Studies on CYP2C8-mediated drug interactions

Useiden lääkkeiden yhtäaikainen käyttö on nykyään hyvin yleistä, mikä lisää lääkeaineiden haitallisten yhteisvaikutusten riskiä. Lääkeaineiden poistumisessa elimistöstä ovat tärkeässä osassa niitä hajottavat (metaboloivat) maksan sytokromi P450 (CYP) entsyymit. Vasta aivan viime vuosina on havaittu, että CYP2C8-entsyymillä voi olla tärkeä merkitys mm. lääkeaineyhteisvaikutuksissa. Eräät lääkeaineet voivat estää (inhiboida) CYP2C8-entsyymin kautta tapahtuvaa metaboliaa. Tässä työssä selvitettiin CYP2C8-entsyymiä estävien lääkkeiden vaikutusta sellaisten lääkeaineiden pitoisuuksiin, joiden aikaisemman tiedon perusteella arveltiin metaboloituvan CYP2C8-välitteisesti. Näiden lääkeaineiden metaboliaa tutkittiin myös koeputkiolosuhteissa (in vitro -menetelmillä). Lisäksi CYP2C8-entsyymiä estävän lipidilääke gemfibrotsiilin yhteisvaikutusmekanismia tutkittiin selvittämällä interaktion säilymistä koehenkilöillä gemfibrotsiilin annostelun lopettamisen jälkeen. Yhteisvaikutuksia tutkittiin terveillä vapaaehtoisilla koehenkilöillä käyttäen vaihtovuoroista koeasetelmaa. Koehenkilöille annettiin CYP2C8-entsyymiä estävää lääkitystä muutaman päivän ajan ja tämän jälkeen kerta-annos tutkimuslääkettä. Koehenkilöiltä otettiin useita verinäytteitä, joista määritettiin lääkepitoisuudet nestekromatografisilla tai massaspektrometrisillä menetelmillä. Gemfibrotsiili nosti ripulilääke loperamidin pitoisuudet keskimäärin kaksinkertaiseksi. Gemfibrotsiili lisäsi, mutta vain hieman, kipulääke ibuprofeenin pitoisuuksia, eikä sillä ollut mitään vaikutusta unilääke tsopiklonin pitoisuuksiin toisin kuin aiemman kirjallisuuden perusteella oli odotettavissa. Toinen CYP2C8-estäjä, mikrobilääke trimetopriimi, nosti diabeteslääke pioglitatsonin pitoisuuksia keskimäärin noin 40 %. Gemfibrotsiili nosti diabeteslääke repaglinidin pitoisuudet 7-kertaiseksi ja tämä yhteisvaikutus säilyi lähes yhtä voimakkaana vielä 12 tunnin päähän viimeisestä gemfibrotsiiliannoksesta. Tehdyt havainnot ovat käytännön lääkehoidon kannalta merkittäviä ja ne selvittävät CYP2C8-entsyymin merkitystä useiden lääkkeiden metaboliassa. Gemfibrotsiilin tai muiden CYP2C8-entsyymiä estävien lääkkeiden yhteiskäyttö loperamidin kanssa voi lisätä loperamidin tehoa tai haittavaikutuksia. Toisaalta CYP2C8-entsyymin osuus tsopiklonin ja ibuprofeenin metaboliassa näyttää olevan pieni. Trimetopriimi nosti kohtalaisesti pioglitatsonin pitoisuuksia, ja kyseisten lääkkeiden yhteiskäyttö voi lisätä pioglitatsonin annosriippuvaisia haittavaikutuksia. Gemfibrotsiili-repaglinidi-yhteisvaikutuksen päämekanismi in vivo näyttää olevan CYP2C8-entsyymin palautumaton esto. Tämän vuoksi gemfibrotsiilin estovaikutus ja yhteisvaikutusriski säilyvät pitkään gemfibrotsiilin annostelun lopettamisen jälkeen, mikä tulee ottaa huomioon käytettäessä sitä CYP2C8-välitteisesti metaboloituvien lääkkeiden kanssa.

