The goal of the work presented herein was to further our understanding of the rumen microbiota and microbiome of wild moose, and to use that understanding to improve other processes. The moose has adapted to eating a diet of woody browse, which is very high in fiber, but low in digestibility due to the complexity of the plant polysaccharides, and the presence of tannins, lignin, and other plant-secondary compounds. Therefore, it was hypothesized that the moose would host novel microorganisms that would be capable of a wide variety of enzymatic functions, such as improved fiber breakdown, metabolism of digestibility-reducing or toxic plant compounds, or production of functional metabolites, such as volatile fatty acids, biogenic amines, etc. The first aim, naturally, was to identify the microorganisms present in the rumen of moose, in this case, the bacteria, archaea, and protozoa. This was done using a variety of high-throughput techniques focusing on the SSU rRNA gene (see CHAPTERS 2-5). The second aim was to culture bacteria from the rumen of the moose in order to study their biochemical capabilities (see CHAPTERS 6-7). The final aim was to apply those cultured bacterial isolates to improve other systems. Specifically, bacteria from the rumen of the moose was introduced to young lambs in order to colonize the digestive tract, speed the pace of rumen development, and improve dietary efficiency (see CHAPTER 8).

The role of abnormal DNA methylation in the progression of disease is a growing area of research that relies upon the establishment of sound statistical methods. The common method for declaring there is differential methylation between two groups at a given CpG site, as summarized by the difference between proportions methylated db=b1-b2, has been through use of a Filtered Two Sample t-test, using the recommended filter of 0.17 (Bibikova et al., 2006b). In this dissertation, we performed a re-analysis of the data used in recommending the threshold by fitting a mixed-effects ANOVA model. It was determined that the 0.17 filter is not accurate and conjectured that application of a Filtered Two Sample t-test likely leads to loss of power. Further, the Two Sample t-test assumes that data arise from an underlying distribution encompassing the entire real number line, whereas b1 and b2 are constrained on the interval . Additionally, the imposition of a filter at a level signifying the minimum level of detectable difference to a Two Sample t-test likely reduces power for smaller but truly differentially methylated CpG sites. Therefore, we compared the Two Sample t-test and the Filtered Two Sample t-test, which are widely used but largely untested with respect to their performance, to three proposed methods. These three proposed methods are a Beta distribution test, a Likelihood ratio test, and a Bootstrap test, where each was designed to address distributional concerns present in the current testing methods. It was ultimately shown through simulations comparing Type I and Type II error rates that the (unfiltered) Two Sample t-test and the Beta distribution test performed comparatively well.

Les contaminations par les moisissures représentent un problème majeur au sein de l'industrie agroalimentaire, pharmaceutique, cosmétique, et dans le secteur médical. Actuellement, l'identification des champignons filamenteux est basée sur l'analyse des caractéristiques phénotypiques, nécessitant une expertise et pouvant manquer de précision, ou sur les méthodes moléculaires, coûteuses et fastidieuses. Dans ce contexte, l'objectif de cette étude a consisté à développer un protocole simple et standardisé à l'aide de la spectroscopie infrarouge à transformée de Fourier (IRTF) combinée à une méthode d'analyse chimiométrique, proposant une méthode alternative pour l'identification rapide des moisissures. Au total, 498 souches de champignons filamenteux (45 genres et 140 espèces) ont été analysées à l'aide d'un spectromètre IRTF à haut débit. L'analyse discriminante des moindres carrés partiels (PLS -DA), méthode chimiométrique supervisée, a été appliquée à chaque spectre dans les gammes spectrales 3200-2800 et 1800-800 cm-1. Différents modèles de calibration ont été construits à partir de 288 souches, ceci en cascade de la sous-division jusqu'à l'espèce en se basant sur la taxonomie actuelle. La prédiction des spectres en aveugle, obtenus à partir de 105 souches, au niveau du genre et de l'espèce est respectivement de 99,17 % et 92,3 %. La mise en place d'un score de prédiction et d'un seuil a permis de valider 80,22 % des résultats. L'implémentation d'une fonction de standardisation (SF) a permis d'augmenter le pourcentage de spectres bien prédits, acquis sur un autre instrument, de 72,15 % (sans fonction) à 89,13 %, validant la transférabilité de la méthode. Puisqu'une biomasse mycélienne suffisante peut être obtenue après 48h de culture et que la préparation des échantillons implique l'utilisation d'un protocole simple, la spectroscopie IRTF combinée à la PLS-DA apparaît comme une méthode rapide et peu coûteuse, ce qui la rend particulièrement attractive pour l'identification des champignons filamenteux au niveau industriel. Les résultats obtenus placent la spectroscopie IRTF parmi les méthodes analytiques prometteuses et avant-gardistes, possédant un haut pouvoir discriminant et une forte capacité d'identification, en comparaison avec les techniques conventionnelles. / Mold contaminants represent a major problem in various areas such as food and agriculture, pharmaceutics, cosmetics and health. Currently, molds identification is based either on phenotypic characteristics, requiring an expertise and can lack accuracy, or on molecular methods, which are quite expensive and fastidious. In this context, the objective was to develop a simple and standardized protocol using Fourier transform infrared (FTIR) spectroscopy combined with a chemometric analysis, allowing to implement an alternative method for rapid identification of molds. In total, 498 fungal strains (45 genera and 140 species) were analyzed using a high-throughput FTIR spectrometer. Partial Least Squares Discriminant Analysis (PLS-DA), a supervised chemometrics method, was applied to each spectrum in the spectral ranges 3200-2800 and 1800-800 cm-1 for the identification process. Using 288 strains, different calibration models were constructed in cascade and following the current taxonomy, from the subphylum to the species level. Blind prediction of spectra from 105 strains at the genus and species levels was achieved at 99.17 % and 92.3% respectively. The establishment of a prediction score and a threshold permitted to validate 80.22% of the obtained results. The implementation of a standardization function (SF) permitted to increase the percentage of well predicted spectra from strains analyzed using another instrument from 72.15% (without SF) to 89.13% and permitted to verify the transferability of the method. Since sufficient mycelial biomass can be obtained at 48h culture and sample preparation involved a simple protocol, FTIR spectroscopy combined with PLS-DA is a very rapid and cost effective method, which could be particularly attractive for the identification of moulds at the industrial level. The results obtained places FTIR spectroscopy among the avant-garde promising analytical approaches, with high discriminant power and identification capacity, compared to conventional techniques.

