Investigation of the metabolism of N, N-Dimethylformamide and its metabolites

The industrial solvent N, N-dimethylformamide (DMF) causes liver damage in humans. The hepatotoxicity of N-alkylformamides seems to be linked to their metabolism to N-alkylcarbamic acid thioesters. To clarify the role of metabolism in DMF hepatotoxicity, the metabolic fate of DMF was investigated in rodents. DMF was rapidly metabolised and excreted in the urine as N-hydroxymethyl-N-methyl-formamide (HMMF), N-acetyl-S-(N-methylcarbamoyl) cysteine (AMCC) and a metabolite measured as formamide by GLC. At high doses (0.7 and 7.0mmo1/kg) a small proportion of the dose was excreted unchanged. AMCC, measured by GLC after derivatisation to ethyl N-methylcarbamate, was a minor metabolite. Only 5.2% of the dose (0.1mmo1/kg) in rats or 1.2% in mice was excreted as AMCC. The minor extent of this metabolic pathway in rodents might account for the marginal liver damage induced by DMF in these species. In a collaborative study, volunteers were shown to metabolise DMF to AMCC to a greater extent than rodents. Nearly 15% of the inhaled dose (0.049mmo1/kg) was excreted as AMCC. This result suggests that the metabolic pathway leading to AMCC is more important in humans than in rodents. Consequently the risk associated with exposure to DMF might be higher in humans than in rodents. The metabolism of formamides to S-(N-alkylcarbamoyl) glutathione, the metabolic precursor of the thioester mercapturates, was studied using mouse, rat and human hepatic microsomes. The metabolism of NMF (10mM) to S-(N-methylcarbanoyl)glutathione (SMG) required the presence of GSH, NADPH and air. Generation of S-(N-methyl-carbamoyl)glutathione (SMG) was inhibited when incubations were conducted in an atmosphere of CO:air (1:1) or when SKF 525-A (3.0mM) was included in the incubations. Pre-treatment of mice with phenobarbitone (PB, 80mg/kg for 4 days) or beta-naphthoflavone (BNF, 50mg/kg for 4 days) failed to increase the microsomal formation of SMG from NMF. This result suggests that the oxidation of NMF is catalysed by a cytochrome P-450 isozyme which is unaffected by PB or BNF. Microsomal incubations with DMF (5 or 10mM) failed to generate measurable amounts of SMG although DMF was metabolised to HMMF. Incubations of microsomes with HMMF resulted in the generation of a small amount of SMG which was affected by inhibitors of microsomal enzymes in the same way as in the case of NMF. HMMF was metabolised to AMCC by rodents in vivo. This result suggests that HMMF is a major intermediate in the metabolic activation of DMF.

Studies of the metabolism and the toxicity of N-Methylformamide and related amides

The hepatotoxicity of the industrial solvent and investigational anti-tumour agent N-methylformamide (NMF, HOCNHCH3) and several structural analogues was assessed in mice. NMF and its ethyl analogue (NEF) were equipotent hepatotoxins causing extensive centrilobular necrosis and damage to the gall bladder. Pretreatment of mice with SKF525A did not influence the toxicity of these N-alkylformamides. Replacement of the formyl hydrogen of NMF with deuterium or methyl significantly reduced its hepatotoxicity. An in vitro model for the study of the toxicity and metabolism of N-alkylformamides was developed using isolated mouse hepatocytes. The cytotoxicity of NMF in vitro was concentration-dependent with maximal toxicity being achieved at concentrations of 5mM or above. The cytotoxic potential of related amides correlated well with their in vivo hepatotoxic potential. Pretreatment of mice with buthionine sulphoximine (BSO), which depleted hepatocytic levels of glutathione to 15% of control values, exacerbated the cytotoxicity of NMF towards the hepatocytes. NMF (1mM or above), incubated with isolated mouse hepatocytes, depleted intracellular glutathione levels to 26% of control values within 4h. Depletion of glutathione was quantitatively matched by the formation of a carbamoylating metabolite. Metabolism was dependent on the concentration of NMF and was drastically reduced in incubations of hepatocytes isolated from mice pretreated with BSO. The carbamoylating metabolite, S-(N-methylcarbamoyl)-glutathione (SMG), was identified in vitro using FAB-MS. The generation of SMG was subject to a large primary H/D kinetic isotope effect when the formyl hydrogen was replaced with deuterium. Likewise, glutathione depletion and metabolite formation were reduced or abolished by the deuteration or methylation of the formyl moiety of NMF. NEF, like NMF, depleted hepatocytic glutathione levels and was metabolised to a carbamoylating metabolite. Radioactivity derived from 14C-NMF and 14C-NEF, labelled in the alkyl moieties, was found to be irreversibly associated with microsomal protein on incubation in vitro. Binding was dependent on the presence of NADPH and was mostly abolished in the presence of reduced glutathione. SKF525A failed to influence the binding.

