Zuverlässigkeit der Prognosen von hybriden Neuronalen Netzwerken und ihre Visualisierung mit Anwendungen in der Limnologie

Die Approximation nicht-linearer und multidimensionaler Regressionsfunktionen durch Radiale-Basisfunktionen-Netzwerke, deren verdeckte Neuronen von Selbstorganisierenden Karten (SOM) unüberwacht trainiert werden, liefert im Gegensatz zu vielen anderen Prognosesystemen für jede Vorhersage eine Abschätzung der zu erwartenden Zuverlässigkeit dieses hybriden Künstlichen Neuronalen Netzwerkes (KNN) in Abhängigkeit von der Eingabe sowie für ein- oder zweidimensionale SOM-Gitter grafische Veranschaulichungen der Daten und des Netzwerkverhaltens. In dem durch eine SOM partitionierten Eingaberaum lassen sich für jede Klasse die Anzahlen der in ihr enthaltenen Eingabedaten, Mittelwerte und Dispersionsmaße der eingeschränkten empirischen Verteilung der Ausgabegröße sowie mittlere Prognosefehler angeben. Nach der Hybridisierung mit Validity-Index-Netzen (VIN) können auf der Basis von Kreuzvalidierungen lokale Fehler sowie Vertrauens- und Vorhersageintervalle geschätzt werden. Neben dem minimalen Abstand zu den Klassenprototypen und dem maximalen Funktionswert lokaler radialer Basisfunktionen erlauben das Extrapolationsmaß des VINs und Likelihoods von Parzen-Dichteschätzern, Netzeingaben als bekannt oder neuartig zu klassifizieren. Aus dem anschaulichen, wenige Voraussetzungen und Daten erfordernden Ansatz resultieren prinzipielle Schwierigkeiten bei der Abbildung intrinsisch hochdimensionaler Eingaberäume auf zweidimensionale SOM-Gitter und eine mögliche suboptimale Prognosequalität aufgrund des unüberwachten Lernens sowie praktische Probleme bei der Optimierung der Bandbreiten radialer Basisfunktionen und der Anzahl von SOM-Zellen. Das entwickelte Softwarepaket zur Simulation des KNN-Hybrids und anderer Modelle erzeugt zahlreiche Grafiken, die Lern- und Testdaten, Residuen und Szenarien für partielle Netzausgabefunktionen gemeinsam mit den genannten lokalen Zuverlässigkeitsmaßen in Linien- und Streudiagrammen veranschaulichen und eine visuelle Inspektion der verdeckten Schicht als Graustufendarstellungen dieser Werte für die SOM-Klassen, deren Prototypen oder einzelne Netzeingaben sowie Sequenzen von Eingabemustern auf dem SOM-Gitter ermöglichen. Nach der Entfernung irrelevanter und redundanter Eingabegrößen lassen sich die verbleibenden Eingabemerkmale zur Verbesserung der Generalisierungsfähigkeit des KNNs durch eine weitere, vorgeschaltete Schicht von Neuronen durch ein Gradientenabstiegsverfahren automatisch reskalieren. Die Anwendbarkeit des Modells und der Software demonstrieren exemplarisch die Vorhersagen des täglichen Abflusses eines kleinen, hessischen Baches in Abhängigkeit von Niederschlags- und Temperaturwerten sowie die Prognosen der jährlichen Abundanz von dort in einer Emergenzfalle gefangenen Eintags-, Stein- und Köcherfliegenarten für veränderliche Umweltbedingungen auf der Basis eines Langzeitdatensatzes

