Systematic analysis of genome-wide fitness data in yeast reveals novel gene function and drug action

The relationship between co-fitness and co-inhibition of genes in chemicogenomic yeast screens provides insights into gene function and drug target prediction

Predicting lifespan-extending chemical compounds for C. elegans with machine learning and biologically interpretable features

Recently, there has been a growing interest in the development of pharmacological interventions targeting ageing, as well as in the use of machine learning for analysing ageing-related data. In this work, we use machine learning methods to analyse data from DrugAge, a database of chemical compounds (including drugs) modulating lifespan in model organisms. To this end, we created four types of datasets for predicting whether or not a compound extends the lifespan of C. elegans (the most frequent model organism in DrugAge), using four different types of predictive biological features, based on: compound-protein interactions, interactions between compounds and proteins encoded by ageing-related genes, and two types of terms annotated for proteins targeted by the compounds, namely Gene Ontology (GO) terms and physiology terms from the WormBase’s Phenotype Ontology. To analyse these datasets, we used a combination of feature selection methods in a data pre-processing phase and the well-established random forest algorithm for learning predictive models from the selected features. In addition, we interpreted the most important features in the two best models in light of the biology of ageing. One noteworthy feature was the GO term “Glutathione metabolic process”, which plays an important role in cellular redox homeostasis and detoxification. We also predicted the most promising novel compounds for extending lifespan from a list of previously unlabelled compounds. These include nitroprusside, which is used as an antihypertensive medication. Overall, our work opens avenues for future work in employing machine learning to predict novel life-extending compounds

n-vitro time-kill assays and semi-mechanistic pharmacokinetic-pharmacodynamic modeling of a beta-lactam antibiotic combination against enterococcus faecalis: Optimizing dosing regimens for the geriatric population

