Disentangling the effects of insomnia and night work on cardiovascular diseases: a study in nursing professionals

Cardiovascular diseases (CVDs) are known to be associated with poor sleep quality in general populations, but they have not been consistently associated with specific work schedules. Studies of CVD generally do not simultaneously consider sleep and work schedules, but that approach could help to disentangle their effects. We investigated the association between insomnia and a self-reported physician diagnosis of CVD in day and night workers, considering all sleep episodes during nocturnal and diurnal sleep. A cross-sectional study was conducted in 1307 female nursing professionals from 3 public hospitals, using baseline data from the “Health and Work in Nursing - a Cohort Study.” Participants were divided into two groups: i) day workers with no previous experience in night shifts (n=281) and whose data on insomnia were related to nocturnal sleep and ii) those who worked exclusively at night (n=340) and had data on both nocturnal and diurnal sleep episodes, as they often sleep at daytime. Multiple logistic regression analysis was performed. Among day workers, insomnia complaints increased the odds of CVD 2.79-fold (95% CI=1.01-6.71) compared with workers who had no complaints. Among night workers, reports of insomnia during both nocturnal and diurnal sleep increased the odds of reported CVD 3.07-fold (95% CI=1.30-7.24). Workers with insomnia had similar probabilities of reporting CVD regardless of their work schedule, suggesting a relationship to insomnia and not to night work per se. The results also highlighted the importance of including evaluation of all sleep episodes (diurnal plus nocturnal sleep) for night workers.

The role of necroptosis in neurosurgical diseases

Programmed necrosis or necroptosis is an alternative form of cell death that is executed through a caspase-independent pathway. Necroptosis has been implicated in many pathological conditions. Genetic or pharmacological inhibition of necroptotic signaling has been shown to confer neuroprotection after traumatic and ischemic brain injury. Therefore, the necroptotic pathway represents a potential target for neurological diseases that are managed by neurosurgeons. In this review, we summarize recent advances in the understanding of necroptotic signaling pathways and explore the role of necroptotic cell death in craniocerebral trauma, brain tumors, and cerebrovascular diseases.

Accuracy of dose planning for prostate radiotherapy in the presence of metallic implants evaluated by electron spin resonance dosimetry

Radiotherapy is one of the main approaches to cure prostate cancer, and its success depends on the accuracy of dose planning. A complicating factor is the presence of a metallic prosthesis in the femur and pelvis, which is becoming more common in elderly populations. The goal of this work was to perform dose measurements to check the accuracy of radiotherapy treatment planning under these complicated conditions. To accomplish this, a scale phantom of an adult pelvic region was used with alanine dosimeters inserted in the prostate region. This phantom was irradiated according to the planned treatment under the following three conditions: with two metallic prostheses in the region of the femur head, with only one prosthesis, and without any prostheses. The combined relative standard uncertainty of dose measurement by electron spin resonance (ESR)/alanine was 5.05%, whereas the combined relative standard uncertainty of the applied dose was 3.35%, resulting in a combined relative standard uncertainty of the whole process of 6.06%. The ESR dosimetry indicated that there was no difference (P>0.05, ANOVA) in dosage between the planned dose and treatments. The results are in the range of the planned dose, within the combined relative uncertainty, demonstrating that the treatment-planning system compensates for the effects caused by the presence of femur and hip metal prostheses.

Association between NOx exposure and deaths caused by respiratory diseases in a medium-sized Brazilian city

Exposure to nitrogen oxides (NOx) emitted by burning fossil fuels has been associated with respiratory diseases. We aimed to estimate the effects of NOx exposure on mortality owing to respiratory diseases in residents of Taubaté, São Paulo, Brazil, of all ages and both sexes. This time-series ecological study from August 1, 2011 to July 31, 2012 used information on deaths caused by respiratory diseases obtained from the Health Department of Taubaté. Estimated daily levels of pollutants (NOx, particulate matter, ozone, carbon monoxide) were obtained from the Centro de Previsão de Tempo e Estudos Climáticos Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System. These environmental variables were used to adjust the multipollutant model for apparent temperature. To estimate association between hospitalizations owing to asthma and air pollutants, generalized additive Poisson regression models were developed, with lags as much as 5 days. There were 385 deaths with a daily mean (±SD) of 1.05±1.03 (range: 0-5). Exposure to NOx was significantly associated with mortality owing to respiratory diseases: relative risk (RR)=1.035 (95% confidence interval [CI]: 1.008-1.063) for lag 2, RR=1.064 (95%CI: 1.017-1.112) lag 3, RR=1.055 (95%CI: 1.025-1.085) lag 4, and RR=1.042 (95%CI: 1.010-1.076) lag 5. A 3 µg/m3 reduction in NOx concentration resulted in a decrease of 10-18 percentage points in risk of death caused by respiratory diseases. Even at NOx concentrations below the acceptable standard, there is association with deaths caused by respiratory diseases.