The Hydrodynamics of Pool-Riffle Sequences with Changing Bedform Length

Previous research has demonstrated that pool-riffle bedforms play a critical role in channel stability and ecosystem health in many natural gravel-bed channels. Although the bedform length is known to scale with channel width, no experimental research has yet isolated the effect of bedform length on pool-riffle hydrodynamics. To improve the understanding of the hydrodynamics of these bedforms so that they can be better incorporated in restoration practices, flume experiments were conducted testing the flow at seven different bedform lengths. Velocity profiles are measured in a 17 m flume with movable PVC bedforms using ultrasonic velocity profilers (UVPs). Smooth two-dimensional (no sinuosity) bedforms are used in order to isolate the key dynamics in convective acceleration and deceleration. The angle of transition between pool and riffle heights was 7°, so that permanent flow separation did not occur. Parameters calculated from the velocity and turbulence profiles include the Coles’ wake parameter (a measure of the deviation from the log law), shear stress estimated from the velocity profile, shear stress estimated from the Reynolds shear stress, and vertical velocity. From the individual velocity time series, the integral length scale and the integral time scales are also calculated. Overall, the length of riffles and pools exert a fundamental control on the distribution of flow and turbulence within a channel. In the pool, energy is dissipated both through turbulence and as the flow is redistributed to uniform flow conditions. In the riffle, kinetic energy increases as the flow velocity increases, and as the length increases, the flow moves towards a new uniform flow condition. The results start to explain the reasons behind the persistent scaling relation between width and bedform length. It can be concluded that uniform flow conditions exist at the end of the pool when the bedform length ratio is greater than approximately 1:5.0 when the riffle length is held constant, and that uniform flow conditions are no longer observed at the end of the pool when the bedform length ratio exceeds 1:7.0 when the pool length is held constant. Future research should concentrate on extending the results to include three-dimensional pool-riffle configurations, repeating bedform configurations, internal scaling parameters, and sediment transport. Ultimately, as the hydrodynamics of pool-riffle sequences are better understood, better bedform designs can be implemented in restoration projects

Selective Photokilling of Human Pancreatic Cancer Cells Using Cetuximab-Targeted Mesoporous Silica Nanoparticles for Delivery of Zinc Phthalocyanine

Background: Photodynamic therapy (PDT) is a non-invasive and innovative cancer therapy based on the photodynamic effect. In this study, we sought to determine the singlet oxygen production, intracellular uptake, and in vitro photodynamic therapy potential of Cetixumab-targeted, zinc(II) 2,3,9,10,16,17,23,24-octa(tert-butylphenoxy))phthalocyaninato(2-)-N29,N30,N31,N32 (ZnPcOBP)- loaded mesoporous silica nanoparticles against pancreatic cancer cells. Results: The quantum yield (Φ∆) value of ZnPcOBP was found to be 0.60 in toluene. In vitro cellular studies were performed to determine the dark- and phototoxicity of samples with various concentrations of ZnPcOBP by using pancreatic cells (AsPC-1, PANC-1 and MIA PaCa-2) and 20, 30, and 40 J/cm2 light fluences. No dark toxicity was observed for any sample in any cell line. ZnPcOBP alone showed a modest photodynamic activity. However, when incorporated in silica nanoparticles, it showed a relatively high phototoxic effect, which was further enhanced by Cetuximab, a monoclonal antibody that targets the Epidermal Growth Factor Receptor (EGFR). The cell-line dependent photokilling observed correlates well with EGFR expression levels in these cells. Conclusions: Imidazole-capped Cetuximab-targeted mesoporous silica nanoparticles are excellent vehicles for the selective delivery of ZnPcOBP to pancreatic cancer cells expressing the EGFR receptor. The novel nanosystem appears to be a suitable agent for photodynamic therapy of pancreatic tumor

Nonviral-Mediated Hepatic Expression of IGF-I Increases Treg Levels and Suppresses Autoimmune Diabetes in Mice

Altres ajuts: This work was supported by grants from Ministerio de Ciencia e Innovación (SAF2005-01262 and SAF2008-00962) and from the European Community (FP6 CLINIGENE, LSHB-CT-2006-018933). X.M.A., J.A., and A.R. were recipients of a predoctoral fellowship from Ministerio de Educación, Cultura y Deporte, and D.C. received a predoctoral fellowship from Instituto de Salud Carlos III, Spain. C.J.M.In type 1 diabetes, loss of tolerance to β-cell antigens results in T-cell-dependent autoimmune destruction of β cells. The abrogation of autoreactive T-cell responses is a prerequisite to achieve long-lasting correction of the disease. The liver has unique immunomodulatory properties and hepatic gene transfer results in tolerance induction and suppression of autoimmune diseases, in part by regulatory T-cell (Treg) activation. Hence, the liver could be manipulated to treat or prevent diabetes onset through expression of key genes. IGF-I may be an immunomodulatory candidate because it prevents autoimmune diabetes when expressed in β cells or subcutaneously injected. Here, we demonstrate that transient, plasmid-derived IGF-I expression in mouse liver suppressed autoimmune diabetes progression. Suppression was associated with decreased islet inflammation and β-cell apoptosis, increased β-cell replication, and normalized β-cell mass. Permanent protection depended on exogenous IGF-I expression in liver nonparenchymal cells and was associated with increased percentage of intrapancreatic Tregs. Importantly, Treg depletion completely abolished IGF-I-mediated protection confirming the therapeutic potential of these cells in autoimmune diabetes. This study demonstrates that a nonviral gene therapy combining the immunological properties of the liver and IGF-I could be beneficial in the treatment of the disease

