Metagenomics and functional genomics of bacterial symbionts of Spongia (Porifera, Dictyoceratida) specimens from the Algarvian shore (South Portugal)

Sponges are early-branched, filter-feeding metazoans that usually harbor complex microbial communities comprised of diverse “uncultivable” symbiotic bacteria. In this thesis, the functional and taxonomic features of the marine sponge microbiome are determined, using Spongia officinalis as model host organism. Emphasis is given to adaptive and functional traits of the profuse and biotechnologically-relevant alphaproteobacterial symbionts of sponges. A metagenomics-centred approach was employed to reveal microbial taxa and genomic signatures enriched in the Spongia officinalis endosymbiotic consortium, and thus likely to play pivotal roles in holobiont functioning. Further, a comparative genomics study is presented unveiling the common and specific traits of ten Alphaproteobacteria genera isolated from S. officinalis with alternative symbiont cultivation methodology. Finally, a sequence composition-dependent binning approach is employed to assemble, from metagenomic sequences, the genome of an uncultured alphaproteobacterial symbiont of S. officinalis belonging to the family Rhodospirillaceae. High abundance of polyketide and terpene synthase-, eukaryotic-like protein- (ELPs), type IV secretion system-, plasmid- and ABC transporter-encoding genes, among others, characterized the sponge microbial metagenomes. In contrast, motility and chemotaxis genes were abundant in seawater and sediment microbiomes, but nearly absent in the S. officinalis symbiotic consortium. Much higher frequencies of anti-viral CRISPR-Cas and restrictionmodification systems, along with much lower viral abundances, were observed in the spongeassociated metagenomes than in the environment and interpreted as true hallmarks of this symbiotic consortium. In line with outcomes retrieved for the whole symbiotic community, alphaproteobacterial symbionts of marine sponges likely contribute the most to host fitness through nutritional exchange, cell detoxification processes and chemical defense, the latter being theoretically promoted by both polyketide and terpenoid biosynthesis. The several alphaproteobacterial cultures retrieved in this thesis, displaying high natural product biosynthesis capacities, can now be explored in studies aiming at revealing novel biological activities and chemical structures from these symbionts.As esponjas marinhas (filo Porifera) são consideradas um dos mais simples grupos entre os metazoários em função de sua falta de organização em tecidos e órgãos verdadeiros. Porém, estes animais relativamente simples em termos de plano corporal normalmente abrigam comunidades muito complexas de microorganismos. Em função de seu surgimento basal na história evolutiva do planeta, o conhecimento a respeito deste “holobionte”, isto é, o consórcio de organismos formado pela esponja marinha hospedeira e todos os seus simbiontes microbianos, possui grande relavância ao avanço da nossa compreensão sobre as interações hospedeiro-microorganismos. Nesta tese de doutoramento, tive como objetivo a determinação das características funcionais e taxonómicas do microbioma das esponjas marinhas no contexto de seu ambiente circundante (água e sedimentos marinhos, e suas respecticvas microbiotas), dando ênfase aos traços adaptativos e funcionais de alfaproteobactérias associadas ao organismo modelo Spongia officinalis (“bath sponge”)

A Generalized Optimal Planning Platform for Microgrids of Remote Communities Considering Frequency and Voltage Regulation Constraints

Access to electricity is a key factor behind development and expansion of modern societies, and electric power systems are the backbone infrastructure for economic growth of nations and communities. However, more than a billion people all over the world have no or limited access to electricity and are deprived of basic services. Furthermore, there are many communities that rely on small-scale isolated microgrids to supply their electric power demands, and many challenges exist in keeping those microgrids operating. The cost of operating isolated microgrids is a major issue which impacts the availability of a proper power network in remote communities. Hence, many organizations, communities and governments around the world are looking into alternative options for electrification of remote communities by considering Renewable Energy (RE) resources, such as wind and solar power, and utilization of Energy Storage Systems (ESS). This thesis investigates the feasibility of RE deployment in remote communities, by proposing a generalized optimal planning platform and conducting comprehensive simulation studies based on real measured data, and evaluates the impact of economic, technical and operation constraints on the planning of an isolated microgrid involving conventional generation, RE resources and ESS. This work suggests that further investigation should be made on the potential impacts of the integration of RE resource on systems operation constraints, such as frequency and voltage regulation, and the results justify the importance of such investigations. Detailed studies on the impact of operation constraints on the planning and sizing of the microgrid are performed. The impact of ESS on planning studies and its potential role in system operation are analyzed. Furthermore, the impact of RE integration on reduction of diesel generation and thus carbon footprint in remote communities is evaluated. The inclusion of a demand response management strategy in microgrid planning problem is considered and its impact on the integration of RE and ESS in remote communities is analyzed. The proposed planning platform is applied to the microgrid of Kasabonika Lake First Nation (KLFN), a northern Ontario remote community. The results indicate that RE and ESS integration projects are achievable considering alternative incentives and funding resources. It is also shown that frequency regulation constraints have remarkable impact on the sizing of the RE units and ESS. A sensitivity analysis is also performed in order to study the effect of variable parameters on the optimal design of the microgrid at KLFN