Heat shock proteins in leukaemia cell differentiation and cell death

When HL60 cells were induced to differentiate to granulocyte-like cells with the agents N-methylformamide and tunicamycin an concentrations marginally below those which were cytotoxic, there was a decrease in the synthesis of the glucose- regulated proteins which preceded the expression of markers of a differentiated phenotype. There was a transient increase in the amount of hsp70 after 36 hours in NMF treated cells but in differentiated cells negligible amounts were detected. Inducers which were known to modulate hsp70 such as azetadine carboxylic acid did not induce differentiation suggesting early changes in the endoplasmic reticulum may be involved in the commitment to terminal differentiation of HL60 cells. These changes in group synthesis were not observed when K562 human chronic myelogenous leukemia cells were induced to differentiate to erythroid-like cells but there was a comparable increase in amounts of hsp70. When cells were treated with concentrations of drugs which brought about a loss in cell viability there was an early increase in the amount of hsp70 protein in the absence of any increase in synthesis. HL60 cells were treated with NMF (225mM), Adriamycin (1μM), or CB3717 (5μM) and there was an increase in the amounts of hsp70, in the absence of any new synthesis, which preceded any loss of membrane integrity and any significant changes in cell cycle but was concomitant with a later loss in viability of > 50% and a loss in proliferative potential. The amounts of hsp70 in the cell after treatment with any of the drugs was comparable to that obtained after a heat shock. Following a heat shock hsp70 was translocated from the cytoplasm to the nucleus, but treatment with toxic concentrations of drug caused hsp70 to remain localised in the cytoplasm. Changes in hsp70 turn-over was observed after a heat shock compared to NMF-treated cells. Morphological studies suggested that cells that had been treated with NMF and CB3717 were undergoing necrosis whereas the Adriamycin cells showed characteristics that were indicative of apoptosis. The data supports the hypothesis that an increase in amounts of hsp70 is an early marker of cell death.

Studies of the mechanism of antitumour activity of N-methylformamide

NMF induces the terminal differentiation or acquisition of more benign characteristics in certain malignant cells in vitro and has good antitumour activity against murine tumours in vivo. This study was concerned with a comparison of the mechanism of antitumour activity of NMF in vitro and in vivo against the murine TLX5 lymphoma, which is sensitive to NMF in vivo. TLX5 cells incubated continuously with NMF in vitro showed a concentration and time dependent decrease in cell growth rate, which was associated with an increase in membrane permeability, a decrease in cell size and at the higher NMF concentrations, cell death. Analysis of the cell cycle after incubation with NMF indicated an early G1 phase arrest. TLX5 cells were incubated with NMF and washed free of the drug. Analysis of clonogenicity and tumourigenicity showed that all viable cells retained their proliferative potential and malignancy. Therefore, TLX5 cells exposed to NMF in vitro are not terminally differentiated, but reside in a quiescent substate which was reversed on drug removal. The intracellular GSH levels of TLX5 cells was decreased in a concentration and time dependent fashion by NMF. GSH depletion of TLX5 cells was not however a prerequisite for growth arrest, unlike the reported data for human colon carcinoma cell lines. A single administration of NMF caused a dose dependent regression of the TLX5 lymphoma in tumour bearing mice. Cell death occurred by apoptosis and necrosis. The antitumour activity of NMF was dependent on formyl C-H bond fission, with the parent drug or metabolites reaching all parts of the tumour 4h after dosing. There was a non-dose dependent increase in the S phase population, which was due to an increase in DNA synthesis, 24h after administration of NMF. NMF administration caused a decrease in GSH levels of the TLX5 lymphoma, which did not correlate with the antitumour response. However, the GSH depleting agent, BSO, marginally increased the antitumour activity of NMF.

