The health effects of sea buckthorn berries and oil

Sea buckthorn (Hippophaë) berries are ingredients of the Chinese traditional medicine. In addition to China, they are nowadays cultivated for food in several European countries, Russia, Canada, the USA, and Japan. Sea buckthorn berries are a rich source of flavonoids, mainly flavonol glycosides and proanthocyanidins. Depending on the genetic background, growth conditions, and ripeness of the berries, vitamin C concentrations up to over 1 g/100 ml juice, have been reported. Sea buckthorn berries contain inositols and methyl inositols, components of messenger molecules in humans. Sea buckthorn seed oil is rich in essential aplha-linolenic and linoleic acids, whereas the most abundant fatty acids in the berry oil are palmitoleic, palmitic and oleic acids. Other potentially beneficial lipophilic compounds of sea buckthorn seeds and berries include carotenoids, phytosterols, tocopherols and tocotrienols. The effects of sea buckthorn fractions on inflammation, platelet aggregation, oxidation injuries, the liver, skin and mucosa, among others, have been reported. The aim of the thesis work was to investigate the health effects of sea buckthorn berries and oil in humans. The physiological effects of sea buckthorn berries, berry components, and oil have mostly been studied in vitro and in animal models, leaving a demand for more clinical trials. In the first randomized, placebo-controlled trial of this thesis healthy adults consumed 28 g/day of sea buckthorn berries for three months. The main objective was to investigate the effects on the common cold. In addition, effects on other infections, inflammation and circulating lipid markers associated with cardiovascular disease risk were studied. In the second randomized, placebocontrolled trial participants reporting dry eye symptoms consumed 2 g/day of sea buckthorn oil from the seeds and berries for three months. The effects on symptoms and clinical signs of dry eye were monitored. In addition, the effects on circulating markers of inflammation and liver functions were analyzed. Sea buckthorn berries did not affect the common cold or other infections in healthy adults. However, a decrease in serum C-reactive protein was detected, indicating effects on inflammation. Fasting concentrations of serum flavonols, typical to sea buckthorn berry, increased without affecting the circulating total, HDL, LDL cholesterol, or triacylglycerol concentrations. Tear film hyperosmolarity and activation of inflammation at the ocular surface are among the core mechanisms of dry eye. Combined sea buckthorn berry and seed oil attenuated the rise in tear film osmolarity taking place during the cold season. It also positively affected some of the dry eye symptoms. Based on the tear film fatty acid analysis, the effects were not mediated through direct incorporation of sea buckthorn oil fatty acids to tear film lipids. It is likely that the fatty acids, carotenoids, tocopherols and tocotrienols of sea buckthorn oil affected the inflammation of the ocular surface, lacrimal and/or meibomian glands. The effects on the differentiation of meibomian gland cells are also possible. Sea buckthorn oil did not affect the serum concentrations of inflammation markers or liver enzymes investigated. In conclusion, this thesis work suggests positive effects of sea buckthorn berries and oil on inflammation and dry eye, respectively, in humans.

Biomolecular screening for inhibitors of butyrylcholinesterase : identification and characterization using in vitro and in silico tools

Drug discovery is a continuous process where researchers are constantly trying to find new and better drugs for the treatment of various conditions. Alzheimer’s disease, a neurodegenerative disease mostly affecting the elderly, has a complex etiology with several possible drug targets. Some of these targets have been known for years while other new targets and theories have emerged more recently. Cholinesterase inhibitors are the major class of drugs currently used for the symptomatic treatment of Alzheimer’s disease. In the Alzheimer’s disease brain there is a deficit of acetylcholine and an impairment in signal transmission. Acetylcholinesterase has therefore been the main target as this is the main enzyme hydrolysing acetylcholine and ending neurotransmission. It is believed that by inhibiting acetylcholinesterase the cholinergic signalling can be enhanced and the cognitive symptoms that arise in Alzheimer’s disease can be improved. Butyrylcholinesterase, the second enzyme of the cholinesterase family, has more recently attracted interest among researchers. Its function is still not fully known, but it is believed to play a role in several diseases, one of them being Alzheimer’s disease. In this contribution the aim has primarily been to identify butyrylcholinesterase inhibitors to be used as drug molecules or molecular probes in the future. Both synthetic and natural compounds in diverse and targeted screening libraries have been used for this purpose. The active compounds have been further characterized regarding their potencies, cytotoxicity, and furthermore, in two of the publications, the inhibitors ability to also inhibit Aβ aggregation in an attempt to discover bifunctional compounds. Further, in silico methods were used to evaluate the binding position of the active compounds with the enzyme targets. Mostly to differentiate between the selectivity towards acetylcholinesterase and butyrylcholinesterase, but also to assess the structural features required for enzyme inhibition. We also evaluated the compounds, active and non-active, in chemical space using the web-based tool ChemGPS-NP to try and determine the relevant chemical space occupied by cholinesterase inhibitors. In this study, we have succeeded in finding potent butyrylcholinesterase inhibitors with a diverse set of structures, nine chemical classes in total. In addition, some of the compounds are bifunctional as they also inhibit Aβ aggregation. The data gathered from all publications regarding the chemical space occupied by butyrylcholinesterase inhibitors we believe will give an insight into the chemically active space occupied by this type of inhibitors and will hopefully facilitate future screening and result in an even deeper knowledge of butyrylcholinesterase inhibitors.