Pharmacokinetic-pharmacodynamic (PKPD) modeling and simulation have emerged as pivotal tools in drug development and usage. Such models characterize typical trends in data and quantify the variability in relationships among dose, concentration, and desired effects. For antibacterial applications, models characterizing bacterial growth and antibiotic-induced bacterial killing offer insight into interactions between antibiotics, bacteria, and the host. Simulations from these models predict outcomes for untested scenarios, refine study designs, and optimize dosing regimens. Enterococcus faecalis, a significant opportunistic bacterial pathogen with increasing clinical relevance, is commonly found in the gastrointestinal tract but can lead to severe infection, such as endocarditis. Treatments for E. faecalis endocarditis involves combination antibiotic therapy, such as beta-lactam antibiotics and aminoglycosides. However, due to the toxicity of aminoglycosides, the primary treatment is typically double beta-lactam therapy—ampicillin and ceftriaxone. Eradicating an E. faecalis infection typically requires a lengthy six-week course of antibiotic treatment. However, keeping patients in hospitals for such an extended duration is impractical. Therefore, the objective of this thesis project is to explore the extension of double beta-lactam therapy to outpatient antibiotic treatment (OPAT). This approach is gaining importance due to the rising risks of hospital-acquired infections and escalating healthcare expenses. Leveraging the stability of penicillin G, which can be stored at room temperature for extended periods, makes it a promising candidate for OPAT, offering potential benefits in terms of both efficacy and cost-effectiveness. Despite limited evidence for penicillin G plus ceftriaxone, this research successfully bridges the gap through in-vitro time-kill assays and the subsequent development of a semi-mechanistic model for this antibiotic combination against E. faecalis isolates. This dissertation research evaluated 21 clinical strains of E. faecalis isolated from infected patients\u27 blood, sourced from Mount Sinai Health System and a hospital in Detroit as part of Dr. Jaclyn Cusumano’s American Association of Pharmacists (AACP) new investigator award research project. The first aim was to conduct susceptibility testing on these isolates. This testing played a pivotal role in guiding antibiotic therapy by determining a drug\u27s minimum inhibitory concentration (MIC) for a specific bacterial strain, offering insight into its effectiveness. The project highlights the importance of knowing a patient\u27s strain susceptibility since it influences the dosing regimen or treatment strategy. After susceptibility testing using broth microdilution techniques, strains were categorized as highly susceptible (MIC ≤ 2 μg/ml) or less susceptible (MIC = 4 μg/ml) to penicillin G. The next phase of the project involved in-vitro time-kill assays—a gold standard method for testing antibiotic concentrations and synergy in combination therapies. All 21 patient isolates were tested with penicillin G monotherapy and in combination with ceftriaxone, along with testing ampicillin and ceftriaxone combination therapies for comparison. It was noted that both combinations showed efficacy for strains highly susceptible to penicillin G (MIC ≤ 2 μg/ml), exhibiting bactericidal and synergistic activity. However, both treatments demonstrated poor performance for the less susceptible strains (MIC = 4 μg/ml). This observation focuses on the importance of in-vitro pharmacodynamic studies in understanding antibiotic action dynamics, forming the basis for the semi-mechanistic model. These 24-hour time-kill assays strongly suggested further investigation into the penicillin G and ceftriaxone combination, while considering the differential effects of the combination on more and less susceptible strains. Semi-mechanistic models were created for two out of the twenty-one tested strains, one with high susceptibility and another with lower susceptibility, with the goal of understanding the bacterial growth and drug kill effect in greater detail along with testing different dosing regimens. Following the typical progression of constructing a semi-mechanistic PK-PD model, a bacterial sub-model was created by employing intensive sampling during time-kill assays. This approach enabled the comprehension of the complete bacterial growth dynamics for both strains. By employing non-linear least squares regression within RStudio, the predictive model was effectively fitted to the observed data, providing estimates of essential bacterial growth parameters. The utilization of the Gompertz growth model yielded a remarkably close match between predicted and observed data, giving confidence in the accuracy of the estimated growth parameters. Subsequently, the focus shifted to obtaining the most suitable pharmacodynamic (PD) parameters to accurately encapsulate the drug\u27s antibacterial effects. This necessitated the use of a mathematical model. A widely employed model for this purpose is the Sigmoidal Emax model—an empirical model that is widely published. This model emerged as a valuable tool for formalizing the interpretation of experimental data and understanding the influence of altering penicillin G concentrations, both individually and in conjunction with ceftriaxone. Leveraging the data analysis capacity of RStudio, nonlinear least squares regression analysis was used to intricately fit the sigmoidal Emax equation to the observed data. This led to obtaining vital parameters, including Emax (maximum effect), EC50 (half-maximal effective concentration), and the sigmoidicity factor. Subsequent evaluation of goodness of fit based visual predictive checks and low standard errors in estimated parameters confirmed the favorable alignment between the predicted model and observed data. Physiologically based pharmacokinetic (PBPK) modeling and simulation stands as a well-established approach that bridges insights from preclinical studies to clinical outcomes. By combining drug-specific information with a comprehensive understanding of physiological and biological processes at the organism level, PBPK models mechanistically depict the behavior of drugs within biological systems. This enables the a priori simulation of drug concentration-time profiles. What distinguishes PBPK modeling is its unique capability to account for physiological variations within specific populations, offering predictive insights into pharmacokinetics tailored to those groups. This thesis project ventured into two vital applications of PBPK models: extrapolating novel clinical scenarios and exploring pharmacokinetics in special populations, particularly the geriatric demographic. With the aim of comprehending the pharmacokinetics of penicillin G and ceftriaxone, the project leveraged the Simcyp® Simulator, a modeling and simulation tool that is widely used in drug development. This platform pools the anatomical, physiological, drug-related, and trial design parameters to generate plasma drug concentration profiles. The simulated concentrations were compared against published data, with the fold error—a ratio of simulated to observed values—serving as a benchmark for model accuracy. Typically, predictions within a fold error range of 0.5 to 2 are deemed acceptable. Upon verification within the healthy population, the models were extended to geriatric subjects utilizing the Simcyp® population library. The same fold error criteria were applied, and the models adeptly predicted concentrations across both young and elderly populations. Remarkable differences in pharmacokinetics were seen in the geriatric cohort compared to a young adult population. Notably, for penicillin G, the AUC increased by 46% in the elderly due to an almost 47% decline in total clearance, stemming from a 49% reduction in glomerular filtration rate (GFR). Further expanding the PBPK model for penicillin G, the inclusion of a pharmacodynamic (PD) component led to the final goal of this project. Lua scripting in Simcyp® was utilized to build the PD model. This model used an equation that combined the bacterial growth model with the drug\u27s inhibitory effect via the Emax model. The impacts of monotherapy and combination were explored through the modulation of PD parameters. Consequently, when co-administered with ceftriaxone, kill rates for penicillin G increased, and IC50 values decreased, indicative of ceftriaxone\u27s augmentative effect. The free (unbound) plasma concentration-time profile from the developed PBPK model was linked as input to the PD model, facilitating testing and simulation of diverse penicillin G dosing regimens. Notably, penicillin G, a time-dependent beta-lactam antibiotic, exhibited a strong correlation with the PK/PD index %fT\u3eMIC (% of the dosing interval with a free concentration above MIC). This was especially pertinent for high-susceptibility strains, wherein continuous infusion of penicillin G led to the most significant reduction in bacterial density, irrespective of combination therapy or monotherapy. However, for low-susceptibility strains, the scenario differed, revealing that reliance on a single PK/PD index is not all-encompassing. For the geriatric population, the PBPK-PD model aligned with literature-backed dosing modifications for penicillin G. For highly susceptible strains, increasing the dosing interval or reducing the dose resulted in comparable reductions in bacterial density. Conversely, in low7 susceptibility strains, even an increase in AUC within the geriatric demographic failed to eradicate the bacteria. In summary, this comprehensive thesis journey navigates through the in-vitro bacterial studies and pharmacokinetic-pharmacodynamic (PKPD) modeling and simulation. This project sheds light on the ability to integrate in-vitro data with PBPK models which not only predict untested scenarios but also help dosing strategies. Overall, by addressing the clinical challenge of E. faecalis infections, the project showcased the extension of double beta-lactam therapy to penicillin G and ceftriaxone combination through a stepwise development of semi-mechanistic PK/PD model

