Myocardial remodeling and bioelectric changes in tachycardia-induced heart failure in dogs

In this study, electrical and structural remodeling of ventricles was examined in tachycardia-induced heart failure (HF). We studied two groups of weight-matched adult male mongrel dogs: a sham-operated control group (n=5) and a pacing group (n=5) that underwent ventricular pacing at 230 bpm for 3 weeks. Clinical symptoms of congestive HF were observed in both groups. Their hemodynamic parameters were determined and the severity of the HF was evaluated by M-mode echocardiography. Changes in heart morphology were observed by scanning electron and light microscopy. Ventricular action potential duration (APD), as well as the 50 and 90% APD were measured in both groups. All dogs exhibited clinical symptoms of congestive HF after rapid right ventricular pacing for 3 weeks. These data indicate that rapid, right ventricular pacing produces a useful experimental model of low-output HF in dogs, characterized by biventricular pump dysfunction, biventricular cardiac dilation, and non-ischemic impairment of left ventricular contractility. Electrical and structural myocardial remodeling play an essential role in congestive HF progression, and should thus be prevented.

Diastolic function is associated with quality of life and exercise capacity in stable heart failure patients with reduced ejection fraction

Exercise capacity and quality of life (QOL) are important outcome predictors in patients with systolic heart failure (HF), independent of left ventricular (LV) ejection fraction (LVEF). LV diastolic function has been shown to be a better predictor of aerobic exercise capacity in patients with systolic dysfunction and a New York Heart Association (NYHA) classification ≥II. We hypothesized that the currently used index of diastolic function E/e' is associated with exercise capacity and QOL, even in optimally treated HF patients with reduced LVEF. This prospective study included 44 consecutive patients aged 55±11 years (27 men and 17 women), with LVEF<0.50 and NYHA functional class I-III, receiving optimal pharmacological treatment and in a stable clinical condition, as shown by the absence of dyspnea exacerbation for at least 3 months. All patients had conventional transthoracic echocardiography and answered the Minnesota Living with HF Questionnaire, followed by the 6-min walk test (6MWT). In a multivariable model with 6MWT as the dependent variable, age and E/e' explained 27% of the walked distance in 6MWT (P=0.002; multivariate regression analysis). No association was found between walk distance and LVEF or mitral annulus systolic velocity. Only normalized left atrium volume, a sensitive index of diastolic function, was associated with decreased QOL. Despite the small number of patients included, this study offers evidence that diastolic function is associated with physical capacity and QOL and should be considered along with ejection fraction in patients with compensated systolic HF.

Changes in cardiac aldosterone and its synthase in rats with chronic heart failure: an intervention study of long-term treatment with recombinant human brain natriuretic peptide

The physiological mechanisms involved in isoproterenol (ISO)-induced chronic heart failure (CHF) are not fully understood. In this study, we investigated local changes in cardiac aldosterone and its synthase in rats with ISO-induced CHF, and evaluated the effects of treatment with recombinant human brain natriuretic peptide (rhBNP). Sprague-Dawley rats were divided into 4 different groups. Fifty rats received subcutaneous ISO injections to induce CHF and the control group (n=10) received equal volumes of saline. After establishing the rat model, 9 CHF rats received no further treatment, rats in the low-dose group (n=8) received 22.5 μg/kg rhBNP and those in the high-dose group (n=8) received 45 μg/kg rhBNP daily for 1 month. Cardiac function was assessed by echocardiographic and hemodynamic analysis. Collagen volume fraction (CVF) was determined. Plasma and myocardial aldosterone concentrations were determined using radioimmunoassay. Myocardial aldosterone synthase (CYP11B2) was detected by quantitative real-time PCR. Cardiac function was significantly lower in the CHF group than in the control group (P<0.01), whereas CVF, plasma and myocardial aldosterone, and CYP11B2 transcription were significantly higher than in the control group (P<0.05). Low and high doses of rhBNP significantly improved hemodynamics (P<0.01) and cardiac function (P<0.05) and reduced CVF, plasma and myocardial aldosterone, and CYP11B2 transcription (P<0.05). There were no significant differences between the rhBNP dose groups (P>0.05). Elevated cardiac aldosterone and upregulation of aldosterone synthase expression were detected in rats with ISO-induced CHF. Administration of rhBNP improved hemodynamics and ventricular remodeling and reduced myocardial fibrosis, possibly by downregulating CYP11B2 transcription and reducing myocardial aldosterone synthesis.