PHOTOCATALYTIC OXIDATION OF AQUEOUS SOLUTIONS OF JET FUEL AND ICING INHIBITORS

The present paper is devoted to the results of experimental research undertaken into photocatalytical oxidation (PCO) of aqueous solutions of de-icing agents and aqueous extract of jet fuel. The report consists of introduction, literature review, description of materials and methods, discussion of results and conclusions. TiO2 was selected as a photocatalyst for the experiments with synthetic solutions of ethylene glycol, 2-ethoxyethanol and aqueous extract of jet fuel. To explain the PCO mechanisms affecting certain behaviour of de-icing agent under distinctive conditions, the following factors were studied: the impact of initial concentration of pollutant, the role of pH, the presence of tert-butanol as OH·-radicals scavenger and mineral admixtures. PCO under solar radiation performed in two ways: catalysed by irradiated TiO2 slurry or by TiO2 attached to buoyant hollow glass micro-spheres. Special attention was paid to the energy-saving PCO with reduced intensity mixing of the slurry. The effect of PCO was assessed by determination of residual chemical oxygen demand of solution (COD) and by measuring of concentration of glycols. The PCO process efficiency was assumed to be dependent on the TiO2 suspension fractional composition. Thus, the following effects of solutions’ media were viewed: presence of organic admixtures, pH influence, mixing mode during the PCO. The effects of mineral admixtures - Ca2+, Fe3+/2+, Mn2+, SO42- - that are often present in natural and wastewater systems or produced during the degradation of organic pollutants and which can affect the rate of PCO of de-icing agents, were also investigated.

Effects of Cytochrome P450 Enzyme Inhibitors on the Pharmacokinetics of Nonsteroidal Anti-inflammatory Drugs and Venlafaxine

Cytochrome P450 (CYP) enzymes play a pivotal role in the metabolism of many drugs. Inhibition of CYP enzymes usually increases the plasma concentrations of their substrate drugs and can thus alter the safety and efficacy of these drugs. The metabolism of many widely used nonsteroidal antiinflammatory drugs (NSAIDs) as well as the metabolism of the antidepressant venlafaxine is nown to be catalyzed by CYP enzymes. In the present studies, the effect of CYP inhibition on the armacokinetics and pharmacodynamics of NSAIDs and venlafaxine was studied in clinical trials with healthy volunteers and with a crossover design, by using different antifungal agents as CYP inhibitors. The results of these studies demonstrate that the inhibition of CYP enzymes leads to increased concentrations of NSAIDs. In most cases, the exposure to ibuprofen, diclofenac, etoricoxib, and meloxicam was increased 1.5to 2 fold when they were used concomitantly with antifungal agents. CYP2D6 inhibitor, terbinafine, substantially increased the concentration of parent venlafaxine, whereas the concentration of active moiety of venlafaxine (parent drug plus active metabolite) was only slightly increased. Voriconazole, an inhibitor of the minor metabolic pathway of venlafaxine, produced only minor changes in the pharmacokinetics of venlafaxine. These studies show that an evident increase in the concentrations of NSAIDs may be expected, if they are used concomitantly with CYP inhibitors. However, as NSAIDs are generally well tolerated, use of single doses of NSAIDs concomitantly with CYP inhibitors is not likely to adversely affect patient safety, whereas clinical relevance of longterm concomitant use of NSAIDs with CYP inhibitors needs further investigation. CYP2D6 inhibitors considerably affect the pharmacokinetics of venlafaxine, but the clinical significance of this interaction remains unclear.

Role of human hydroxysteroid (17beta) dehydrogenase type 1 (HSD17B1) in steroid-dependent diseases in females –novel indications for HSD17B1 inhibitors. Phenotypic analysis of transgenic mice overexpressing human HSD17B1.