Scalable Feature Selection Applications for Genome-Wide Association Studies of Complex Diseases

Personalized medicine will revolutionize our capabilities to combat disease. Working toward this goal, a fundamental task is the deciphering of geneticvariants that are predictive of complex diseases. Modern studies, in the formof genome-wide association studies (GWAS) have afforded researchers with the opportunity to reveal new genotype-phenotype relationships through the extensive scanning of genetic variants. These studies typically contain over half a million genetic features for thousands of individuals. Examining this with methods other than univariate statistics is a challenging task requiring advanced algorithms that are scalable to the genome-wide level. In the future, next-generation sequencing studies (NGS) will contain an even larger number of common and rare variants. Machine learning-based feature selection algorithms have been shown to have the ability to effectively create predictive models for various genotype-phenotype relationships. This work explores the problem of selecting genetic variant subsets that are the most predictive of complex disease phenotypes through various feature selection methodologies, including filter, wrapper and embedded algorithms. The examined machine learning algorithms were demonstrated to not only be effective at predicting the disease phenotypes, but also doing so efficiently through the use of computational shortcuts. While much of the work was able to be run on high-end desktops, some work was further extended so that it could be implemented on parallel computers helping to assure that they will also scale to the NGS data sets. Further, these studies analyzed the relationships between various feature selection methods and demonstrated the need for careful testing when selecting an algorithm. It was shown that there is no universally optimal algorithm for variant selection in GWAS, but rather methodologies need to be selected based on the desired outcome, such as the number of features to be included in the prediction model. It was also demonstrated that without proper model validation, for example using nested cross-validation, the models can result in overly-optimistic prediction accuracies and decreased generalization ability. It is through the implementation and application of machine learning methods that one can extract predictive genotype–phenotype relationships and biological insights from genetic data sets.

Comparative antiproliferation of human prostate cancer cells by ethanolic extracts of two groups of Brazilian propolis

Two groups of propolis, group 12, which was collected in the southeastern Brazil and group 13, which was collected in the northeastern Brazil, were examined for antiproliferation of primary malignant tumor (RC-58T/h/SA#4)-derived human prostate cancer cells and human prostate epithelial cells. The strongest inhibition of RC-58T/h/SA#4 cells was observed in propolis group 13 extracts, whereas moderate growth inhibition was observed in human prostate epithelial cells in comparison with group 12. It can be said that the Brazilian propolis of group 13 contains important chemical ingredients.

Use of cereal bars with quinoa (Chenopodium quinoa W.) to reduce risk factors related to cardiovascular diseases

Quinoa is considered a pseudocereal with proteins of high biological value, carbohydrates of low glycemic index, phytosteroids, and omega-3 and 6 fatty acids that bring benefits to the human health. The purpose of this study was to investigate the effects of quinoa on the biochemical and anthropometric profile and blood pressure in humans, parameters for measuring risk of cardiovascular diseases. Twenty-two 18 to 45-year-old students were treated daily for 30 days with quinoa in the form of a cereal bar. Blood samples were collected before and after 30 days of treatment to determine glycemic and biochemical profile of the group. The results indicated that quinoa had beneficial effects on part of the population studied since the levels of total cholesterol, triglycerides, and LDL-c showed reduction. It can be concluded that the use of quinoa in diet can be considered beneficial in the prevention and treatment of risk factors related to cardiovascular diseases that are among the leading causes of death in today's globalized world. However, further studies are needed to prove the benefits observed.

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).

Genetics of inherited small vessel diseases – in search of a novel small vessel disease and modifiers of the clinical course of CADASIL