Intercostal and forearm muscle deoxygenation during respiratory fatigue in patients with heart failure: potential role of a respiratory muscle metaboreflex

The purpose of this study was to determine the effect of respiratory muscle fatigue on intercostal and forearm muscle perfusion and oxygenation in patients with heart failure. Five clinically stable heart failure patients with respiratory muscle weakness (age, 66±12 years; left ventricle ejection fraction, 34±3%) and nine matched healthy controls underwent a respiratory muscle fatigue protocol, breathing against a fixed resistance at 60% of their maximal inspiratory pressure for as long as they could sustain the predetermined inspiratory pressure. Intercostal and forearm muscle blood volume and oxygenation were continuously monitored by near-infrared spectroscopy with transducers placed on the seventh left intercostal space and the left forearm. Data were compared by two-way ANOVA and Bonferroni correction. Respiratory fatigue occurred at 5.1±1.3 min in heart failure patients and at 9.3±1.4 min in controls (P<0.05), but perceived effort, changes in heart rate, and in systolic blood pressure were similar between groups (P>0.05). Respiratory fatigue in heart failure reduced intercostal and forearm muscle blood volume (P<0.05) along with decreased tissue oxygenation both in intercostal (heart failure, -2.6±1.6%; controls, +1.6±0.5%; P<0.05) and in forearm muscles (heart failure, -4.5±0.5%; controls, +0.5±0.8%; P<0.05). These results suggest that respiratory fatigue in patients with heart failure causes an oxygen demand/delivery mismatch in respiratory muscles, probably leading to a reflex reduction in peripheral limb muscle perfusion, featuring a respiratory metaboreflex.

Late emergence of A594V and L595W mutations related to ganciclovir resistance in a patient with HCMV retinitis and long-term HIV progression

The emergence of ganciclovir (GCV) resistance during the treatment of human cytomegalovirus (HCMV) infection is a serious clinical challenge, and is associated with high morbidity and mortality. In this case report, we describe the emergence of two consecutive mutations (A594V and L595W) related to GCV resistance in a patient with HCMV retinitis and long-term HIV progression after approximately 240 days of GCV use. Following the diagnosis of retinitis, the introduction of GCV did not result in viral load reduction. The detected mutations appeared late in the treatment, and we propose that other factors (high initial HCMV load, previous GCV exposure, low CD4+ cell count), in addition to the presence of resistance mutations, may have contributed to the treatment failure of HCMV infection in this patient.

Biological significance of miR-126 expression in atrial fibrillation and heart failure

We investigated the biological significance of microRNA-126 (miR-126) expression in patients with atrial fibrillation (AF) and/or heart failure (HF) to examine the possible mechanism of miR-126-dependent AF and development of HF. A total of 103 patients were divided into three groups: AF group (18 men and 17 women, mean age: 65.62±12.72 years), HF group (17 men and 15 women, mean age: 63.95±19.71 years), and HF-AF group (20 men and 16 women, mean age: 66.56±14.37 years). Quantitative real-time PCR was used to measure relative miR-126 expression as calculated by the 2−ΔΔCt method. miR-126 was frequently downregulated in the 3 patient groups compared with controls. This reduction was significantly lower in permanent and persistent AF patients than in those with paroxysmal AF (P<0.05, t-test). Moreover, miR-126 expression was markedly lower in the HF-AF group compared with the AF and HF groups. The 3 patient groups had higher N-terminal prohormone brain natriuretic peptide (NT-proBNP) levels, lower left ventricular ejection fraction (LVEF), larger left atrial diameter, and higher cardiothoracic ratio compared with controls. There were significant differences in NT-proBNP levels and LVEF among the AF, HF, and HF-AF groups. Pearson correlation analysis showed that relative miR-126 expression was positively associated with LVEF, logarithm of NT-proBNP, left atrial diameter, cardiothoracic ratio, and age in HF-AF patients. Multiple linear regression analysis showed that miR-126 expression was positively correlated with LVEF, but negatively correlated with the logarithm of NT-pro BNP and the cardiothoracic ratio (all P<0.05). Serum miR-126 levels could serve as a potential candidate biomarker for evaluating the severity of AF and HF. However, to confirm these results, future studies with a larger and diverse patient population are necessary.