Evaluation of Demand Forecast Models for Urban Carsharing

RÉSUMÉ : Au cours des dernières décennies, les services de mobilité partagée ont été créés en tant que nouvelles alternatives de transport urbain. Le système d'autopartage est l'un de ces services récents impliquant une flotte de véhicules dispersés dans une ville. Cela a permis de contrecarrer certains problèmes, tels que le stationnement limité dans les zones denses de la ville, la pollution, l’augmentation de la possession automobile, etc. Communauto est l’un des plus anciens services d’auto-partage en Amérique du Nord, établi depuis 1994 au Canada. Le but de ce mémoire est d’appliquer les méthodes d’apprentissage automatique les plus courantes afin de prévoir les heures et les kilomètres consommés selon les réponses souhaitées sur le système opérateur de Communauto avec deux services urbains à Montréal : régulier et en libre-service. La combinaison de différents modèles statistiques et de réseaux de neurones artificiels a été évaluée par le biais d’un ensemble d’expériences afin de prévoir la demande à partir de données historiques. Les modèles appliqués mettent l'accent sur la mise en œuvre de régressions multiples, d'arbres de régression, de forêts aléatoires, de gradient boosting, et des réseaux neuronaux récurrents basés sur long short-term memory et les gated recurrent unit. Les modèles ont été appliqués aux données de Communauto Montréal. Par la suite des données supplémentaires, telles que les informations sur les journées de vacances et les conditions météorologiques, ont été associées aux données de Communauto Montréal afin de déterminer si les performances des modèles de prévision sont améliorées. Il est à noter que les données relatives au service régulier et aux heures consommées, en tant que réponse, ont été prises en compte pour le processus de prévision. Les modèles ont été évalués par l’erreur quadratique moyenne sous forme d’indice de mesure de distance entre les valeurs réelles et les valeurs prédites sur la base des ensembles de test. Les ensembles de tests ont été examinés séparément dans les délais suivants : 2012, 2013, 2014 et 2015 à 2016. La moyenne des résultats a ensuite été considérée comme l'erreur finale de chaque modèle. Les résultats montrent que les modèles statistiques tels que l’intensification du gradient en service régulier par rapport au nombre d’heures consommées (avec un taux d’erreur = 1437,48) étaient supérieurs aux modèles de réseaux neuronaux artificiels (taux d’erreur de LSTM = 2159,05, taux d’erreur de GRU = 2215,14). De plus, des facteurs supplémentaires ont amélioré la capacité des modèles de prévision, le taux d'erreur de renforcement du gradient ayant été considérablement réduit à 1211,96. De plus, les résultats des modèles de prévision en service flottant en ce qui concerne le nombre d'heures consommées et le kilométrage montrent que la régression multiple surpasse les modèles de réseau neuronal artificiel. En outre, les facteurs supplémentaires ont considérablement amélioré les performances des modèles appliqués.----------ABSTRACT : In the last few decades, shared mobility services have been made as new urban transport alternatives. Carsharing system is one of these recent services that involves a fleet of scattered vehicles in a city. This helped to counteract some problems, such as limited parking within city in dense areas, pollution, increase in car ownership, etc. Communauto is one of the oldest carsharing services in North America which has been established since 1994 in Canada. The focus of this thesis is to apply the most common machine learning methods in order to forecast consumed hours and kilometers driven or mileage as desired responses at Communauto operator system with two urban services in Montreal: regular and free-floating. Combination of different statistical and artificial neural network models were evaluated through a set of experiments in order to forecast demand from historical data. The applied models include multiple regression, regression tree, random forests, gradient boosting, long short-term memory and gated recurrent unit based recurrent neural networks. The models were applied to the Montreal Communauto data. Thereafter, additional factors such as holiday information and weather condition were engaged to the Communauto data to explore whether the performance of forecasting models was enhanced. It is noteworthy that the data related to regular service and consumed hours, as response, were considered for the forecasting process. The models were evaluated by root mean squared error as an index of distance measurement between real and predicted values based on test sets. The test sets were considered separately in the following time frames: 2012, 2013, 2014, and from 2015 to 2016. The average of results was then considered as the final error of each model. The results show that statistical models such as gradient boosting in regular service with respect to consumed hours (with error rate= 1437.48) outperformed artificial neural network models (error rate of LSTM = 2159.05, error rate of GRUs = 2215.14). Moreover, additional factors improved the ability of the forecasting models, as the error rate of gradient boosting was significantly reduced to 1211.96. Furthermore, the results of forecasting models in free-floating service with respect to consumed hours and mileage show that multiple regression outperformed artificial neural network models. Besides, the additional factors significantly improved performance of the applied models

