Adequate placental function is essential for the growth and development of a healthy fetus. A major cause of abnormal placental function is thought to occur from inadequate maternal spiral artery remodelling, leading to maternal vascular malperfusion (MVM) of the placenta and ultimately fetal growth restriction (FGR) and stillbirth due to uteroplacental hypoxia. Current methods of investigating a pregnancy at risk of FGR rely on ultrasound estimations of fetal size and Doppler studies. A more informative measure may be to quantify placental function in-vivo. Magnetic resonance imaging (MRI) has the ability to assess placental oxygen saturation (sO2), using Blood Oxygen-Level Dependent (BOLD), and the partial pressure of oxygen (pO2) using Oxygen-Enhanced MRI (OE MRI). These MRI techniques have been shown to correlate with gestation and poor pregnancy outcomes in cross sectional studies. MRI measures of placental oxygenation are hypothesised to be a potential antenatal tool for the identification and stratification of high risk pregnancies at risk of FGR related to uteroplacental hypoxia. To address this hypothesis changes in placental oxygenation, following maternal hyperoxia, were calculated in normal and FGR pregnancies in a cross sectional study. The change in placental oxygenation was reproduced longitudinally to determine if the rate of change differed between normal and FGR pregnancies. Baseline placental MRI parameters (R1 and R2*) and measures of the change in oxygenation were incorporated into a diagnostic model to identify FGR related to uteroplacental hypoxia, which was provisionally tested in a group of high risk pregnancies to demonstrate its potential clinical utility. Placental measures of baseline R1 and R2* were significantly increased in FGR pregnancies. The change in placental pO2 following hyperoxia was found to be significantly lower in FGR pregnancies. The change in pO2 declined similarly with gestation in both cross sectional and longitudinal studies, in normal and FGR pregnancies. There were no significant correlations in the change in placental sO2 with gestation or pregnancy outcome. The use of a diagnostic model combining baseline R1 and R2* and pO2 measures identified FGR with a high specificity, and provided additional information to aid in disease stratification and decision making in a significant proportion of the high risk pregnancies tested. In conclusion, MRI parameters of placental pO2 following hyperoxia are significantly lower in FGR pregnancies, in keeping with the concept of uteroplacental hypoxia. MRI techniques show promise in the identification of FGR pregnancies related to MVM through measures of placental function, irrespective of fetal size, and may aid in the disease stratification of high risk pregnancies.

This thesis deals with description and verification of different methods of DNA isolation from insect tissue of order Lepidoptera -- butterflies with an emphasis on family Sphingidae -- hawk moths and subsequent amplification of COI gene by PCR method. All tested methods were compared and evaluated in terms of efficiency, yield and purity of the DNA isolation, duration and financial costs. We selected to establish a methodology which is sufficient for obtaining COI gene sequences using genetic analyzer, its application in the system BoldSystems and subsequent determination of the sample. This is important in effort to map the species diversity.

In many regions worldwide, older adults now form the fastest growing portion of the population. As such, aging research has seen tremendous growth in recent years, with a focus on identifying early biomarkers of age-related disease. However, crucial to understanding age-related disease is to identify what constitutes normal brain aging, and the life-course factors associated with positive outcomes in later life. In support of this goal, the current dissertation is comprised of three manuscripts that aim to investigate the functional and structural correlates of normal aging in a sample of community-dwelling younger and older adults, from both a multimodal and multi-analysis perspective. Study 1: The first study examined how cumulative cardiovascular risk and self-reported levels of physical, social, and cognitive activity are associated with differences in hippocampal volumes in early and later adulthood. Results indicated that greater cumulative cardiovascular risk was associated with smaller hippocampal volumes across age cohorts. Moreover, a negative association found between frequency of social activities and bilateral hippocampal volumes in older adults, suggesting that social activities with a low cognitive load may not be beneficial to structural brain outcomes in older age. Study 2: This study employed novel advances in functional magnetic resonance imaging (fMRI) to study fluctuations in the blood-oxygen-level dependent (BOLD) signal in relation to age and markers of brain health. Specifically, the study examined the relationship between resting-state BOLD variability and markers of both vascular health and lifestyle activity levels. Results indicated that resting-state BOLD variability is increased in older relative to younger adults. The findings also suggest that the association between BOLD variability and lifestyle activity levels may differ depending on age. Study 3: The final study aimed to further investigate the origins of the BOLD variability signal by examining the feasibility of combining functional near infrared spectroscopy (fNIRS) with fMRI brain signal fluctuation data. In addition to providing proof of concept of combining fNIRS hemoglobin metrics with fMRI BOLD variability maps, the results of this study also indicate that the patterns of regional association between resting hemoglobin concentrations and BOLD fluctuations may vary according to age cohort. Together, the three studies comprising this dissertation illustrate the value of adopting a multimodal, life-course perspective in the study of normal aging. These findings also support increasing evidence of a relationship between the BOLD variability signal and age. Given the limitations of cross-sectional designs for demonstrating change over time, longitudinal investigations with larger sample sizes across multiple age groups are needed to further the development of public health measures aimed at promoting successful aging from early adulthood. / Graduate / 2022-12-08