Characterization of inhibition of platelet function by paracetamol and its interaction with diclofenac and parecoxib

Aim: To characterize the inhibition of platelet function by paracetamol in vivo and in vitro, and to evaluate the possible interaction of paracetamol and diclofenac or valdecoxib in vivo. To assess the analgesic effect of the drugs in an experimental pain model. Methods: Healthy volunteers received increasing doses of intravenous paracetamol (15, 22.5 and 30 mg/kg), or the combination of paracetamol 1 g and diclofenac 1.1 mg/kg or valdecoxib 40 mg (as the pro-drug parecoxib). Inhibition of platelet function was assessed with photometric aggregometry, the platelet function analyzer (PFA-100), and release of thromboxane B2. Analgesia was assessed with the cold pressor test. The inhibition coefficient of platelet aggregation by paracetamol was determined as well as the nature of interaction between paracetamol and diclofenac by an isobolographic analysis in vitro. Results: Paracetamol inhibited platelet aggregation and TxB2-release dose-dependently in volunteers and concentration-dependently in vitro. The inhibition coefficient was 15.2 mg/L (95% CI 11.8 - 18.6). Paracetamol augmented the platelet inhibition by diclofenac in vivo, and the isobole showed that this interaction is synergistic. Paracetamol showed no interaction with valdecoxib. PFA-100 appeared insensitive in detecting platelet dysfunction by paracetamol, and the cold-pressor test showed no analgesia. Conclusions: Paracetamol inhibits platelet function in vivo and shows synergism when combined with diclofenac. This effect may increase the risk of bleeding in surgical patients with an impaired haemostatic system. The combination of paracetamol and valdecoxib may be useful in patients with low risk for thromboembolism. The PFA-100 seems unsuitable for detection of platelet dysfunction and the cold-pressor test seems unsuitable for detection of analgesia by paracetamol.

Automatic wildfire detection and simulation using optical information from unmanned aerial systems

In many parts of the world, uncontrolled fires in sparsely populated areas are a major concern as they can quickly grow into large and destructive conflagrations in short time spans. Detecting these fires has traditionally been a job for trained humans on the ground, or in the air. In many cases, these manned solutions are simply not able to survey the amount of area necessary to maintain sufficient vigilance and coverage. This paper investigates the use of unmanned aerial systems (UAS) for automated wildfire detection. The proposed system uses low-cost, consumer-grade electronics and sensors combined with various airframes to create a system suitable for automatic detection of wildfires. The system employs automatic image processing techniques to analyze captured images and autonomously detect fire-related features such as fire lines, burnt regions, and flammable material. This image recognition algorithm is designed to cope with environmental occlusions such as shadows, smoke and obstructions. Once the fire is identified and classified, it is used to initialize a spatial/temporal fire simulation. This simulation is based on occupancy maps whose fidelity can be varied to include stochastic elements, various types of vegetation, weather conditions, and unique terrain. The simulations can be used to predict the effects of optimized firefighting methods to prevent the future propagation of the fires and greatly reduce time to detection of wildfires, thereby greatly minimizing the ensuing damage. This paper also documents experimental flight tests using a SenseFly Swinglet UAS conducted in Brisbane, Australia as well as modifications for custom UAS.

Computational systems approach for drug target discovery

Importance of the field: The shift in focus from ligand based design approaches to target based discovery over the last two to three decades has been a major milestone in drug discovery research. Currently, it is witnessing another major paradigm shift by leaning towards the holistic systems based approaches rather the reductionist single molecule based methods. The effect of this new trend is likely to be felt strongly in terms of new strategies for therapeutic intervention, new targets individually and in combinations, and design of specific and safer drugs. Computational modeling and simulation form important constituents of new-age biology because they are essential to comprehend the large-scale data generated by high-throughput experiments and to generate hypotheses, which are typically iterated with experimental validation. Areas covered in this review: This review focuses on the repertoire of systems-level computational approaches currently available for target identification. The review starts with a discussion on levels of abstraction of biological systems and describes different modeling methodologies that are available for this purpose. The review then focuses on how such modeling and simulations can be applied for drug target discovery. Finally, it discusses methods for studying other important issues such as understanding targetability, identifying target combinations and predicting drug resistance, and considering them during the target identification stage itself. What the reader will gain: The reader will get an account of the various approaches for target discovery and the need for systems approaches, followed by an overview of the different modeling and simulation approaches that have been developed. An idea of the promise and limitations of the various approaches and perspectives for future development will also be obtained. Take home message: Systems thinking has now come of age enabling a `bird's eye view' of the biological systems under study, at the same time allowing us to `zoom in', where necessary, for a detailed description of individual components. A number of different methods available for computational modeling and simulation of biological systems can be used effectively for drug target discovery.