CHARACTERIZING AND PREDICTING THE ANTIMICROBIAL PROPERTIES OF LIGNIN DERIVATIVES

Due to the overuse of antibiotics in our society, there has been a steady rise in highly antimicrobial-resistant bacteria in the last decade. This has created a renewed interest in natural phenolic compounds for antimicrobial discovery amongst the scientific community. To this end, lignin is the most abundant naturally occurring phenolic polymer on earth and has already been known to have antimicrobial properties due to its polyphenolic structure. In addition, lignin is considered a major waste product for lignocellulosic biorefineries, and its valorization into value-added products will generate extra profit for a biorefinery, making biofuels less expensive, increasing their marketability as an alternative to fossil fuels. However, the retention of lignin’s antimicrobial properties in different materials, as depolymerized products, or even the prediction of their antimicrobial properties is not well understood in the literature. Much work has utilized lignin as a functional polymer in a variety of composites and materials, but their antimicrobial properties have not been as widely explored. Therefore, ionic liquids were used in the facile preparation of cellulose-based hydrogels, and the addition of different lignocellulosic components (lignin and xylan) or the use of whole biomass (poplar and sorghum) were evaluated for their effects on hydrogel properties (mechanical and antimicrobial). The addition of both lignin and xylan improved hydrogel mechanical strength/stiffness, and lignin-containing hydrogels showed retained antimicrobial properties when screened against the target organism (Escherichia coli). Utilizing raw biomass provided increased mechanical strength (poplar), similar water retention abilities (poplar and sorghum), and retained antimicrobial properties (poplar). These results indicate that the different components of lignocellulose can be used to fine tune the properties of cellulose-based hydrogels and that lignin can confer its antimicrobial properties when incorporated into hydrogels. The antimicrobial properties of different lignin depolymerization products were explored using a reductive and oxidative depolymerization method to produce phenolic rich lignin-based bio-oils. Purified alkali-enzymatic corn stover lignin (AEL) was depolymerized by catalytic transfer hydrogenolysis using supercritical ethanol and a Ru/C catalyst, generating a bio-oil stream at high yields. Sequential extraction was used to fractionate the bio-oil into five fractions with different phenolic compositions using hexane, petroleum ether, chloroform, and ethyl acetate. Antimicrobial properties of the bio-oils were screened against Gram-positive/negative bacteria and yeast by examining microbial growth inhibition. The monomers in the bio-oil fractions contained primarily alkylated phenols, hydrogenated hydroxycinnamic acid derivatives, syringol and guaiacol-type lignins created from reductive cleavages of ether linkages. After sequential extraction, the lignin derived compounds were fractionated into groups depending on solvent polarity. Results suggest that the total monomer concentration and the presence of specific monomers (i.e., syringyl propane) may correlate to the antimicrobial activity of lignin depolymerization products, but the exact mode of action or antimicrobial activity caused by the complex mixtures of monomers and unidentified oligomers remains unclear. The same AEL lignin was depolymerized through oxidative procedures using peracetic acid, and its applications as an antibiotic replacement in the fuel ethanol industry were explored. The resulting bio-oil had a low degree of depolymerization that mostly produced unidentifiable lignin oligomers. Nonetheless, this bio-oil displayed highly selective antimicrobial properties, with up to 90% inhibition of commercially sampled lactic acid bacteria (LAB) at 4 mg/ml and no inhibition of yeast. Using the bio-oil (4 mg/ml) as an alternative antibiotic treatment during simultaneous-saccharification and fermentation of raw corn starch showed an 8% increase in ethanol production at a yeast to LAB ratio of 1:100, compared to untreated contaminated controls. The ability of the bio-oil to improve ethanol yields clearly shows its efficacy as an alternative antibiotic and that depending on depolymerization method lignin derivates can display a variety of useful antimicrobial properties/applications. The final study was the first attempt in the literature to predict the antimicrobial properties of lignin derivatives using quantitative structure−activity relationship (QSAR) models. First, the open-access database ChEMBL, with non-lignin specific compounds, was used to create datasets of compounds with MIC activity measurements against both B. subtilis and E. coli. Machine learning algorithms were used to develop the QSARs for the large ChEMBL datasets and were found to underpredict the antimicrobial activity of actual lignin compounds. Conversely, as metanalysis of the literature containing MIC data of lignin derivatives were used to build QSAR models with ordinary least square regressions (OLS). An accurate QSAR model for E. coli was not found, but a satisfactory model was obtained for the B. subtilis metanalysis dataset. Molecular Operation Environment (MOE)-type descriptors and the number of aliphatic carboxylic acid groups showed strong correlations to the MIC values (R2 of 0.759). Comparatively, an additional dataset was experimentally derived by screening 25 lignin monomers and three dimers against B. subtilis by measuring bacterial load difference (BLD). This datasets QSAR, using OLS, found that MOE-type descriptors and the number of aromatic hydroxyl groups were better predictors of BLD (R2 of 0.831). Thus, the smaller datasets highlighted how the variability in antimicrobial measurements and the specific compounds used will impact the predictive nature of the resulting QSARs. Overall, this entire work provides critical knowledge and guidance on using lignin as an antimicrobial source in different industrial processes/products and the identification of lignin derivatives with enhanced activity

In vitro techniques for the assessment of neurotoxicity.

