillance of antimicrobial resistance can be effective in reducing the pneumococcal clinical burden.Keywords: Streptococcus pneumoniae, serotype, pneumococcal conjugate vaccine, PCV, antibiotic susceptibility, multi-drug resistance, MDR

Scene understanding of full-scale 3D models of an urban area remains a challenging task. While advanced computer vision techniques offer cost-effective approaches to analyse 3D urban elements, a precise and densely labelled dataset is quintessential. The paper presents the first-ever labelled dataset for a highly dense Aerial Laser Scanning (ALS) point cloud at city-scale. This work introduces a novel benchmark dataset that includes a manually annotated point cloud for over 260 million laser scanning points into 100'000 (approx.) assets from Dublin LiDAR point cloud [12] in 2015. Objects are labelled into 13 classes using hierarchical levels of detail from large (i.e., building, vegetation and ground) to refined (i.e., window, door and tree) elements. To validate the performance of our dataset, two different applications are showcased. Firstly, the labelled point cloud is employed for training Convolutional Neural Networks (CNNs) to classify urban elements. The dataset is tested on the well-known state-of-the-art CNNs (i.e., PointNet, PointNet++ and So-Net). Secondly, the complete ALS dataset is applied as detailed ground truth for city-scale image-based 3D reconstruction., Comment: Accepted to the 30th British Machine Vision Conference