Development of workflow for picornavirus genome sequence analysis

Picornaviruses are small, non-enveloped, icosahedral, positive stranded RNA viruses and among the most common human pathogens. Some of the clinically important genera for humans are Enterovirus, Hepatovirus, Parechovirus and Cardiovirus. The symptoms for tthe picornaviral infections range from mild, asymptomatic to fatal disease. Threats posed to human health by these viruses is observedd in the constant outbreaks of enteroviruses and parechoviruses in the different parts of the world. Next generation sequencing provides an efficient way to detect and identify known or novel micro-organisms. Advantages of NGS are rapid sequencing methods, high-throughput process and affordable costs. On the other hand, NGS also requires advanced technical and computational skills, and creates a bottleneck owing to necessity of standardization of bioinformatic tools. It is therefore imperative to optimize and determine parameters, which provide accuracy in every stage of NGS workflow. The aim of this thesis was to develop a rapid and straightforward, user-friendly workflow for the assembly and analysis of picornaviral genomes. Chipster platform was chosen as the primary test platform. The workflow involved use of automated analysis pipelines (VirusDetect and A5 assembly pipeline), and alternative approaches, which included pre-processing of raw data, and reference-mapping or de novo assembly (Velvet and SPAdes) of picornavirus sequences. Except for de novo assembly and validation and quality assessment of final outputs, all steps were performed in Chipster. Of these approaches, VirusDetect and reference-mapping were not successful. A5 pipeline for microbial genome assembly was found to be very suited for picornavirus identification. Velvet and SPAdes also performed well, but Velvet assembler was found to more computationally exhaustive and time consuming. Quality assessment suggested that performance of SPAdes was relatively better than the performance of A5 or Velvet. As A5 pipeline does not require any parameter settings, it can be used as initila identification and contig/scaffold generation method for picornaviral sequences. Together with implementation of de novo assembler(s) on Chipster platform a novel, user-friendly NGS workflow for picornavirus sequence assembly can be established

“A Switch Went off in my Whole Body”: Lived Experiences of Fatigue and Post-Exertional Malaise in Long Covid

The growing HCI agenda on health has focused on different chronic conditions but less so on Long Covid, despite its severe impact on the quality of life. We report findings from 2 workshops with 13 people living with Long Covid, indicating the challenges of making sense of their physical, cognitive, and emotional symptoms, and of monitoring the triggers of post-exertional malaise. While most participants engage in pacing activities for the self-management of fatigue, only a few are aware of the importance of planning all their daily activities and routines in order to avoid post-exertional malaise. We conclude with design implications to support lightweight tracking and sensemaking of fatigue symptoms, novel data analytics for monitoring the triggers of post-exertional malaise and the worsening of symptoms, and support for self-management in order to prevent post-exertional malaise

Understanding patterns of fatigue in health and disease : protocol for an ecological momentary assessment study using digital technologies

Peer reviewe

Distinct Diet-Microbiota-Metabolism Interactions in Overweight and Obese Pregnant Women: a Metagenomics Approach

Diet and gut microbiota are known to modulate metabolic health. Our aim was to apply a metagenomics approach to investigate whether the diet-gut microbiota-metabolism and inflammation relationships differ in pregnant overweight and obese women. This cross-sectional study was conducted in overweight (n = 234) and obese (n = 152) women during early pregnancy. Dietary quality was measured by a validated index of diet quality (IDQ). Gut microbiota taxonomic composition and species diversity were assessed by metagenomic profiling (Illumina HiSeq platform). Markers for glucose metabolism (glucose, insulin) and low-grade inflammation (high sensitivity C-reactive protein [hsCRP], glycoprotein acetylation [GlycA]) were analyzed from blood samples. Higher IDQ scores were positively associated with a higher gut microbiota species diversity (r = 0.273, P = 0.007) in obese women, but not in overweight women. Community composition (beta diversity) was associated with the GlycA level in the overweight women (P = 0.04) but not in the obese. Further analysis at the species level revealed a positive association between the abundance of species Alistipes finegoldii and the GlycA level in overweight women (logfold change = 4.74, P = 0.04). This study has been registered at ClinicalTrials.gov under registration no. NCT01922791 (https://clinicaltrials.gov/ct2/show/NCT01922791).</p

Improving women’s diet quality pre-conceptionally and during gestation: effects on birth weight and prevalence of low birth weight; a randomized controlled efficacy trial in India (Mumbai Maternal Nutrition Project)