Skeletal muscle performs essential functions, including movement and posture. Musculoskeletal disorders can disrupt these functions, leading to temporary or permanent impairment. As most muscle abnormalities will cause morphological and physiological changes in skeletal muscle, identifying diseased or injured skeletal muscle relies on having a frame of reference, i.e. a correct characterization of what is considered healthy or 'normal' skeletal muscle. Non-invasive Magnetic Resonance Imaging (MRI) techniques such as 1H Magnetic Resonance Spectroscopy (1H-MRS) to assess the biochemical environment, Magnetization Transfer (MT) to study water dynamics and Blood Oxygen Level Dependent (BOLD) signal to study blood flow and relative (de)oxy-Hb concentration have yet to be extensively explored in skeletal muscle. Therefore, to improve the knowledge of the biochemical environment of skeletal muscle, a series of experiments were performed using these techniques in calf muscles. 1H-MRS investigations showed high repeatability of metabolite quantification within and across scanning sessions despite its challenges due to the high structural organization of skeletal muscle. Furthermore, differences in the metabolic profile between endurance vs. power-oriented participants at rest were found, suggesting 1H-MRS could be used as a non-invasive technique to assess muscle fiber composition. A multimodal MT, and BOLD study were performed on exercised skeletal muscle to complement the metabolic understanding of skeletal muscle. It was shown that high-quality data could be obtained in simultaneous studies of BOLD/EMG. In addition, during a multimodal MT and BOLD acquisition, MT signal showed a decrease after exercise and was linearly correlated to the BOLD signal activation. The ability of MT to distinguish between highly/lowly activated muscle groups during exercise opens the opportunity to non-invasively investigate muscle group recruitment with a higher spatial resolution compared to EMG, and lower scanning times compared to BOLD. Overall, the main purpose of this thesis was to investigate, characterize and provide unique metrics to study the functional and metabolic profile of healthy skeletal muscle at rest and during exercise. / Thesis / Master of Applied Science (MASc) / Skeletal muscle performs vital functions such as movement, heat generation, and posture. The impact of musculoskeletal disorders, which can disrupt these functions and cause temporary or permanent impairment of physical activity and movement, is expected to grow in the future. Correctly characterizing healthy or 'normal' skeletal muscle is necessary to identify diseased or injured skeletal muscle, as most muscle abnormalities cause changes in morphology and physiology. Non-invasive MRI techniques to assess the biochemical environment, water dynamics, blood flow and relative (de)oxy-Hb concentration have yet to be extensively explored in healthy skeletal muscle. Thus, the primary purpose of this thesis was to investigate, characterize and provide unique metrics to study the functional and metabolic profile of healthy skeletal muscle at rest and during exercise. The metrics investigated can be used to establish a baseline to detect abnormal skeletal muscle.

No description available.

No description available.