Nonclassical Phenyl Bioisosteres as Effective Replacements in a Series of Novel Open-Source Antimalarials

The replacement of one chemical motif with another that is broadly similar is a common method in medicinal chemistry to modulate the physical and biological properties of a molecule (i.e., bioisosterism). In recent years, bioisosteres such as cubane and bicyclo[1.1.1]pentane (BCP) have been used as highly effective phenyl mimics. Herein, we show the successful incorporation of a range of phenyl bioisosteres during the open-source optimization of an antimalarial series. Cubane () and -carborane () analogues exhibited improved potency against compared to the parent phenyl compound; however, these changes resulted in a reduction in metabolic stability; unusually, enzyme-mediated oxidation was found to take place on the cubane core. A BCP analogue () was found to be equipotent to its parent phenyl compound and showed significantly improved metabolic properties. While these results demonstrate the utility of these atypical bioisosteres when used in a medicinal chemistry program, the search to find a suitable bioisostere may well require the preparation of many candidates, in our case, 32 compounds

Odpowiedź na dożylne podawanie rt-PA u pacjentów w podeszłym wieku z udarem mózgu

Użycie rekombinowanego tkankowego aktywatora plazminogenu (rt-PA, recombined tissue plasminogen activator) u pacjentów powyżej 80. roku życia z udarem mózgu pozostaje kontrowersyjne i wciąż trwa debata nad istnieniem różnic w odpowiedzi na rt-PA, zależnych od płci. Autorzy ocenili kliniczną wartość terapii trombolitycznej u osób powyżej 80. roku życia (grupa osób starszych) w porównaniu z grupą osób młodszych oraz oszacowali obecność różnic w odpowiedzi na rt-PA wynikających z różnicy płci. Wszystkich kolejno przyjmowanych pacjentów (n = 157), leczonych rt-PA, oceniano prospektywnie od lipca 2001 roku, włączając 49 chorych w podeszłym wieku, którzy spełnili kryteria Narodowego Instytutu Zaburzeń Neurologicznych i Udaru (NINDS, National Institute of Neurological Disorders and Stroke). Grupy starszych i młodszych osób porównano pod kątem: zmian w punktacji Skali Udaru Narodowego Instytutu Zdrowia (NIHSS, National Institute of Health Stroke Scale) w 1. godzinie, w 24. godzinie oraz 7. dnia po podaniu rt-PA; korzystnego rezultatu 90. dnia ([wg zmodyfikowanej Skali Rankina {mRS, modified Rankin Scale}] mRS 0–1 lub 2, jeżeli mRS = 2 przed udarem); objawowych krwawień oraz odsetka zgonów. Za pomocą regresji logistycznej wykazano, że wyjściowa punktacja w NIHSS (iloraz szans [OR, odds ratio] 0,59; 95-procentowy przedział ufności [CI, confidence interval] 0,41-0,84) była niezależnym czynnikiem prognostycznym korzystnego rezultatu, ale nie płeć (OR 0,72; 95% CI 0,33-1,56) lub wiek powyżej 80 lat (OR 0,74; 95% CI 0,32-1,70). Wskaźniki poprawy klinicznej, śmiertelności czy objawowego krwawienia do ośrodkowego układu nerwowego również nie wiązały się z wiekiem ani z płcią. Podsumowując, odpowiedź na dożylne podanie rt-PA nie jest upośledzona u starszych pacjentów z udarem mózgu, a wrażliwość na leczenie jest taka sama u mężczyzn i u kobiet. Polski Przegląd Neurologiczny 2008; 4 (1): 36-3

Linking in vitro lipolysis and microsomal metabolism for the quantitative prediction of oral bioavailability of BCS II drugs administered in lipidic formulations

Lipidic formulations (LFs) are increasingly utilized for the delivery of drugs that belong to class II of the Biopharmaceutics Classification System (BCS). The current work proposes, for the first time, the combination of in vitro lipolysis and microsomal metabolism studies for the quantitative prediction of human oral bioavailability of BCS II drugs administered in LFs. Marinol® and Neoral® were selected as model LFs and their observed oral bioavailabilities (Fobserved) obtained from published clinical studies in humans. Two separate lipolysis buffers, differing in the level of surfactant concentrations, were used for digestion of the LFs. The predicted fraction absorbed (Fabs) was calculated by measuring the drug concentration in the micellar phase after completion of the lipolysis process. To determine first-pass metabolism (Fg∙Fh), drug depletion studies with human microsomes were performed. Clearance values were determined by applying the “in vitro half-life approach”. The estimated Fabs and Fg∙Fh values were combined for the calculation of the predicted oral bioavailability (Fpredicted). Results showed that there was a strong correlation between Fobserved and Fpredicted values only when Fabs was calculated using a buffer with surfactant concentrations closer to physiological conditions. The general accuracy of the predicted values suggests that the novel in vitro lipolysis/metabolism approach could quantitatively predict the oral bioavailability of lipophilic drugs administered in LFs