Risk assessment is a process often divided into the following steps: a) hazard identification, b) dose-response assessment, c) exposure assessment, and d) risk characterization. Regulatory toxicity studies usually are aimed at providing data for the first two steps. Human case reports, environmental research, and in vitro studies may also be used to identify or to further characterize a toxic hazard. In this report the strengths and limitations of in vitro techniques are discussed in light of their usefulness to identify neurotoxic hazards, as well as for the subsequent dose-response assessment. Because of the complexity of the nervous system, multiple functions of individual cells, and our limited knowledge of biochemical processes involved in neurotoxicity, it is not known how well any in vitro system would recapitulate the in vivo system. Thus, it would be difficult to design an in vitro test battery to replace in vivo test systems. In vitro systems are well suited to the study of biological processes in a more isolated context and have been most successfully used to elucidate mechanisms of toxicity, identify target cells of neurotoxicity, and delineate the development and intricate cellular changes induced by neurotoxicants. Both biochemical and morphological end points can be used, but many of the end points used can be altered by pharmacological actions as well as toxicity. Therefore, for many of these end points it is difficult or impossible to set a criterion that allows one to differentiate between a pharmacological and a neurotoxic effect. For the process of risk assessment such a discrimination is central. Therefore, end points used to determine potential neurotoxicity of a compound have to be carefully selected and evaluated with respect to their potential to discriminate between an adverse neurotoxic effect and a pharmacologic effect. It is obvious that for in vitro neurotoxicity studies the primary end points that can be used are those affected through specific mechanisms of neurotoxicity. For example, in vitro systems may be useful for certain structurally defined compounds and mechanisms of toxicity, such as organophosphorus compounds and delayed neuropathy, for which target cells and the biochemical processes involved in the neurotoxicity are well known. For other compounds and the different types of neurotoxicity, a mechanism of toxicity needs to be identified first. Once identified, by either in vivo or in vitro methods, a system can be developed to detect and to evaluate predictive ability for the type of in vivo neurotoxicity produced. Therefore, in vitro tests have their greatest potential in providing information on basic mechanistic processes in order to refine specific experimental questions to be addressed in the whole animal

Vegetable Fiber Reinforced Calcium Aluminate Cement based composites for construction materials VFRCCs