Antimicrobial peptide expression in a wild tobacco plant reveals the limits of host-microbe-manipulations in the field

Plant-microbe associations are thought to be beneficial for plant growth and resistance against biotic or abiotic stresses, but for natural ecosystems, the ecological analysis of microbiome function remains in its infancy. We used transformed wild tobacco plants (Nicotiana attenuata) which constitutively express an antimicrobial peptide (Mc-AMP1) of the common ice plant, to establish an ecological tool for plant-microbe studies in the field. Transgenic plants showed in planta activity against plant-beneficial bacteria and were phenotyped within the plants´ natural habitat regarding growth, fitness and the resistance against herbivores. Multiple field experiments, conducted over 3 years, indicated no differences compared to isogenic controls. Pyrosequencing analysis of the root-associated microbial communities showed no major alterations but marginal effects at the genus level. Experimental infiltrations revealed a high heterogeneity in peptide tolerance among native isolates and suggests that the diversity of natural microbial communities can be a major obstacle for microbiome manipulations in nature

Frequency of Self-Medication and Knowledge about Out-of-Counter Drugs during the COVID-19 Pandemic in a Group of Iranian Dental Students

Objective: To study the frequency of self-medication and knowledge about out-of-counter drugs during the COVID-19 pandemic in a group of Iranian dental students. Material and Methods: A descriptive cross-sectional study was conducted among dental undergraduates from September 2021 to November 2021 after receiving ethical clearance from the Kerman Medical University Ethical Committee. A valid and reliable questionnaire, consisting of demographic data and questions about self-medication and knowledge about out-of-counter drugs, was sent to participants via E-mail. Data was analyzed by SPSS 26 software by using a t-test. The P-value was considered at a 0.05% significant level. Results: A total of 88 students participated in the study with a mean age of 21.39±3.71 years. Prevalence of self-medication was found in 53.4%. The most common cause for self-medication was headache. Acetaminophen was the most commonly used medicine for self-medication. Females had more self-medication than males, but there was no significant differences. There was no significant differences between entering year to university and self-medication. Younger students had significantly more self-medication (p=0.007). Knowledge about out-of-counter drugs was moderate. Conclusion: Moderate self-medication as noticed. The out-of-counter drugs were the most used. Although out-of-counter drugs seem relatively safe, their improper use can cause serious side effects. Dental students need to be educated regarding appropriate safe medication and out-of-counter drugs