BACKGROUND: Low birth weight (LBW) is an important public health problem in undernourished populations.OBJECTIVE: We tested whether improving women's dietary micronutrient quality before conception and throughout pregnancy increases birth weight in a high-risk Indian population.DESIGN: The study was a nonblinded, individually randomized controlled trial. The intervention was a daily snack made from green leafy vegetables, fruit, and milk (treatment group) or low-micronutrient vegetables (potato and onion) (control group) from ? 90 d before pregnancy until delivery in addition to the usual diet. Treatment snacks contained 0.69 MJ of energy (controls: 0.37 MJ) and 10-23% of WHO Reference Nutrient Intakes of ?-carotene, riboflavin, folate, vitamin B-12, calcium, and iron (controls: 0-7%). The primary outcome was birth weight.RESULTS: Of 6513 women randomly assigned, 2291 women became pregnant, 1962 women delivered live singleton newborns, and 1360 newborns were measured. In an intention-to-treat analysis, there was no overall increase in birth weight in the treatment group (+26 g; 95% CI: -15, 68 g; P = 0.22). There was an interaction (P &lt; 0.001) between the allocation group and maternal prepregnant body mass index (BMI; in kg/m(2)) [birth-weight effect: -23, +34, and +96 g in lowest (&lt;18.6), middle (18.6-21.8), and highest (&gt;21.8) thirds of BMI, respectively]. In 1094 newborns whose mothers started supplementation ? 90 d before pregnancy (per-protocol analysis), birth weight was higher in the treatment group (+48 g; 95% CI: 1, 96 g; P = 0.046). Again, the effect increased with maternal BMI (-8, +79, and +113 g; P-interaction = 0.001). There were similar results for LBW (intention-to-treat OR: 0.83; 95% CI: 0.66, 1.05; P = 0.10; per-protocol OR = 0.76; 95% CI: 0.59, 0.98; P = 0.03) but no effect on gestational age in either analysis.CONCLUSIONS: A daily snack providing additional green leafy vegetables, fruit, and milk before conception and throughout pregnancy had no overall effect on birth weight. Per-protocol and subgroup analyses indicated a possible increase in birth weight if the mother was supplemented ? 3 mo before conception and was not underweight. This trial was registered at www.controlled-trials.com/isrctn/ as ISRCTN62811278<br/

Development of a smart-phone based augmented reality view application for driver assistance systems

The goal of this thesis is to develop a smartphone application for augmented reality view; it is an initial attempt to realize a driver assistance functionality using just a smartphone and an external lens. Initially it depicts a brief analysis about the most feasible development technologies for mobile application development, selecting a proper lens and positioning of the smartphone in the car. Later, it discusses the strategies for real-time object detection using OpenCV; the video frames are processed using the strategies to find patterns in the videos. Different techniques like Hough-line transform, watershed, contour detection, color segmentation, color thresholding and HAAR cascades are implemented and compared in terms of real time detection of the desired objects. Then a unified algorithm is implemented for the given scenario which overcomes the challenges faced during the conceptualization phase. Finally, the results are depicted with the snapshots of the real time detection done from the smartphone and then evaluated against the vision of the application and the achieved tasks. This thesis is concluded by stating the prospects of this mobile application in the future

Self-presentation and authenticity on LinkedIn: a comparative study of Singapore and India-based entrepreneurs

Entrepreneurs‘ self-presentations on LinkedIn offer a glimpse into their contrived performances of professionalism. They tell us who they think they are, what they do, and what they aim for. Through a mixed methods research of content analysis of LinkedIn profiles and semi-structured interviews with entrepreneurs in India and Singapore, I found that entrepreneurs claim that their self-presentation on LinkedIn is authentic and reflective of their true selves. Entrepreneurs in Singapore perform authenticity and practice personal branding while entrepreneurs in India think that personal branding and authenticity cannot co-exist. Subsequently, dilemmas emerge from performances of authenticity in self-presentation and personal branding which are intensified by social contexts and online-offline continuum. This study builds on prior scholarship on social networking sites, self, self-presentation, identity, entrepreneurs, and authenticity as a social process and interactional performance.Master of Art

“A switch went off in my whole body” – lived experiences of fatigue and post-exertional malaise in Long Covid

The growing HCI agenda on health has focused on different chronic conditions but less so on Long Covid, despite its severe impact on the quality of life. We report findings from 2 workshops with 13 people living with Long Covid, indicating the challenges of making sense of their physical, cognitive, and emotional symptoms, and of monitoring the triggers of post-exertional malaise. While most participants engage in pacing activities for the self-management of fatigue, only a few are aware of the importance of planning all their daily activities and routines in order to avoid post-exertional malaise. We conclude with design implications to support lightweight tracking and sensemaking of fatigue symptoms, novel data analytics for monitoring the triggers of post-exertional malaise and the worsening of symptoms, and support for self-management in order to prevent post-exertional malaise

“A Switch Went off in my Whole Body”: Lived Experiences of Fatigue and Post-Exertional Malaise in Long Covid

The growing HCI agenda on health has focused on different chronic conditions but less so on Long Covid, despite its severe impact on the quality of life. We report findings from 2 workshops with 13 people living with Long Covid, indicating the challenges of making sense of their physical, cognitive, and emotional symptoms, and of monitoring the triggers of post-exertional malaise. While most participants engage in pacing activities for the self-management of fatigue, only a few are aware of the importance of planning all their daily activities and routines in order to avoid post-exertional malaise. We conclude with design implications to support lightweight tracking and sensemaking of fatigue symptoms, novel data analytics for monitoring the triggers of post-exertional malaise and the worsening of symptoms, and support for self-management in order to prevent post-exertional malaise

“A switch went off in my whole body”:Lived experiences of fatigue and post-exertional malaise in long Covid

The growing HCI agenda on health has focused on different chronic conditions but less so on Long Covid, despite its severe impact on the quality of life. We report findings from 2 workshops with 13 people living with Long Covid, indicating the challenges of making sense of their physical, cognitive, and emotional symptoms, and of monitoring the triggers of post-exertional malaise. While most participants engage in pacing activities for the self-management of fatigue, only a few are aware of the importance of planning all their daily activities and routines in order to avoid post-exertional malaise. We conclude with design implications to support lightweight tracking and sensemaking of fatigue symptoms, novel data analytics for monitoring the triggers of post-exertional malaise and the worsening of symptoms, and support for self-management in order to prevent post-exertional malaise