Vegetable Fiber Reinforced Cement Composite Materials (VFRCC) have emerged as a potential construction material, providing adequate load-bearing capacity and ductility for non-structural applications. VFRCC have good mechanical properties (strength and ductility) which make them potentially suitable for non-structural construction applications. The improved capacity of this material is due to the fact that, unlike ordinary mortar, a reinforcement is introduced that is distributed throughout the section of the piece, allowing the fibers to work throughout the entire tensile block. Commonly publications analyze the mechanical behavior of these materials in bending mode, their durability properties, chemical compositions and the micro-structure of matrix. The objective of this doctoral thesis is to evaluate the mechanical behavior of VFRCC as a non-structural construction material. In this context, a cement-based matrix will be used which will be optimized by incorporating two different additives, a pozzolanic addition and two types of vegetable fibers (VF) as reinforcing elements, that will be introduced into the matrix in different proportions. The mechanical behavior will be carried out by means of three-point bending tests and four mechanical parameters will be analyzed, depending on the level of applied load: Limit of proportionality (LOP), maximum resistance to bending (MOR), Modulus of elasticity (MOE ) and specific energy. The durability of the material will also be studied through an accelerated aging treatment consisting of 10 dry-wet cycles. The chemical composition of the matrix will also be analyzed by X-Ray diffractometry (XRD) and the micro-structure by scanning electron microscopy (SEM) and backscattered electron microscopy (BSEM) and atomic composition by energy dispersive X-Ray spectroscopy (EDX). In terms of mechanical performance, it was found that the composites containing 10% cotton linter fiber with the polycarboxylate additive incorporated, exhibited higher flexural strength compared to the flax fiber composites, with good and sufficient deformability and ductility. At the same time, the influence of CAC on VFRCC demonstrated that this cement matrix could be a viable alternative to an OPC matrix in terms of VF durability for this type of material, compared to those conventional PV-OPC.Los materiales Compuestos de Cemento Reforzado con Fibras Vegetales (CCRFV) han surgido como un potencial material de construcción, proporcionando una capacidad de carga y ductilidad adecuadas para aplicaciones no estructurales. Los CCRFV poseen unas buenas propiedades mecánicas (resistencia y ductilidad) que los hacen potencialmente adecuados para aplicaciones constructivas no estructurales. La capacidad mejorada de este material se debe al hecho de que, a diferencia del mortero ordinario, se introduce un refuerzo que se distribuye en toda la sección de la pieza, permitiendo que las fibras funcionen en todo el bloque de tracción completo. Comúnmente, las publicaciones analizan el comportamiento mecánico de estos materiales a flexión, sus propiedades de durabilidad, composiciones químicas y microestructura de la matriz. El objetivo de esta tesis doctoral es evaluar el comportamiento mecánico de los CCRVF como un material de construcción no estructural. En este contexto, se utilizará una matriz a base de cemento que se optimizará incorporando dos aditivos distintos, una adición puzolánica y dos tipos de fibras vegetales (FV) como elementos de refuerzo, que se introducirán en la matriz en diferentes proporciones. El comportamiento mecánico se llevará a cabo mediante ensayos de flexión de tres puntos y se analizarán, en función del nivel de carga aplicada, cuatro parámetros mecánicos: Límite de proporcionalidad (LOP), resistencia máxima a flexión (MOR), Módulo de elasticidad (MOE) y Energia específica. También se estudiará la durabilidad del material mediante un tratamiento de envejecimiento acelerado compuesto por 10 ciclos seco-húmedo. También se analizarán la composición química de la matriz mediante difractometria de rayos x (DRX) y la microestructura mediante microscopía electrónica de barrido (SEM) y microscopía de electrones retrodispersados (BSEM) y composición atómica mediante espectroscòpia de rayos X con dispersión de energia (EDX). En términos de rendimiento mecánico, se encontró que los compuestos que contenían 10% de algodón con el aditivo de policarboxilato incorporado, exhibieron mayor resistencia a la flexión en comparación con los compuestos de fibra de lino, con una buena y suficiente capacidad