An investigation into the complex function of muscle using non-invasive imaging and novel analytical approaches. / The human body is inherently complex as seen through the structural organization of muscle in terms of its contractile subunit organization and scaling, innervation patterns, and vascular organization. However, the functional complexity of muscle such as its state of oxygenation, metabolism or blood-flow has been less well explored. Thus in an effort to improve our understanding of muscle, blood oxygenation level dependent (BOLD) magnetic resonance imaging of the lower leg, at rest and during a variety of weighted plantar-flexion paradigms, at 40% maximal voluntary contraction, was employed. Prior to experimentation, on 11 healthy subjects, an ergometer and electromyogram (EMG), suitable for use within the MRI, were constructed to allow for concurrent exercise and image acquisition. After collecting muscle BOLD data, four novel techniques were using to describe muscle function. The first technique used the fractal dimension, a measure of complexity, conveying the rate of variation of muscle blood flow at rest. This technique was able to determine differences between the muscles of lower leg, which have varying distributions of muscle fibre types based on function. The second exploratory technique was the use of the phase space, which provides insight into state/state-transitions of a system over time. The phase space representation of the BOLD signal provided novel insight into the muscle activation state. It demonstrated that muscle has more than the two blood flow states of reduced levels at rest and increased levels when exercising. The third technique involved using a signal saturation (SAT) region, proximal to the imaging region, to mitigate the arterial in-flow effects to more accurately represent muscle activation. By observing the correlation between the ideal reference and recorded signal, the acquisition with the arterial suppression improved the assessment of what regions in the muscle were active in the range borderline activation, which has the highest uncertainty. The final outlook on muscle behaviour involved using measures of fatigue from the collected EMG data to develop novel metrics of fatigue based on the BOLD signal. Concurrent BOLD and EMG of the anterior compartment of the lower leg during a plantar-flexion block design, demonstrated that the change in blood-flow between rest and contracted states is an excellent indicator of muscle fatigue. The primary outlook of this thesis is to provide a unique data collection and analytic framework to describe muscle behaviour, which was achieved using non-invasive measures with a complex outlook. / Thesis / Master of Applied Science (MASc) / The human body is complex, and an incredible amount of research has been done to better understand it. Specifically, muscle is built and works in a complex way to allow us to move and perform everyday tasks. There are many diseases that affect how a muscle works, which is why there is a need to describe muscle performance when it is healthy and unhealthy. In this research, muscle behaviour is explored by taking pictures of the leg. From these pictures the blood flow in the calf and shin was measured both when staying still and when performing exercise. Four new techniques were created to describe the blood flow in the leg. The first technique measured how complex the muscle activity is, while staying still. If blood-flow changes a lot in a short amount of time, it is complex. This showed that the different components of muscle, either used for stamina or power, receive blood differently. The second technique used a different way of looking at the muscle to show that there are many different rates and amounts of blood-flow in the muscle. It revealed that muscle has more than the two blood flow options of 1) the normal level when resting and 2) the increased level when exercising. The third technique involved using an image filter to get a clean image of the muscle without the blood vessels affecting or misrepresenting the image. It was able to show what muscle regions were involved in exercise more accurately than before. The final technique involved measuring muscle electricity and blood flow at the same time, to find out when the muscle was exhausted. It demonstrated that muscle, when exhausted, showed larger changes in blood flow when going from resting to exercising. Overall, this research described how muscle performs in healthy individuals using new techniques. These techniques can now be used to compare healthy muscle to damaged/diseased muscle to determine how the muscle is recovering or to diagnose muscular disease.