Hormone-dependent diseases, e.g. cancers, rank high in mortality in the modern world, and thus, there is an urgent need for new drugs to treat these diseases. Although the diseases are clearly hormone-dependent, changes in circulating hormone concentrations do not explain all the pathological processes observed in the diseased tissues. A more inclusive explanation is provided by intracrinology – a regulation of hormone concentrations at the target tissue level. This is mediated by the expression of a pattern of steroid-activating and -inactivating enzymes in steroid target tissues, thus enabling a concentration gradient between the blood circulation and the tissue. Hydroxysteroid (17beta) dehydrogenases (HSD17Bs) form a family of enzymes that catalyze the conversion between low active 17-ketosteroids and highly active 17beta-hydroxysteroids. HSD17B1 converts low active estrogen (E1) to highly active estradiol (E2) with high catalytic efficiency, and altered HSD17B1 expression has been associated with several hormone-dependent diseases, including breast cancer, endometriosis, endometrial hyperplasia and cancer, and ovarian epithelial cancer. Because of its putative role in E2 biosynthesis in ovaries and peripheral target tissues, HSD17B1 is considered to be a promising drug target for estrogen-dependent diseases. A few studies have indicated that the enzyme also has androgenic activity, but they have been ignored. In the present study, transgenic mice overexpressing human HSD17B1 (HSD17B1TG mice) were used to study the effects of the enzyme in vivo. Firstly, the substrate specificity of human HSD17B1 was determined in vivo. The results indicated that human HSD17B1 has significant androgenic activity in female mice in vivo, which resulted in increased fetal testosterone concentration and female disorder of sexual development appearing as masculinized phenotype (increased anogenital distance, lack of nipples, lack of vaginal opening, combination of vagina with urethra, enlarged Wolffian duct remnants in the mesovarium and enlarged female prostate). Fetal androgen exposure has been linked to polycystic ovary syndrome (PCOS) and metabolic syndrome during adulthood in experimental animals and humans, but the genes involved in PCOS are largely unknown. A putative mechanism to accumulate androgens during fetal life by HSD17B1 overexpression was shown in the present study. Furthermore, as a result of prenatal androgen exposure locally in the ovaries, HSD17B1TG females developed ovarian benign serous cystadenomas in adulthood. These benign lesions are precursors of low-grade ovarian serous tumors. Ovarian cancer ranks fifth in mortality of all female cancers in Finland, and most of the ovarian cancers arise from the surface epithelium. The formation of the lesions was prevented by prenatal antiandrogen treatment and by transplanting wild type (WT) ovaries prepubertally into HSD17B1TG females. The results obtained in our non-clinical TG mouse model, together with a literature analysis, suggest that HSD17B1 has a role in ovarian epithelial carcinogenesis, and especially in the development of serous tumors. The role of androgens in ovarian carcinogenesis is considered controversial, but the present study provides further evidence for the androgen hypothesis. Moreover, it directly links HSD17B1-induced prenatal androgen exposure to ovarian epithelial carcinogenesis in mice. As expected, significant estrogenic activity was also detected for human HSD17B1. HSD17B1TG mice had enhanced peripheral conversion of E1 to E2 in a variety of target tissues, including the uterus. Furthermore, this activity was significantly decreased by treatments with specific HSD17B1 inhibitors. As a result, several estrogen-dependent disorders were found in HSD17B1TG females. Here we report that HSD17B1TG mice invariably developed endometrial hyperplasia and failed to ovulate in adulthood. As in humans, endometrial hyperplasia in HSD17B1TG females was reversible upon ovulation induction, triggering a rise in circulating progesterone levels, and in response to exogenous progestins. Remarkably, treatment with a HSD17B1 inhibitor failed to restore ovulation, yet completely reversed the hyperplastic morphology of epithelial cells in the glandular compartment. We also demonstrate that HSD17B1 is expressed in normal human endometrium, hyperplasia, and cancer. Collectively, our non-clinical data and literature analysis suggest that HSD17B1 inhibition could be one of several possible approaches to decrease endometrial estrogen production in endometrial hyperplasia and cancer. HSD17B1 expression has been found in bones of humans and rats. The non-clinical data in the present study suggest that human HSD17B1 is likely to have an important role in the regulation of bone formation, strength and length during reproductive years in female mice. Bone density in HSD17B1TG females was highly increased in femurs, but in lesser amounts also in tibias. Especially the tibia growth plate, but not other regions of bone, was susceptible to respond to HSD17B1 inhibition by increasing bone length, whereas the inhibitors did not affect bone density. Therefore, HSD17B1 inhibitors could be safer than aromatase inhibitors in regard to bone in the treatment of breast cancer and endometriosis. Furthermore, diseases related to improper growth, are a promising new indication for HSD17B1 inhibitors.