Identification of Protein Targets of Reactive Metabolites of Tienilic Acid in Human Hepatocytes

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Chemical Research in Toxicology, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see http://pubs.acs.org/doi/abs/10.1021/tx300103jTienilic acid (TA) is a uricosuric diuretic that was withdrawn from the market only months after its introduction because of reports of serious incidents of drug-induced liver injury including some fatalities. Its hepatotoxicity is considered to be primarily immunoallergic in nature. Like other thiophene compounds, TA undergoes biotransformation to a S-oxide metabolite which then reacts covalently with cellular proteins. To identify protein targets of TA metabolites, we incubated [14C]-TA with human hepatocytes, separated cellular proteins by 2D gel electrophoresis, and analyzed proteins in 36 radioactive spots by tryptic digestion followed by LC-MS/MS. Thirty one spots contained at least one identifiable protein. Sixteen spots contained only one of 14 non-redundant proteins which were thus considered to be targets of TA metabolites. Six of the 14 were also found in other radioactive spots that contained from 1 to 3 additional proteins. Eight of the 14 had not been reported to be targets for any reactive metabolite other than TA. The other 15 spots each contained from 2–4 identifiable proteins, many of which are known targets of other chemically reactive metabolites, but since adducted peptides were not observed, the identity of the adducted protein(s) in these spots is ambiguous. Interestingly, all the radioactive spots corresponded to proteins of low abundance, while many highly abundant proteins in the mixture showed no radioactivity. Furthermore, of approximately 16 previously reported protein targets of TA in rat liver (Methogo, R., Dansette, P. and Klarskov, K. (2007) Int. J. Mass Spectrom., 268, 284–295), only one (fumarylacetoacetase) is among the 14 targets identified in this work. One reason for this difference may be statistical, given that each study identified a small number of targets from among thousands present in hepatocytes. Another may be the species difference (i.e. rat vs. human), and still another may be the method of detection of adducted proteins (i.e. Western blot vs. C-14). Knowledge of human target proteins is very limited. Of more than 350 known protein targets of reactive metabolites, only 42 are known from human and only 21 of these are known to be targets for more than one chemical. Nevertheless, the demonstration that human target proteins can be identified using isolated hepatocytes in vitro should enable the question of species differences to be addressed more fully in the future

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients

Background: Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Results: Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Conclusions: Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Figure not available: see fulltext. © 2015 Freitas et al.; licensee Springer

What are the most efficacious treatment regimens for isoniazid-resistant tuberculosis?:A systematic review and network meta-analysis

INTRODUCTION: Consensus on the best treatment regimens for patients with isoniazid-resistant TB is limited; global treatment guidelines differ. We undertook a systematic review and meta-analysis using mixed-treatment comparisons methodology to provide an up-to-date summary of randomised controlled trials (RCTs) and relative regimen efficacy. METHODS: Ovid MEDLINE, the Web of Science and EMBASE were mined using search terms for TB, drug therapy and RCTs. Extracted data were inputted into fixed-effects and random-effects models. ORs for all possible network comparisons and hierarchical rankings for different regimens were obtained. RESULTS: 12 604 records were retrieved and 118 remained postextraction, representing 59 studies-27 standalone and 32 with multiple papers. In comparison to a baseline category that included the WHO-recommended regimen for countries with high levels of isoniazid resistance (rifampicin-containing regimens using fewer than three effective drugs at 4 months, in which rifampicin was protected by another effective drug at 6 months, and rifampicin was taken for 6 months), extending the duration of rifampicin and increasing the number of effective drugs at 4 months lowered the odds of unfavourable outcomes (treatment failure or the lack of microbiological cure; relapse post-treatment; death due to TB) in a fixed-effects model (OR 0.31 (95% credible interval 0.12-0.81)). In a random-effects model all estimates crossed the null. CONCLUSIONS: Our systematic review and network meta-analysis highlight a regimen category that may be more efficacious than the WHO population level recommendation, and identify knowledge gaps where data are sparse. SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO CRD42014015025