Zusammenfassung Einleitung: Die Kraniotomie mit umfassender Tumorresektion bleibt Therapie der Wahl zur Behandlung von Hirntumoren. Bei der geforderten Radikalität des therapeutischen Vorgehens kommt der präoperativen Lokalisationsdiagnostik eloquenter Hirnareale eine besondere Bedeutung zu. In der vorliegenden Arbeit wird ein Verfahren vorgestellt, daß den präzisen Übertrag der Ergebnisse funktioneller MRT-Studien in die Therapie von Hirntumoren ermöglicht. Desweiteren wird das klinische Potential der fMRT untersucht. In einem hierarchischem System erfolgt die Beurteilung der klinischen Wirksamkeit der Methode zur präoperativen Lokalisationsdiagnostik eloquenter Hirnareale bei Patienten mit Hirntumoren. Methode: Bei 40 Patienten mit supratentoriellen Hirntumoren wurden insgesamt 144 präoperative funktionelle MRT-Studien durchgeführt. Die Bewertung der klinischen Wirksamkeit erfolgte in einem hierarchischem Modell unter Betrachtung der aufgeführten Dimensionen: 1. Ebene: Technische Wirksamkeit 2. Ebene: Wirksamkeit in Bezug auf die diagnostische Genauigkeit 3. Ebene: Wirksamkeit in Bezug auf das diagnostische Denken 4. Ebene: Therapeutische Wirksamkeit 5. Ebene: Wirksamkeit in Bezug auf das Patient-Outcome 6. Ebene: Wirksamkeit in Bezug auf die Gesellschaft Die Ergebnisse der funktionellen MRT-Untersuchungen wurden in ein neurochirurgisches Navigationssystem eingebracht. Intraoperativ besteht für den Operateur die Möglichkeit sich die Lagebeziehung zu den gekennzeichneten Arealen in das Okular des Operationsmikroskop einzuspielen. Ergebnisse: Das geschilderte Verfahren ermöglicht die navigierte Operation von Hirntumoren unter besonderer Berücksichtigung eloquenter- das heißt funktionstragender Hirnareale. Die beschriebene Methode zur Integration der fMRT weist ein hohe Praktikabilität auf. Wie diese Arbeit zeigen konnte, erbringt die fMRT als Methode auch bei Patienten mit Hirntumoren für die klinische Anwendung ausreichend zuverlässige Ergebnisse. Schlussfolgerung: 1. Mit dem geschilderten Verfahren gelingt die zuverlässige Integration von fMRT-Daten in die Therapie von Hirntumoren. 2. Die fMRT ist für den klinischen Einsatz zur präoperativen Lokalisation eloquenter Hirntumoren mit Einschränkungen geeignet. / Abstract Introduction: Craniotomy and maximal tumour resection remains the major therapy in patients with brain tumours. Preoperatively it is of great importance to identify eloquent brain areas. In this study we develop a method which allows the precise integration of functional MR-data into the therapy of brain tumours. Additionally we investigated the diagnostic potential of functional MRI in a clinical setting. We were assessing the effectiveness of functional MRI in patients with brain tumours in a hierarchical system. Methods: We performed 122 preoperative, functional MRI studies in 40 patients with supratentorial brain tumours. We evaluated the effectiveness in a hierarchic model. 1. level: technical effectiveness 2. level: diagnostic effectiveness 3. level: diagnostic effectiveness 4. level: therapeutical effectiveness 5. level: patient-outcome 6. level: society The acquired parametric maps were integrated into a neurosurgical navigation system. Intraoperatively the neurosurgeon can have the localisation of functional brain areas displayed within the optical system of the microscope. Conclusion: 1. The described approach allows image guided neurosurgery paying special attention to eloquent brain areas. The method is very practicable and reliable. 2. As we could demonstrate in our work, the functional MRI is sufficiently robust for clinical application