A Bayesian Approach for Forecasting Heat Load in a District Heating System

The growing population in cities increases the energy demand and affects the environment by increasing carbon emissions. Information and communications technology solutions which enable energy optimization are needed to address this growing energy demand in cities and to reduce carbon emissions. District heating systems optimize the energy production by reusing waste energy with combined heat and power plants. Forecasting the heat load demand in residential buildings assists in optimizing energy production and consumption in a district heating system. However, the presence of a large number of factors such as weather forecast, district heating operational parameters and user behavioural parameters, make heat load forecasting a challenging task. This thesis proposes a probabilistic machine learning model using a Naive Bayes classifier, to forecast the hourly heat load demand for three residential buildings in the city of Skellefteå, Sweden over a period of winter and spring seasons. The district heating data collected from the sensors equipped at the residential buildings in Skellefteå, is utilized to build the Bayesian network to forecast the heat load demand for horizons of 1, 2, 3, 6 and 24 hours. The proposed model is validated by using four cases to study the influence of various parameters on the heat load forecast by carrying out trace driven analysis in Weka and GeNIe. Results show that current heat load consumption and outdoor temperature forecast are the two parameters with most influence on the heat load forecast. The proposed model achieves average accuracies of 81.23 % and 76.74 % for a forecast horizon of 1 hour in the three buildings for winter and spring seasons respectively. The model also achieves an average accuracy of 77.97 % for three buildings across both seasons for the forecast horizon of 1 hour by utilizing only 10 % of the training data. The results indicate that even a simple model like Naive Bayes classifier can forecast the heat load demand by utilizing less training data.

Load balancing in P2P smartphone based distributed IoT systems

With the new age of Internet of Things (IoT), object of everyday such as mobile smart devices start to be equipped with cheap sensors and low energy wireless communication capability. Nowadays mobile smart devices (phones, tablets) have become an ubiquitous device with everyone having access to at least one device. There is an opportunity to build innovative applications and services by exploiting these devices’ untapped rechargeable energy, sensing and processing capabilities. In this thesis, we propose, develop, implement and evaluate LoadIoT a peer-to-peer load balancing scheme that can distribute tasks among plethora of mobile smart devices in the IoT world. We develop and demonstrate an android-based proof of concept load-balancing application. We also present a model of the system which is used to validate the efficiency of the load balancing approach under varying application scenarios. Load balancing concepts can be apply to IoT scenario linked to smart devices. It is able to reduce the traffic send to the Cloud and the energy consumption of the devices. The data acquired from the experimental outcomes enable us to determine the feasibility and cost-effectiveness of a load balanced P2P smart phone-based applications.

Failure Mode and Effect Analysis (FMEA) for confectionery manufacturing in developing countries: Turkish delight production as a case study

The Failure Mode and Effect Analysis (FMEA) was applied for risk assessment of confectionary manufacturing, in whichthe traditional methods and equipment were intensively used in the production. Potential failure modes and effects as well as their possible causes were identified in the process flow. Processing stages that involve intensive handling of food by workers had the highest risk priority numbers (RPN = 216 and 189), followed by chemical contamination risks in different stages of the process. The application of corrective actions substantially reduced the RPN (risk priority number) values. Therefore, the implementation of FMEA (The Failure Mode and Effect Analysis) model in confectionary manufacturing improved the safety and quality of the final products.