de deformación y ductilidad. Al mismo tiempo, la influencia del CAC en los CCRFV demostró que esta matriz de cemento podría ser una alternativa viable a una matriz de OPC en términos de durabilidad de las FV para este tipo de material, en comparación con los FV-OPC convencionales. También se observó que los ciclos de envejecimiento acelerado tenían un efecto mayor en la propia matriz de CAC que en las FV, lo que indica que esta matriz podría ser una alternativa viable para producir CCRFV durable. En términos de adición puzolánica en matriz CAC, los resultados de los análisis BSEM/SEM y XRD revelaron que, con concentraciones más altas de puzolana, el humo de sílice no reacciona por completo con el CAC, por lo que aparecía un excedente de partículas de SF en la microestructura de la matriz. Según los resultados de XRD, las nuevas fases de la strätlingita (C2ASH8) estaban presentes en mezclas con bajo contenido de SF. Simultáneamente, la incorporación de humo de sílice en CCRFV pareció minimizar aún más la degradación de la fibra. Esta tesis doctoral proporciona conocimientos y datos que pueden ayudar a futuras investigaciones y contribuir al desarrollo futuro de estrategias de diseño de CCRFV.Els materials compostos de Ciment Reforçat amb Fibres Vegetals (CCRFV) han sorgit com un possible material de construcció, proporcionant una capacitat de carrega i ductilitat adequades per a aplicacions no estructurals. Els CCRFV tenen unes bones propietats mecàniques (resistència i ductilitat) que els fan potencialment adequats per a aplicacions constructives no estructurals. La capacitat millorada d'aquest material es deu al fet que, a diferencia del morter ordinari, se n'introdueix un que es distribueix en tota la secció de la peca, permetent que les fibres funcionin a tot el bloc de tracció complet. Comunament, les publicacions analitzen el comportament mecànic d’aquests materials a flexió, les seves propietats de durabilitat, composicions químiques i microestructura de la matriu. L´objectiu d´aquesta tesi doctoral es avaluar el comportament mecànic dels CCRVF com un material de construcció no estructural. En aquest context, s’utilitzarà una matriu a base de ciment que s’optimitzarà incorporant dos additius diferents, una addició putzolànica i dos tipus de fibres vegetals (FV) com a elements de reforç, que s’introduiran a la matriu en diferents proporcions. El comportament mecànic es dura a terme mitjançant assaigs de flexió de tres punts i s'analitzaran, segons el nivell de carrega aplicada, quatre paràmetres mecànics: Límit de proporcionalitat (LOP), resistència màxima a flexió (MOR), Mòdul d'elasticitat (MOE) i Energia especifica. També s’estudiarà la durabilitat del material mitjançant un tractament d'envelliment accelerat compost per 10 cicles secs-humit. També s'analitzaran la composició química de la matriu mitjançant difractometria de raigs x (DRX) i la microestructura mitjançant microscopia electrònica d'escombrada (SEM) i microscopia d'electrons retrodispersats (BSEM) i composició atòmica mitjançant espectroscopia de raigs X amb dispersió d'energia (EDX). En termes de rendiment mecànic, es va trobar que els compostos que contenien 10% de coto i amb Sika Viscocrete incorporat, van exhibir mes resistència a flexió en comparació dels compostos de fibra de lli, amb una bona i suficient capacitat de deformació i ductilitat. Simultàniament, la influencia del CAC als CCRFV va demostrar que aquesta matriu de ciment podria ser una alternativa viable a una matriu de ciment Portland comú en termes de durabilitat de les FV en aquests materials, en comparació dels FV-OPC convencionals. També, es va observar que els cicles d'envelliment accelerat tenien un efecte mes gran a la mateixa matriu de CAC que a les FV, cosa que indica que aquesta matriu podria ser una alternativa viable per produir CCRFV durables. En termes d’addició putzolànica en matriu CAC, els resultats de les anàlisis BSEM/SEM i XRD van revelar que, amb concentracions mes altes de puzolana, el fum de sílice no reacciona del tot amb el CAC, per la qual cosa apareixia un excedent de partícules de SF a la microestructura de la matriu. Segons els resultats de XRD, les noves fases de la stratlingita (C2ASH8) estaven presents en barreges amb baix contingut de SF. Simultàniament, la incorporació de fum de sílice a CCRFV va semblar minimitzar encara mes la degradació de la fibra. Aquesta tesi doctoral proporciona coneixements i dades que poden ajudar a investigar futures i contribuir al desenvolupament futur d’estratègies de disseny de CCRFV.Postprint (published version