The Role of Cytochrome P450 3A Inducers and Inhibitors in the Metabolism and the Effects of Oxycodone

Oxycodone is an opioid used in the treatment of moderate or severe pain. It is principally metabolized in the liver by cytochrome P450 3A (CYP3A) enzymes whereas approximately 10% is metabolized by CYP2D6. Little is known about the interactions between oxycodone and other drugs, herbals and nutritional substances. In this work the effects of CYP3A inducers rifampicin and St. John’s wort and CYP3A inhibitors voriconazole, grapefruit juice, ritonavir and lopinavir/ritonavir were investigated on the pharmacokinetics and pharmacodynamics of oxycodone. All studies were randomized, balanced, placebo-controlled crossover clinical studies in healthy volunteers. The plasma concentrations of oxycodone and its metabolites were determined for 48 hours and pharmacodynamic parameters were recorded for 12 hours in each study. Pharmacokinetic parameters were calculated by noncompartmental methods. Rifampicin decreased the plasma concentrations, analgesic effects, and oral bioavailability of oral oxycodone. St. John’s wort reduced the concentrations of oxycodone and diminished the self-reported drug effect. Voriconazole increased the exposure to oral oxycodone by 3.6-fold whereas grapefruit juice, which inhibits predominantly the intestinal CYP3A, elevated the mean concentrations of oxycodone by 1.7-fold. Ritonavir and lopinavir/ritonavir increased the mean AUC of oxycodone by 3.0- and 2.6-fold, respectively, and prolonged its elimination half-life. In spite of increased oxycodone plasma concentrations during concomitant administration of CYP3A inhibitors, the analgesic effects were not increased. These studies show that the induction or inhibition of CYP3A alters the pharmacokinetics and pharmacologic effects of oxycodone. The exposure to oxycodone decreased after induction and increased after inhibition of CYP3A. As a conclusion, the clinicians should avoid concomitant administration of CYP3A inducers or inhibitors and oral oxycodone. If this is not possible, they should be prepared to interactions leading to impaired analgesia after CYP3A inducers or increased adverse effects after CYP3A inhibitors and oral oxycodone.

Adsorptive removal of harmful organic compound from aqueous solutions

Adsorption is one of the most commonly used methods in water treatment processes. It is attractive due to it easy operation and the availability of a wide variety of commercial adsorbents. This doctoral thesis focuses on investigating and explaining the influence of external phase conditions (temperature, pH, ionic strength, acidity, presence of cosolutes) on adsorption phenomena. In order to cover a wide range of factors and phenomena, case studies were chosen from various fields where adsorption is applied. These include the adsorptive removal of surface active agents (used in cleaning chemicals, for example) from aqueous effluents, the removal of hormones (estradiol) from drinking water, and the adsorption of antibiotics onto silica. The latter can beused to predict the diffusion of antibiotics in the aquatic system if they are released into the environment. Also the adsorption of living cells on functionalized polymers to purify infected water streams was studied. In addition to these examples, the adsorptive separation of harmful compounds from internal water streams within a chemical process was investigated. The model system was removal of fermentation inhibitors from lignocelluloses hydrolyzates. The detoxification of the fermentation broth is an important step in the manufacture of bioethanol from wood, but has not been studied previously in connection with concentrated acid hydrolyzates. New knowledge on adsorption phenomena was generated for all of the applications investigated. In most cases, the results could be explained by combining classical theories for individual phenomena. As an example, it was demonstrated how liquid phase aggregation could explain abnormal-looking adsorption equilibrium data. In addition to the fundamental phenomena, also process performance was of interest. This aspect is often neglected in adsorption studies. It was demonstrated that adsorbents should not be selected for a target application based on their adsorption properties only, but regeneration of the spent adsorbent must be considered. It was found that using a suitable amount of organic co-solvent in the regeneration can significantly improve the productivity of the process.