The role of metabolism in the toxicity of N-alkylformamides

Using ionspray tandem mass spectrometry the glutathione conjugate SMG was identified as a biliary metabolite of DMF in rats (0.003% of a dose of 5OOmg/kg DMF i.p.). Formation of this metabolite was increased five fold after induction of CYP2E1 by acetone, and was inhibited to 20% of control values following pretreatment with disulfrram. Generation of SMG from DMF in vivo was shown to exhibit a large kinetic deuterium isotope effect (KWKD=10.1 ± 1.3), which most likely represents the product of 2 discrete isotope effects on N-demethylation and formyl oxidation reactions.The industrial solvent N,N-dimethylformamide (DMF) and the investigational anti-tumour agent N-methylformamide (NMF) cause liver damage in rodents and humans. The hepatotoxicity of N-alkylformamides is linked to their metabolism to N-alkylcarbamic acid thioesters. The enzymatic details of this pathway were investigated. Hepatocytes isolated from BALB/c mice which had been pretreated with acetone, an inducer of the cytochrome P-450 isozyme CYP2E1, were incubated with NMF (10mM). NMF caused extensive toxicity (> 90% ) as determined by lactate dehydrogenase (LDH) release, compared to cells from untreated animals. Incubation of liver cells with NMF for 6 hrs caused 60±17% LDH release whilst in the presence of DMSO (10mM), an alternative substrate for CYP2E1, LDH release was reduced to 20±10% . The metabolism of NMF to S-(N-methylcarbamoyl)glutathione (SMG) was measured in incubates with liver microsomes from mice, rats or humans. Metabolism of NMF was elevated in microsomes isolated from rats and mice pretreated with acetone, by 339% and 183% respectively. Pretreatment of animals with 4-methylpyrazole induced the metabolism of NMF to 280% by rat microsomes, but was without effect on NMF metabolism by mouse microsomes. The CYP2E1 inhibitors or alternative substrates diethyl dithiocarbamate (DEDTC), p-nitrophenol (PNP) and dimethyl sulphoxide (DMSO) strongly inhibited the metabolism of NMF in suspensions of rat liver microsomes, at concentrations which did not effect aminopyrine N-demethylation. The rate of metabolism of NMF to SMG in human microsomes correlated (r> 0.8) with the rate of metabolism of chlorzoxazone, a CYP2E1 probe. A polyclonal antibody against rat CYP2E1 (10mg/nmol P-450) inhibited NMF metabolism in microsomes from rats and humans by 75% and 80% , respectively. The amount of immunoblottable enzyme in human microsomes, determined using an anti-rat CYP2E1 antibody, correlated with the rate of NMF metabolism (r> 0.8). Purified rat CYP2E1 catalysed the generation of SMG from NMF. Formation of the DMF metabolite N-hydroxymethyl-N-methylformamide (HMMF) in incubations with rat liver microsomes was elevated by 200% following pretreatment of animals with acetone. Co-incubation with DEDTC (100μM) inhibited HMMF generation from DMF by 88% . Co-incubation of DMF (10mM) with NMF (1mM) inhibited the formation of SMG by 95% . A polyclonal antibody against rat CYP2E1 (10mg/nmol P-450) inhibited generation of HMMF in incubates with rat and human liver microsomes by 68.4% and 67.5% , respectively. Purified rat CYP2E1 catalysed the generation of HMMF from DMF. Using ionspray tandem mass spectrometry the glutathione conjugate SMG was identified as a biliary metabolite of DMF in rats (0.003% of a dose of 5OOmg/kg DMF i.p.). Formation of this metabolite was increased five fold after induction of CYP2E1 by acetone, and was inhibited to 20% of control values following pretreatment with disulfrram. Generation of SMG from DMF in vivo was shown to exhibit a large kinetic deuterium isotope effect (KHKD=10.1 ± 1.3), which most likely represents the product of 2 discrete isotope effects on N-demethylation and formyl oxidation reactions.

Text analytics of social media: Sentiment analysis, event detection and summarization

In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. ^ Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. ^ In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data. ^

Text Analytics of Social Media: Sentiment Analysis, Event Detection and Summarization

In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data.