Selective detection of single-enantiomer spectrum of chiral molecules aligned in the polypeptide liquid crystalline solvent: Transition selective one-dimensional H-1-H-1 COSY

One-dimensional (1D) proton NMR spectra of enantiomers are generally undecipherable in chiral orienting poly-gamma-benzyl-L-glutamate (PBLG)/CDCl3 solvent. This arises due to large number of couplings, in addition to superposition of spectra from both the enantiomers, severely hindering the H-1 detection. On the other hand in the present study the benefit is derived front the presence of several couplings among the entire network of interacting protons. Transition selective 1D H-1-H-1 correlation experiment (1D-COSY) which utilizes the Coupling assisted transfer of magnetization not only for unraveling the overlap but also for the selective detection of enantiopure spectrum is reported. The experiment is simple, easy to implement and provides accurate eanantiomeric excess in addition to the determination of the proton-proton couplings of an enantiomer within a short experimental time (few minutes). (C) 2009 Elsevier Inc. All rights reserved.

High-Rate Space-Time Coded Large-MIMO Systems: Low-Complexity Detection and Channel Estimation

In this paper, we present a low-complexity algorithm for detection in high-rate, non-orthogonal space-time block coded (STBC) large-multiple-input multiple-output (MIMO) systems that achieve high spectral efficiencies of the order of tens of bps/Hz. We also present a training-based iterative detection/channel estimation scheme for such large STBC MIMO systems. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed multistage likelihood ascent search (M-LAS) detector in conjunction with the proposed iterative detection/channel estimation scheme at low complexities. The fact that we could show such good results for large STBCs like 16 X 16 and 32 X 32 STBCs from Cyclic Division Algebras (CDA) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot based training for channel estimation and turbo coding) establishes the effectiveness of the proposed detector and channel estimator. We decode perfect codes of large dimensions using the proposed detector. With the feasibility of such a low-complexity detection/channel estimation scheme, large-MIMO systems with tens of antennas operating at several tens of bps/Hz spectral efficiencies can become practical, enabling interesting high data rate wireless applications.

Business busts and U.S. auditors' interest in fraud detection: Evidence from the 20th century

We find evidence that U.S. auditors increased their attention to fraud detection during or immediately after the economic contractions of the 20th century, based on a content analysis of the 12 volumes of the 20th-century auditing reference series Montgomery’s Auditing. Contractions, however, do not seem to have affected auditors’ attention to the formal goal of fraud detection. The study suggests that auditors’ aversion to the heightened risks of fraud during economic downturns leads them to focus more on fraud detection at those times regardless of the particular guidance in formal audit standards. This study is the first to find some evidence of a recession-influenced difference between fraud detection practices and formal fraud detection goals.

Detection of microorganisms using biosensors-a smarter way towards detection techniques.

Along with useful microorganisms, there are some that cause potential damage to the animals and plants. Detection and identification of these harmful organisms in a cost and time effective way is a challenge for the researchers. The future of detection methods for microorganisms shall be guided by biosensor, which has already contributed enormously in sensing and detection technology. Here, we aim to review the use of various biosensors, developed by integrating the biological and physicochemical/mechanical properties (of tranducers), which can have enormous implication in healthcare, food, agriculture and biodefence. We have also highlighted the ways to improve the functioning of the biosensor.