The spindle assembly checkpoint as a drug target - Novel small-molecule inhibitors of Aurora kinases

Cell division (mitosis) is a fundamental process in the life cycle of a cell. Equal distribution of chromosomes between the daughter cells is essential for the viability and well-being of an organism: loss of fidelity of cell division is a contributing factor in human cancer and also gives rise to miscarriages and genetic birth defects. For maintaining the proper chromosome number, a cell must carefully monitor cell division in order to detect and correct mistakes before they are translated into chromosomal imbalance. For this purpose an evolutionarily conserved mechanism termed the spindle assembly checkpoint (SAC) has evolved. The SAC comprises a complex network of proteins that relay and amplify mitosis-regulating signals created by assemblages called kinetochores (KTs). Importantly, minor defects in SAC signaling can cause loss or gain of individual chromosomes (aneuploidy) which promotes tumorigenesis while complete failure of SAC results in cell death. The latter event has raised interest in discovery of low molecular weight (LMW) compounds targeting the SAC that could be developed into new anti-cancer therapeutics. In this study, we performed a cell-based, phenotypic high-throughput screen (HTS) to identify novel LMW compounds that inhibit SAC function and result in loss of cancer cell viability. Altogether, we screened 65 000 compounds and identified eight that forced the cells prematurely out of mitosis. The flavonoids fisetin and eupatorin, as well as the synthetic compounds termed SACi2 and SACi4, were characterized in more detail utilizing versatile cell-based and biochemical assays. To identify the molecular targets of these SAC-suppressing compounds, we investigated the conditions in which SAC activity became abrogated. Eupatorin, SACi2 and SACi4 preferentially abolished the tensionsensitive arm of the SAC, whereas fisetin lowered also the SAC activity evoked by lack of attachments between microtubules (MTs) and KTs. Consistent with the abrogation of SAC in response to low tension, our data indicate that all four compounds inhibited the activity of Aurora B kinase. This essential mitotic protein is required for correction of erratic MT-KT attachments, normal SAC signaling and execution of cytokinesis. Furthermore, eupatorin, SACi2 and SACi4 also inhibited Aurora A kinase that controls the centrosome maturation and separation and formation of the mitotic spindle apparatus. In line with the established profound mitotic roles of Aurora kinases, these small compounds perturbed SAC function, caused spindle abnormalities, such as multi- and monopolarity and fragmentation of centrosomes, and resulted in polyploidy due to defects in cytokinesis. Moreover, the compounds dramatically reduced viability of cancer cells. Taken together, using a cell-based HTS we were able to identify new LMW compounds targeting the SAC. We demonstrated for the first time a novel function for flavonoids as cellular inhibitors of Aurora kinases. Collectively, our data support the concept that loss of mitotic fidelity due to a non-functional SAC can reduce the viability of cancer cells, a phenomenon that may possess therapeutic value and fuel development of new anti-cancer drugs.

Effects of cytochrome P450 enzyme inhibitors and inducers on the metabolism of S-ketamine

The human body eliminates foreign compounds primarily by metabolizing them to hydrophilic forms to facilitate effective excretion through the kidneys. Cytochrome P450 (CYP) enzymes in the liver and intestine contribute to the metabolism of many drugs. Pharmacokinetic drugdrug interactions occur if the activity of CYPs are inhibited or induced by another drug. Prescribing multiple drugs to the improve effectiveness of therapy or to treat coexisting diseases is a common practice in clinical medicine. Polypharmacy predisposes patients to adverse effects because of the profound unpredictability in CYP enzymatic-mediated drug metabolism. S-ketamine is a phencyclidine derivative which functions as an antagonist of the N-methyl-Daspartate (NMDA) receptor in the central nervous system. It is a unique anaesthetic producing “dissociative anaesthesia” in high doses and analgesia in low doses. Studies with human liver microsomes suggest that ketamine is metabolized primarily via CYP3A4 and CYP2B6 enzymes. In this thesis, in healthy volunteers, randomized and controlled cross-over studies were conducted to investigate the effects of different CYP inducers and inhibitors on the pharmacokinetics and pharmacodynamics of oral and intravenous S-ketamine. The plasma concentrations of ketamine and its metabolite, norketamine, were determined at different timepoints over a 24 hour period. Other pharmacodynamic variables were examined for 12 hours. Results of these studies showed that the inhibition of the CYP3A4 pathway by clarithromycin or grapefruit juice increased the exposure to oral S-ketamine by 2.6- and 3.0-fold. Unexpectedly, CYP3A4 inhibition by itraconazole caused no significant alterations in the plasma concentrations of oral S-ketamine. CYP3A4 induction by St. John´s wort or rifampicin decreased profoundly the concentrations of oral S-ketamine. However, after rifampicin, there were no significant differences in the plasma concentrations of S-ketamine when it was administered intravenously. This demonstrated that rifampicin inhibited the metabolism of Sketamine at the intestinal level. When CYP2B6 was inhibited by ticlopidine, there was a 2.4- fold increase in the exposure of S-ketamine. These studies demonstrated that low dose oral Sketamine is metabolized both via CYP3A4 and CYP2B6 pathways. The concomitant use of drugs that affect CYP3A4 or CYP2B6, during oral S-ketamine treatment, may cause clinically significant drug-drug interactions.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.