Les Archaea planctoniques contribuent de façon significative aux grands cycles biogéochimiques dans les écosystèmes aquatiques, néanmoins la structure des communautés actives ainsi que leurs variations saisonnières sont encore largement méconnues. En outre, la découverte de l’implication des Archaea dans le cycle de l’azote (Ammonia Oxidizing Archaea ou AOA), plus particulièrement dans le processus de nitrification a considérablement modifié la perception d’un processus autotrophe réalisé uniquement par des bactéries (Ammonia Oxidizing Bacteria ou AOB). Dans les écosystèmes marins, la large distribution des AOA suggère que ces microorganismes joueraient un rôle prépondérant dans le cycle de l’azote néanmoins, ces observations ne sont pas généralisables à l’ensemble des écosystèmes aquatiques en raison de leur grande diversité et/ou d'un manque d'informations et d’études sur certains d'entre eux. Ainsi, les objectifs de ce projet étaient i) d’étudier la structure spatiale et temporelle des communautés d’Archaea actives dans des écosystèmes aquatiques contrastés en termes d’apports anthropiques et/ou de gradients de salinité (lac, estuaire, milieu côtier) ; ii) de déterminer la contribution relative des Archaea au processus d’oxydation de l’ammonium, en comparaison avec celle des bactéries ; et iii) de mieux comprendre les paramètres environnementaux qui pourraient déterminer l’établissement des communautés d’AOA ou d’AOB. / Aquatic Archaea are important players among microbial plankton and significantly contribute to biogeochemical cycles, especially nitrogen, but details regarding their community structure and seasonal activity and dynamics remain largely unexplored. In marine ecosystems, the widespread distribution of Ammonia Oxidizing Archaea (AOA) suggests that they probably play a major role in nutrients cycling. However, we cannot generalize these observations to all aquatic ecosystems because of their high diversity and/or a lack of information and studies on these organisms for some of these ecosystems. More precisely, lacustrine and coastal ecosystems were less studied while they are potentially subjected to strong anthropogenic impacts. Moreover, notable differences in terms of diversity and activity between marine and freshwater communities can be expected, considering the specific environmental parameters of each ecosystem. The objectives of this thesis were: i) to study the archaeal community structure across a temporal scale and assess the diversity of archaeal communities and AOA in diverse aquatic ecosystems along anthropogenic and/or salinity gradient (lacustrine, estuarine and coastal ecosystems); ii) to determine their relative contribution in ammonia oxidation, compared to Ammonia Oxidizing Bacteria (AOB) by looking at their spatial and temporal distribution and activity, and iii) to explore more precisely the environmental parameters that could drive AOA and/or AOB establishment.