Optimización de la factorización de matrices no negativas en Bioinformática

En los últimos años se ha incrementado el interés de la comunidad científica en la Factorización de matrices no negativas (Non-negative Matrix Factorization, NMF). Este método permite transformar un conjunto de datos de grandes dimensiones en una pequeña colección de elementos que poseen semántica propia en el contexto del análisis. En el caso de Bioinformática, NMF suele emplearse como base de algunos métodos de agrupamiento de datos, que emplean un modelo estadístico para determinar el número de clases más favorable. Este modelo requiere de una gran cantidad de ejecuciones de NMF con distintos parámetros de entrada, lo que representa una enorme carga de trabajo a nivel computacional. La mayoría de las implementaciones de NMF han ido quedando obsoletas ante el constante crecimiento de los datos que la comunidad científica busca analizar, bien sea porque los tiempos de cómputo llegan a alargarse hasta convertirse en inviables, o porque el tamaño de esos datos desborda los recursos del sistema. Por ello, esta tesis doctoral se centra en la optimización y paralelización de la factorización NMF, pero no solo a nivel teórico, sino con el objetivo de proporcionarle a la comunidad científica una nueva herramienta para el análisis de datos de origen biológico. NMF expone un alto grado de paralelismo a nivel de datos, de granularidad variable; mientras que los métodos de agrupamiento mencionados anteriormente presentan un paralelismo a nivel de cómputo, ya que las diversas instancias de NMF que se ejecutan son independientes. Por tanto, desde un punto de vista global, se plantea un modelo de optimización por capas donde se emplean diferentes tecnologías de alto rendimiento...

Multivariate Techniques in Biomechanical Analysis

This work outlines the theoretical advantages of multivariate methods in biomechanical data, validates the proposed methods and outlines new clinical findings relating to knee osteoarthritis that were made possible by this approach. New techniques were based on existing multivariate approaches, Partial Least Squares (PLS) and Non-negative Matrix Factorization (NMF) and validated using existing data sets. The new techniques developed, PCA-PLS-LDA (Principal Component Analysis – Partial Least Squares – Linear Discriminant Analysis), PCA-PLS-MLR (Principal Component Analysis – Partial Least Squares –Multiple Linear Regression) and Waveform Similarity (based on NMF) were developed to address the challenging characteristics of biomechanical data, variability and correlation. As a result, these new structure-seeking technique revealed new clinical findings. The first new clinical finding relates to the relationship between pain, radiographic severity and mechanics. Simultaneous analysis of pain and radiographic severity outcomes, a first in biomechanics, revealed that the knee adduction moment’s relationship to radiographic features is mediated by pain in subjects with moderate osteoarthritis. The second clinical finding was quantifying the importance of neuromuscular patterns in brace effectiveness for patients with knee osteoarthritis. I found that brace effectiveness was more related to the patient’s unbraced neuromuscular patterns than it was to mechanics, and that these neuromuscular patterns were more complicated than simply increased overall muscle activity, as previously thought.

Linear Hyperspectral Unmixing Using L0-norm Approximations and Nonnegative Matrix Factorization

Spectral unmixing (SU) is a technique to characterize mixed pixels of the hyperspectral images measured by remote sensors. Most of the existing spectral unmixing algorithms are developed using the linear mixing models. Since the number of endmembers/materials present at each mixed pixel is normally scanty compared with the number of total endmembers (the dimension of spectral library), the problem becomes sparse. This thesis introduces sparse hyperspectral unmixing methods for the linear mixing model through two different scenarios. In the first scenario, the library of spectral signatures is assumed to be known and the main problem is to find the minimum number of endmembers under a reasonable small approximation error. Mathematically, the corresponding problem is called the $\ell_0$-norm problem which is NP-hard problem. Our main study for the first part of thesis is to find more accurate and reliable approximations of $\ell_0$-norm term and propose sparse unmixing methods via such approximations. The resulting methods are shown considerable improvements to reconstruct the fractional abundances of endmembers in comparison with state-of-the-art methods such as having lower reconstruction errors. In the second part of the thesis, the first scenario (i.e., dictionary-aided semiblind unmixing scheme) will be generalized as the blind unmixing scenario that the library of spectral signatures is also estimated. We apply the nonnegative matrix factorization (NMF) method for proposing new unmixing methods due to its noticeable supports such as considering the nonnegativity constraints of two decomposed matrices. Furthermore, we introduce new cost functions through some statistical and physical features of spectral signatures of materials (SSoM) and hyperspectral pixels such as the collaborative property of hyperspectral pixels and the mathematical representation of the concentrated energy of SSoM for the first few subbands. Finally, we introduce sparse unmixing methods for the blind scenario and evaluate the efficiency of the proposed methods via simulations over synthetic and real hyperspectral data sets. The results illustrate considerable enhancements to estimate the spectral library of materials and their fractional abundances such as smaller values of spectral angle distance (SAD) and abundance angle distance (AAD) as well.