Using multi-label classification for acoustic pattern detection and assisting bird species surveys

Acoustics is a rich source of environmental information that can reflect the ecological dynamics. To deal with the escalating acoustic data, a variety of automated classification techniques have been used for acoustic patterns or scene recognition, including urban soundscapes such as streets and restaurants; and natural soundscapes such as raining and thundering. It is common to classify acoustic patterns under the assumption that a single type of soundscapes present in an audio clip. This assumption is reasonable for some carefully selected audios. However, only few experiments have been focused on classifying simultaneous acoustic patterns in long-duration recordings. This paper proposes a binary relevance based multi-label classification approach to recognise simultaneous acoustic patterns in one-minute audio clips. By utilising acoustic indices as global features and multilayer perceptron as a base classifier, we achieve good classification performance on in-the-field data. Compared with single-label classification, multi-label classification approach provides more detailed information about the distributions of various acoustic patterns in long-duration recordings. These results will merit further biodiversity investigations, such as bird species surveys.

Infections in lung and heart transplant recipients : Studies on the impact of bronchoscopy in the diagnosis of respiratory infections and detection of viral infections in blood and bronchoalveolar lavage fluid

Infection is a major cause of mortality and morbidity after thoracic organ transplantation. The aim of the present study was to evaluate the infectious complications after lung and heart transplantation, with a special emphasis on the usefulness of bronchoscopy and the demonstration of cytomegalovirus (CMV), human herpes virus (HHV)-6, and HHV-7. We reviewed all the consecutive bronchoscopies performed on heart transplant recipients (HTRs) from May 1988 to December 2001 (n = 44) and lung transplant recipients (LTRs) from February 1994 to November 2002 (n = 472). To compare different assays in the detection of CMV, a total of 21 thoracic organ transplant recipients were prospectively monitored by CMV pp65-antigenemia, DNAemia (PCR), and mRNAemia (NASBA) tests. The antigenemia test was the reference assay for therapeutic intervention. In addition to CMV antigenemia, 22 LTRs were monitored for HHV-6 and HHV-7 antigenemia. The diagnostic yield of the clinically indicated bronchoscopies was 41 % in the HTRs and 61 % in the LTRs. The utility of the bronchoscopy was highest from one to six months after transplantation. In contrast, the findings from the surveillance bronchoscopies performed on LTRs led to a change in the previous treatment in only 6 % of the cases. Pneumocystis carinii and CMV were the most commonly detected pathogens. Furthermore, 15 (65 %) of the P. carinii infections in the LTRs were detected during chemoprophylaxis. None of the complications of the bronchoscopies were fatal. Antigenemia, DNAemia, and mRNAemia were present in 98 %, 72 %, and 43 % of the CMV infections, respectively. The optimal DNAemia cut-off levels (sensitivity/specificity) were 400 (75.9/92.7 %), 850 (91.3/91.3 %), and 1250 (100/91.5 %) copies/ml for the antigenemia of 2, 5, and 10 pp65-positive leukocytes/50 000 leukocytes, respectively. The sensitivities of the NASBA were 25.9, 43.5, and 56.3 % in detecting the same cut-off levels. CMV DNAemia was detected in 93 % and mRNAemia in 61 % of the CMV antigenemias requiring antiviral therapy. HHV-6, HHV-7, and CMV antigenemia was detected in 20 (91 %), 11 (50 %), and 12 (55 %) of the 22 LTRs (median 16, 31, and 165 days), respectively. HHV-6 appeared in 15 (79 %), HHV-7 in seven (37 %), and CMV in one (7 %) of these patients during ganciclovir or valganciclovir prophylaxis. One case of pneumonitis and another of encephalitis were associated with HHV-6. In conclusion, bronchoscopy is a safe and useful diagnostic tool in LTRs and HTRs with a suspected respiratory infection, but the role of surveillance bronchoscopy in LTRs remains controversial. The PCR assay acts comparably with the antigenemia test in guiding the pre-emptive therapy against CMV when threshold levels of over 5 pp65-antigen positive leukocytes are used. In contrast, the low sensitivity of NASBA limits its usefulness. HHV-6 and HHV-7 activation is common after lung transplantation despite ganciclovir or valganciclovir prophylaxis, but clinical manifestations are infrequently linked to them.