The genetic and environmental risk factors of vascular cognitive impairment are still largely unknown. This thesis aimed to assess the genetic background of two clinically similar familial small vessel diseases (SVD), CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy) and Swedish hMID (hereditary multi-infarct dementia of Swedish type). In the first study, selected genetic modifiers of CADASIL were studied in a homogenous Finnish CADASIL population of 134 patients, all carrying the p.Arg133Cys mutation in NOTCH3. Apolipoprotein E (APOE) genotypes, angiotensinogen (AGT) p.Met268Thr polymorphism and eight NOTCH3 polymorphisms were studied, but no associations between any particular genetic variant and first-ever stroke or migraine were seen. In the second study, smoking, statin medication and physical activity were suggested to be the most profound environmental differences among the monozygotic twins with CADASIL. Swedish hMID was for long misdiagnosed as CADASIL. In the third study, the CADASIL diagnosis in the Swedish hMID family was ruled out on the basis of genetic, radiological and pathological findings, and Swedish hMID was suggested to represent a novel SVD. In the fourth study, the gene defect of Swedish hMID was then sought using whole exome sequencing paired with a linkage analysis. The strongest candidate for the pathogenic mutation was a 3’UTR variant in the COL4A1 gene, but further studies are needed to confirm its functionality. This study provided new information about the genetic background of two inherited SVDs. Profound knowledge about the pathogenic mutations causing familial SVD is also important for correct diagnosis and treatment options.

Clinical and genetic markers in disease progression – a study among subjects with obstructive lung diseases

Asthma, COPD, and asthma and COPD overlap syndrome (ACOS) are chronic pulmonary diseases with an obstructive component. In COPD, the obstruction is irreversible and the disease is progressive. The aim of the study was to define and analyze factors that affected disease progression and patients’ well-being, prognosis and mortality in Chronic Airway Disease (CAD) cohort. The main focus was on COPD and ACOS patients. Retrospective data from medical records was combined with genetic and prospective follow-up data. Smoking is the biggest risk factor for COPD and even after the diagnosis of the disease, smoking plays an important role in disease development and patient’s prognosis. Sixty percent of the COPD patients had succeeded in smoking cessation. Patients who had managed to quit smoking had lower mortality rates and less psychiatric diseases and alcohol abuse although they were older and had more cardiovascular diseases than patients who continued smoking. Genetic polymorphism rs1051730 in the nicotinic acethylcholine receptor gene (CHRNA3/5) associated with heavy smoking, cancer prevalence and mortality in two Finnish independent cohorts consisting of COPD patients and male smokers. Challenges in smoking cessation and higher mortality rates may be partly due to individual patient’s genetic composition. Approximately 50% of COPD patients are physically inactive and the proportion was higher among current smokers. Physically active and inactive patients didn’t differ from each other in regard to age, gender or comorbidities. Bronchial obstruction explained inactivity only in severe disease. Subjective sensation of dyspnea, however, had very strong association to inactivity and was also associated to low health related quality of life (HRQoL). ACOS patients had a significantly lower HRQoL than either the patients with asthma or with COPD even though they were younger than COPD patients, had better lung functions and smaller tobacco exposure.

Identification and validation of novel prostate cancer biomarkers

Prostate cancer (PCa) has emerged as the most commonly diagnosed lethal cancer in European men. PCa is a heterogeneous cancer that in the majority of the cases is slow growing: consequently, these patients would not need any medical treatment. Currently, the measurement of prostate-specific antigen (PSA) from blood by immunoassay followed by digital rectal examination and a pathological examination of prostate tissue biopsies are the most widely used methods in the diagnosis of PCa. These methods suffer from a lack of sensitivity and specificity that may cause either missed cancers or overtreatment as a consequence of over-diagnosis. Therefore, more reliable biomarkers are needed for a better discrimination between indolent and potentially aggressive cancers. The aim of this thesis was the identification and validation of novel biomarkers for PCa. The mRNA expression level of 14 genes including AMACR, AR, PCA3, SPINK1, TMPRSS2-ERG, KLK3, ACSM1, CACNA1D, DLX1, LMNB1, PLA2G7, RHOU, SPON2, and TDRD1 was measured by a truly quantitative reverse transcription PCR in different prostate tissue samples from men with and without PCa. For the last eight genes the function of the genes in PCa progression was studied by a specific siRNA knockdown in PC-3 and VCaP cells. The results from radical prostatectomy and cystoprostatectomy samples showed statistically significant overexpression for all the target genes, except for KLK3 in men with PCa compared with men without PCa. Statistically significant difference was also observed in low versus high Gleason grade tumors (for PLA2G7), PSA relapse versus no relapse (for SPON2), and low versus high TNM stages (for CACNA1D and DLX1). Functional studies and siRNA silencing results revealed a cytotoxicity effect for the knock-down of DLX1, PLA2G7, and RHOU, and altered tumor cell invasion for PLA2G7, RHOU, ACSM1, and CACNA1D knock-down in 3D conditions. In addition, effects on tumor cell motility were observed after silencing PLA2G7 and RHOU in 2D monolayer cultures. Altogether, these findings indicate the possibility of utilizing these new markers as diagnostic and prognostic markers, and they may also represent therapeutic targets for PCa.