Hävittäjäohjaajan kognitiivisen kuormituksen tason mittaaminen NASA-Task Load Index ja Modified Cooper-Harper -mittareilla F/A-18 virtuaalisimulaattorissa

F/A-18-monitoimihävittäjän ohjaajan tehtävän kognitiiviset vaatimukset ovat korkeat. Kognitiivisen kuormituksen taso vaikuttaa hävittäjäohjaajan suoritustasoon ja subjektiivisiin tun-temuksiin. Yerkesin ja Dodsonin periaatteen mukaisesti erittäin matala tai erittäin korkea kuormituksen taso laskee suoritustasoa. Optimaalinen kuormituksen taso ja suoritustaso saa-vutetaan jossain ääripäiden välillä. Hävittäjäohjaajan kognitiivisen kuormituksen tasoon vaikuttaa lentotehtävän suorittamiseen vaadittava henkinen ponnistelu. Vaadittavan ponnistelun taso riippuu tehtävien vaatimustasosta ja määrästä, tehtäviin käytettävissä olevasta ajasta sekä yksilöllisistä ominaisuuksista. Tutkimuksessa mitattiin kognitiivisen kuormituksen tasoa subjektiivisen arvioinnin menetelmällä NASA-TLX (National Aeronautics and Space Administration - Task Load Index) ja MCH (Modified Cooper-Harper) -mittareilla. Tutkimuksessa selvitettiin mittareiden havaintoarvojen muutosta, sensitiivisyyttä ja yhdenmukaisuutta kognitiivisen kuormituksen tason muuttuessa. Tutkimuksen mittauksiin osallistui 35 Suomen ilmavoimien aktiivisessa palveluksessa olevaa F/A-18-monitoimihävittäjäohjaajaa. Koehenkilöiden lentotuntien keskiarvo F/A-18-monitoimihävittäjällä oli 598 tuntia ja keskihajonta 445 tuntia. Koehenkilöiden tehtävänä oli lentää F/A-18-virtuaalisimulaattorilla 11 ILS (Instrument Landing System) -mittarilähestymistä eri aloitusetäisyyksiltä kiitotien kynnyksestä. Kognitiivisesti kuormitta-van mittarilähestymistehtävän aikana kuormituksen tasoa nostettiin lisätehtävillä ja vähentä-mällä tehtäviin käytettävissä olevaa aikaa. Koehenkilöitä pyydettiin ponnistelemaan mahdollisimman paljon tehtävien suorittamisen aikana hyvän suoritustason ylläpitämiseksi. Tulosten perusteella mittareiden havaintoarvot muuttuivat kognitiivisen kuormituksen tason muuttuessa. Käytettävissä olevan ajan vaikutus kognitiivisen kuormituksen tasoon oli tilastollisesti erittäin merkitsevä. Mittarit olivat sensitiivisiä kognitiivisen kuormituksen tason muutokselle ja antoivat yhdenmukaisia havaintoarvoja.

Glycemic index and glycemic load of tropical fruits and the potential risk for chronic diseases

The objective was to determine the glycemic index and glycemic load of tropical fruits and the potential risk for chronic diseases. Nine fruits were investigated: coconut water (for the purpose of this study, coconut water was classified as a “fruit”), guava, tamarind, passion fruit, custard apple, hog plum, cashew, sapodilla, and soursop. The GI and GL were determined according to the Food and Agriculture Organization protocol. The GL was calculated taking into consideration intake recommendation guidelines; 77.8% of the fruits had low GI although significant oscillations were observed in some graphs, which may indicate potential risks of disease. Coconut water and custard apple had a moderate GI, and all fruits had low GL. The fruits evaluated are healthy and can be consumed following the daily recommended amount. However, caution is recommended with fruits causing early glycemic peak and the fruits with moderated GI (coconut water and custard apple).

Effect of ultrasound treatment on quality and microbial load of carrot juice

Effect of ultrasound treatment on carrot juice was investigated through measuring pH, electrical conductivity, viscosity, visual color, total soluble solids, total sugars, total carotenoids, ascorbic acid contents and microbial load. No significant effect (p>0.05) of ultrasound treatment on pH of carrot juice was observed. Electrical conductivity, viscosity and color values gradually increased (p<0.05) with treatment time increase. Total soluble solids, total sugars, total carotenoids and ascorbic acid contents of carrot juice were significantly improved (p<0.05) due to ultrasound treatment. Moreover, significant decrease (p<0.05) in microbial load of sonicated carrot juice was observed. Results from present study suggested that ultrasound treatment could improve quality and safety of carrot juice.

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.