A fast non-smooth nonnegative matrix factorization for learning sparse representation

Nonnegative matrix factorization (NMF) is a hot topic in machine learning and data processing. Recently, a constrained version, non-smooth NMF (NsNMF), shows a great potential in learning meaningful sparse representation of the observed data. However, it suffers from a slow linear convergence rate, discouraging its applications to large-scale data representation. In this paper, a fast NsNMF (FNsNMF) algorithm is proposed to speed up NsNMF. In the proposed method, it first shows that the cost function of the derived sub-problem is convex and the corresponding gradient is Lipschitz continuous. Then, the optimization to this function is replaced by solving a proximal function, which is designed based on the Lipschitz constant and can be solved through utilizing a constructed fast convergent sequence. Due to the usage of the proximal function and its efficient optimization, our method can achieve a nonlinear convergence rate, much faster than NsNMF. Simulations in both computer generated data and the real-world data show the advantages of our algorithm over the compared methods.

Novel insights into the dynamics of green turtle fibropapillomatosis

Outbreaks of fibropapillomatosis (FP), a neoplastic infectious disease of marine turtles, have occurred worldwide since the 1980s. Its most likely aetiological agent is a virus, but disease expression depends on external factors, typically associated with altered environments. The scarcity of robust long-term data on disease prevalence has limited interpretations on the impacts of FP on turtle populations. Here we model the dynamics of FP at 2 green turtle foraging aggregations in Puerto Rico, through 18 yr of capture-mark-recapture data (1997−2014). We observed spatiotemporal variation in FP prevalence, potentially modulated via individual site-fidelity. FP ex pression was residency dependent, and FP-free individuals developed tumours after 1.8 ± 0.8 yr (mean ± SD) in the infected area. Recovery from the disease was likely, with complete tumour regression occurring in 2.7 ± 0.7 yr (mean ± SD). FP does not currently seem to be a major threat to marine turtle populations; however, disease prevalence is yet unknown in many areas. Systematic monitoring is highly advisable as human-induced stressors can lead to deviations in host− pathogen relationships and disease virulence. Finally, data collection should be standardized for a global assessment of FP dynamics and impacts.

Introdução à Matemática - Álgebra, Análise e Otimização

Este livro destina-se às/aos estudantes das várias disciplinas de introdução à matemática nos cursos superiores que incluem algum conteúdo matemático, mas sem prosseguirem para uma formação aprofundada nesta disciplina. Aprender é difícil. No caso particular da matemática essa dificuldade está principalmente na sua natureza estritamente abstrata, embora seja aumentada por um conjunto de factores materiais e culturais (que incluem a infame pergunta/desculpa "mas afinal, para que é que isto serve?" e más práticas como "deixar as matemáticas para o fim do curso"). Com este livro pretendemos ajudar a reduzir as dificuldades materiais e, portanto, contingentes mas desnecessárias que assombram a aprendizagem da Matemática. A nossa experiência como professores (em conjunto, mais de sessenta anos) precisamente para estes estudantes, nestes cursos, produziu uma atitude pragmática para este tipo específico de ensino: o conteúdo deve ser comunicado claramente, rigorosamente e em pequenas doses concretizadas abundantemente com exemplos e exercícios. Ao longo dos anos, conforme fomos refinando esta abordagem, também fomos observando os seus efeitos: os nossos estudantes aprendem melhor a matéria, de forma mais aprofundada e com melhores resultados. É esse pragmatismo que orienta o conteúdo da "Introdução à Matemática": a apresentação dos conceitos teóricos é sucinta, rigorosa, está claramente identificada, acompanhada por exemplos e complementada por inúmeros exercícios. Cada parte do livro corresponde a uma das grandes áreas da matemática normalmente presentes no ensino superior: a álgebra linear, a análise infinitesimal e a otimização.