Fully-automated tongue detection in ultrasound images

Tracking the tongue in ultrasound images provides information about its shape and kinematics during speech. In this thesis, we propose engineering solutions to better exploit the existing frameworks and deploy them to convert a semi-automatic tongue contour tracking system to a fully-automatic one. Current methods for detecting/tracking the tongue require manual initialization or training using large amounts of labeled images. This work introduces a new method for extracting tongue contours in ultrasound images that requires no training nor manual intervention. The method consists in: (1) application of a phase symmetry filter to highlight regions possibly containing the tongue contour; (2) adaptive thresholding and rank ordering of grayscale intensities to select regions that include or are near the tongue contour; (3) skeletonization of these regions to extract a curve close to the tongue contour and (4) initialization of an accurate active contour from this curve. Two novel quality measures were also developed that predict the reliability of the method so that optimal frames can be chosen to confidently initialize fully automated tongue tracking. This is achieved by automatically generating and choosing a set of points that can replace the manually segmented points for a semi-automated tracking approach. To improve the accuracy of tracking, this work also incorporates two criteria to re-set the tracking approach from time to time so the entire tracking result does not depend on human refinements. Experiments were run on 16 free speech ultrasound recordings from healthy subjects and subjects with articulatory impairments due to Steinert’s disease. Fully automated and semi automated methods result in mean sum of distances errors of 1.01mm±0.57mm and 1.05mm± 0.63mm, respectively, showing that the proposed automatic initialization does not significantly alter accuracy. Moreover, the experiments show that the accuracy would improve with the proposed re-initialization (mean sum of distances error of 0.63mm±0.35mm)

Maternal serum levels of C-reactive protein at early pregnancy to predict fetal growth restriction and preterm delivery: A prospective cohort study

Background: A considerable evidence suggests that maternal inflammation dysregulation may play as a risk factor for both maternal and neonatal outcomes. Objective: The study’s objectives were designed to evaluate the correlation between serum C-reactive protein (CRP) levels, as an inflammation factor, preterm delivery, and small for gestational age (SGA) births. Materials and Methods: This prospective cohort study was conducted on 120 singleton pregnant women with gestational age less than 20 wk. Maternal CRP serum concentration was measured before 20 wk gestation. Patients were followed-up until the delivery and final outcomes of pregnancy were recorded in terms of preterm delivery and SGA births. Results: Serum CRP levels in participants with normal fetuses and SGA births were 4.09 ± 1.35 mg/l and 6.04 ± 3.29 mg/l, respectively (p = 0.19), while in cases of preterm delivery, it was 9.63 ± 5.78 mg/l (p < 0.001). By using receiver operating characteristic (ROC) curve, serum CRP levels (cut-off point 5.27 mg/l, area 0.836) had acceptable diagnostic accuracy value in distinguishing preterm delivery (sensitivity (75%), specificity (86.1%), positive predictive value (37.5%), negative predictive value (96.87%), accuracy (85%)) and serum CRP levels (cut-off point 6.67 mg/l, area 0.673) in distinguishing SGA births (sensitivity (50%), specificity (91.2%), positive predictive value (23.07%), and negative predictive value (97.19%), and accuracy (89.16 %)). Conclusion: Higher maternal serum CRP levels measured early in pregnancy may associate with higher risk of preterm delivery and SGA. Key words: C-reactive protein, Small for gestational age, Preterm birth

Association between the dietary inflammatory index and markers of endothelial and systemic inflammation in hemodialysis patients

ObjectivesThe current survey aimed to investigate the link between energy-adjusted dietary inflammatory index (E-DII) and risk factors for CVD including markers of endothelial and systemic inflammation in Iranian hemodialysis patients.MethodsPatients on hemodialysis for at least 6 months prior to enrollment were considered eligible in this cross-sectional study. The usual dietary intakes of the hemodialysis individuals were examined through 4 non-consecutive days including 2 dialysis days and 2 non-dialysis days using a 24-h recall approach to calculate E-DII. Multiple linear regression analysis was utilized to investigate the link between E-DII and selected biomarkers of inflammation and oxidative stress including high-sensitive C reactive protein (hs-CRP), serum intercellular adhesion molecule (sICAM), serum vascular cell adhesion molecule (sVCAM), malondialdehyde, and nitric oxide (NO), sE-selectin, and endothelin-1, and beta (β) and 95% confidence interval (CI) was reported. Value of p < 0.05 was considered statistically significant.ResultsOverall, 291 hemodialysis patients make up our study population. In the crude model, the E-DII score was positively associated with a higher sVCAM-1 (β = 177.39; 95% CI: 60.51, 294.26; ptrend = 0.003). Further adjustment for potential confounders attenuated the findings in a way that an increase of 128.72 in the sVCAM-1 was observed when the E-DII score increased from −2.68 to −1.14 (95% CI: 13.50, 243.94). After controlling for potential confounders, E-DII was associated with sE-selectin in hemodialysis patients in the highest category of E-DII as compared to the lowest category (β = 4.11; 95% CI: 0.22, 8.00; ptrend = 0.039).ConclusionThe present findings suggest that adherence to a pro-inflammatory diet among hemodialysis patients is associated with a higher inflammatory status as evidenced by sVCAM-1 and sE-selectin; however, bidirectionality may exist and the role of residual confounders should be taken into account. Therefore, more longitudinal investigations are needed to elucidate the role of diet on the inflammatory status of hemodialysis patients