Abstract Functional communication between brain regions is likely to play a key role in complex cognitive processes that require continuous integration of information across different regions of the brain. This makes the studying of functional connectivity in the human brain of high importance. It also provides new insights into the hierarchical organization of the human brain regions. Resting-state networks (RSNs) can be reliably and reproducibly detected using independent component analysis (ICA) at both individual subject and group levels. A growing number of ICA studies have reported altered functional connectivity in clinical populations. In the current work, it was hypothesized that ICA model order selection influences characteristics of RSNs as well as their functional connectivity. In addition, it was suggested that high ICA model order could be a useful tool to provide more detailed functional connectivity results. RSNs’ characteristics, i.e. spatial features, volume and repeatability of RSNs, were evaluated, and also differences in functional connectivity were investigated across different ICA model orders. ICA model order estimation had a significant impact on the spatial characteristics of the RSNs as well as their parcellation into sub-networks. Notably, at low model orders neuroanatomically and functionally different units tend to aggregate into large singular RSN components, while at higher model orders these units become separate RSN components. Disease-related differences in functional connectivity also seem to alter as a function of ICA model order. The volume of between-group differences reached maximum at high model orders. These findings demonstrate that fine-grained RSNs can provide detailed, disease-specific functional connectivity alterations. Finally, in order to overcome the multiple comparisons problem encountered at high ICA model orders, a new framework for group-ICA analysis was introduced. The framework involved concatenation of IC maps prior to permutation tests, which enables statistical inferences from all selected RSNs. In SAD patients, this new correction enabled the detection of significantly increased functional connectivity in eleven RSNs. / Tiivistelmä Toiminnallisten aivoalueiden välinen viestintä on todennäköisesti avainasemassa kognitiivisissa prosesseissa, jotka edellyttävät jatkuvaa tiedon integraatiota aivojen eri alueiden välillä. Tämä tekee ihmisaivojen toiminnallisen kytkennällisyyden tutkimuksesta erittäin tärkeätä. Kytkennälllisyyden tutkiminen antaa myös uutta tietoa ihmisaivojen osa-alueiden välisestä hierarkiasta. Aivojen hermoverkot voidaan luotettavasti ja toistettavasti havaita lepotilan toiminnasta yksilö- ja ryhmätasolla käyttämällä itsenäisten komponenttien analyysia (engl. Independent component analysis, ICA). Yhä useammat ICA-tutkimukset ovat raportoineet poikkeuksellisia toiminnallisen konnektiviteetin muutoksia kliinisissä populaatioissa. Tässä tutkimuksessa hypotetisoitiin, että ICA:lla laskettaujen komponenttien lukumäärä (l. asteluku) vaikuttaa tuloksena saatujen hermoverkkojen ominaisuuksiin kuten tilavuuteen ja kytkennällisyyteen. Lisäksi oletettiin, että korkea ICA-asteluku voisi olla herkempit tuottamaan yksityiskohtaisia toiminnallisen jaottelun tuloksia. Aivojen lepotilan hermoverkkojen ominaisuudet, kuten anatominen jakautuminen, volyymi ja lepohermoverkkojen havainnoinnin toistettavuus evaluoitin. Myös toiminnallisen kytkennällisyyden erot tutkitaan eri ICA-asteluvuilla. Havaittiin että asteluvulla on huomattava vaikutus aivojen lepotilan hermoverkkojen tilaominaisuuksiin sekä niiden jakautumiseen alaverkoiksi. Pienillä asteluvuilla hermoverkojen neuroanatomisesti erilliset yksiköt pyrkivät keräytymään laajoiksi yksittäisiksi komponenteiksi, kun taas korkeammilla asteluvuilla ne havaitaan erillisinä. Sairauksien aiheuttamat muutokset toiminnallisessa kytkennällisyydessä näyttävät muuttuvan myös ICA asteluvun mukaan saavuttaen maksiminsa korkeilla asteluvuilla. Korkeilla asteluvuilla voidaan havaita yksityiskohtaisia, sairaudelle ominaisia toiminnallisen konnektiviteetin muutoksia. Korkeisiin ICA asteluvun liittyvän tilastollisen monivertailuongelman ratkaisemiseksi kehitimme uuden menetelmän, jossa permutaatiotestejä edeltävien itsenäisten IC-karttoja yhdistämällä voidaan tehdä luotettava tilastollinen arvio yhtä aikaa lukuisista hermoverkoista. Kaamosmasennuspotilailla esimerkiksi kehittämämme korjaus paljastaa merkittävästi lisääntynyttä toiminnallista kytkennällisyyttä yhdessätoista hermoverkossa.

Circadian Rhythms (CR) are driven by a biological clock called as suprachiasmaticnucleus (SCN), located in a brain region called the hypothalamus. These rhythms are very much necessary in maintaining the sleep and wake cycle at appropriate times in a day. As a starting step towards non-invasive investigation of CR, aim is to study changes in the physiological processes of two Regions of Interest (ROI), the hypothalamus and the visual cortex. This was studied using a functional Magnetic Resonance Imaging (fMRI) technique to investigate for any changes or differences in the Blood Oxygen Level Dependent (BOLD)signals extracted from the ROI during a visual stimulation. We acquired and processed fMRI data to extract BOLD signals from ROI and the extracted signals are again further used to study the correlation with the experimental ON-OFF design paradigm. The extracted BOLD signals varied a lot between the two specified brain regions within the same subject and between three types of fMRI data. These variations were found in terms of number of activated voxels and also Signal to Noise ratio(SNR) level present in the signals. The number of activated voxels and SNR werehigh in visual cortex whereas low number of activated voxels and low SNR were found in hypothalamus. The correlation between BOLD responses from primaryvisual cortex were shown as positive with the experimental stimulation whereas BOLD responses extracted from hypothalamus have shown a negative correlation in time with the experimental stimulation. As a start up of the project, these BOLD responses can provide references for a future use in research studies, especially to further study about change in phase of the BOLD signal extracted exactly from the SCN. These phase responses can then be used to study physiological processing in subjects affected by sleep disorders.