Outlook Magazine, Fall 2004

https://digitalcommons.wustl.edu/outlook/1156/thumbnail.jp

The side-effects of airborne pesticides on fungi and vascular plants

VakpublicatieInstitute of Environmental Science

Patterns of innovation in the chemical industry

No abstract available. From the first page of the introduction: The analysis of innovation contained in this thesis differs considerably in both scope and aims from most analyses of innovation. It is important to discuss why the approach taken has been adopted, and to justify its usefulness. There is no absence of analyses of innovation and associated invention. Individual inventions have been examined, notedly by Jewkes and his co-authors (1); analyses have been made of innovation in selected industries, and this has been related to international trade in these industries (2); the detailed antecedents of individual technological innovations have been traced back in time, both for weapon systems and for civilian products (3); the spread of important new techniques, normally associated with large-scale capital investment, has been analysed (4). Much of this work has been done, either directly or indirectly, to answer specific questions of science policy, and these works have been influential factors in the formulation of science policy. The questions which may be answered by such approaches are important. Is money aimed at producing inventions (and, by implication at least, innovation) best invested in establishing large research centres, or in encouraging with suitable fiscal measures individual inventors (5)? What is the relationship between the concentration of an industry and its propensity to innovate? Should government finance be concentrated in closely targetted contracts, or in university research? What should the government attitude be towards industries, such as the pharmaceuticals industry, in which successful products enjoy what may appear super-normal profits while overall heavy research expenditure is incurred (6)