Outcome of cryopreserved-thawed embryo transfer in the GnRH agonist versus antagonist protocol

Abstract Background: GnRH agonist and antagonist were developed to control the premature release of LH surge. There is some difference between two protocols. Objective: We compared the outcome of frozen-thawed embryo transfer in infertile women who used GnRH agonist or antagonist protocol for previous COH cycle and evaluation of any adverse effect of GnRH antagonist on oocyte and embryo. Materials and Methods: The study group included all infertile women who referred to Yazd Research and Clinical Center for Infertility. Overall 20-35 years old women who were candidate for frozen-thawed embryo transfer with regard to inclusion and exclusion criteria were participated in the study. The patients based on previous control ovarian stimulation (COH) protocol divided in to two groups: GnRH agonist long protocol (n=165) and GnRH antagonist multiple dose protocol (n=165). Frozen-thawed embryos were transferred after endometrial preparation in both groups. Main outcome measures were: implantation, chemical and clinical pregnancy rate. Results: The implantation and clinical pregnancy rate following cryopreserved embryo transfer in GnRH agonist group and antagonist group were 16.3% vs. 15.7% (p=0.806) and 38.1% (63/165) vs. 36.9% (61/165) (p=0.915) and chemical pregnancy rate was 44.8% (74/165) vs. 43.6% (72/165) (p=0.915) respectively. Conclusion: There was no statistically difference between two groups in terms of implantation and pregnancy rate. Although pregnancy rate in fresh embryo transfer in antagonist cycles was lower than agonist groups, Therefore decrease in these parameters might be due to detrimental effect of GnRH antagonist on the endometrium, not embryo or oocyte

Prevalence of Nephrolithiasis in 7-11 year-old Students: A Multicenter Study

Introduction: Renal diseases can be asymptomatic even in progressive disorders; therefore, detecting urine and ultrasound abnormalities may help facilitate early diagnosis and prevention of renal diseases. This study was conducted to investigate random urine parameters and urinary system ultrasonography findings in 7-11 year-old students.Materials and Methods: Healthy students from Tehran and Qom, Iran were enrolled in a prospective descriptive study and their sex, age, weight, height, and BMI were measured. Then, a fresh clean urine sample was collected and ultrasonography of the urinary tract was done. The urine specimen was tested for urine Ca/Cr, urine oxalate/Cr, and urine citrate/Cr.Results: Of 932 students, 47.9% were female and 52.1% were male. The age range of the students was 7-11 years with a mean age of9.08 years. A history of renal disease and UTI was positive in 1.1% and 9.9% of the students, respectively. Ultrasound was normal in78% and abnormal in 22% of the students. Abnormal findings included hydronephrosis in 1.1%, fullness of the urinary tract in 0.1%, urinary system duplication in 3%, urolithiases in 0.7%, decreased kidney size in 0.4%, increased bladder thickness in 8.9%, and other abnormal findings in 7.8% of the subjects. Abnormal urine findings included hypercalciuria, in 10.9%, urine hyperuricosuria in 5.4%, urine hyperoxaluria in 12.8%, and hypocitraturia in 96.9% of the students.Conclusions: According to the results, nephrolithiasis may be due to hyperoxaluria, hypercalciuria, and hyperuricosuria in a normal population. Genetics and nutrition are more important risk factors. Therefore, some nutritional interventions for decreasing urine oxalate, calcium, and uric acid may be beneficial. Keywords: Urinalysis; Ultrasonography; Hypercalciuria; Hyperuricosuria; Hyperoxaluria; Child