Coccolithophores are biogeochemically important marine algae that interact with the carbon cycle through photosynthesis (CO2 sink), calcification (CO2 source) and burial of carbon into oceanic sediments. The group is considered susceptible to the ongoing climate perturbations, in particular to ocean acidification, temperature increase and nutrient limitation. The aim of this thesis was to investigate the adaptation of coccolithophores to environmental change, with the focus on temperature stress and nutrient limitation. The research was conducted in frame of three approaches: experiments testing the physiological response of coccolithophore species Helicosphaera carteri and Coccolithus pelagicus to phosphorus limitation, field studies on coccolithophore life-cycles with a method comparison and an investigation of the phenotypic evolution of the coccolithophore genus Helicosphaera over the past 15 Ma. Experimental results show that the physiology and morphology of large coccolithophores are sensitive to phosphorus limitation, and that the adaptation to low-nutrient conditions can lead to a decrease in calcification rates. Field studies have contributed to our understanding of coccolithophore life cycles, revealing complex ecological patterns within the Mediterranean community which are seemingly regulated by seasonal, temperature-driven environment changes. In addition, the high-throughput sequencing (HTS) molecular method was shown to provide overall good representation of coccolithophore community composition. Finally, the study on Helicosphaera evolution showed that adaptation to decreasing CO2 in higher latitudes involved cell and coccolith size decrease, whereas the adaptation in tropical ecosystems also included a physiological decrease in calcification rates in response to nutrient limitation. This thesis advanced our understanding of coccolithophore adaptive strategies and will improve our predictions on the fate of the group under ongoing climate change.

In this dissertation, power allocation approaches considering path loss, shadowing, and Rayleigh and Nakagami-m fading are proposed. The goal is to improve power consumption, and energy and throughput efficiency based on user target signal to interference plus noise ratio (SINR) requirements and an outage probability threshold. First, using the moment generating function (MGF), the exact outage probability over Rayleigh and Nakagami-m fading channels is derived. Then upper and lower bounds on the outage probability are derived using the Weierstrass, Bernoulli and exponential inequalities. Second, the problem of minimizing the user power subject to outage probability and user target SINR constraints is considered. The corresponding power allocation problems are solved using Perron-Frobenius theory and geometric programming (GP). A GP problem can be transformed into a nonlinear convex optimization problem using variable substitution and then solved globally and efficiently by interior point methods. Then, power allocation problems for throughput maximization and energy efficiency are proposed. As these problems are in a convex fractional programming form, parametric transformation is used to convert the original problems into subtractive optimization problems which can be solved iteratively. Simulation results are presented which show that the proposed approaches are better than existing schemes in terms of power consumption, throughput, energy efficiency and outage probability. Prioritized cell association and power allocation (CAPA) to solve the load balancing issue in heterogeneous networks (HetNets) is also considered in this dissertation. A Hetnet is a group of macrocell base stations (MBSs) underlaid by a diverse set of small cell base stations (SBSs) such as microcells, picocells and femtocells. These networks are considered to be a good solution to enhance network capacity, improve network coverage, and reduce power consumption. However, HetNets are limited by the disparity of power levels in the different tiers. Conventional cell association approaches cause MBS overloading, SBS underutilization, excessive user interference and wasted resources. Satisfying priority user (PU) requirements while maximizing the number of normal users (NUs) has not been considered in existing power allocation algorithms. Two stage CAPA optimization is proposed to address the prioritized cell association and power allocation problem. The first stage is employed by PUs and NUs and the second stage is employed by BSs. First, the product of the channel access likelihood (CAL) and channel gain to interference plus noise ratio (GINR) is considered for PU cell association while network utility is considered for NU cell association. Here, CAL is defined as the reciprocal of the BS load. In CAL and GINR cell association, PUs are associated with the BSs that provide the maximum product of CAL and GINR. This implies that PUs connect to BSs with a low number of users and good channel conditions. NUs are connected to BSs so that the network utility is maximized, and this is achieved using an iterative algorithm. Second, prioritized power allocation is used to reduce power consumption and satisfy as many NUs with their target SINRs as possible while ensuring that PU requirements are satisfied. Performance results are presented which show that the proposed schemes provide fair and efficient solutions which reduce power consumption and have faster convergence than conventional CAPA schemes. / Graduate

Cross-coupling reactions, where a transition metal catalyst facilitates the formation of a new carbon-carbon or carbon-heteroatom bond between two coupling partners, has become one of the most widely used, reliable, and robust family of transformations for the construction of molecules. The Nobel Prize was awarded to pioneers in this field who primarily used aryl iodides, bromides, and triflates as electrophilic coupling partners. The expansion of the reaction scope to non-traditional electrophiles is an ongoing challenge to enable an even greater number of useful products to be made from simple starting materials. The major goal of this thesis research is to improve and expand upon this field by using esters as electrophiles via the activation of the strong C(acyl)−O bond. Esters are particularly robust in comparison to other carboxylic acid derivatives used in cross-coupling reactions. Success on the activation of such inert functional group using catalysis has both fundamental and practical value. By discovering new reaction modes of this abundant functional group, synthetic routes to access novel or industrially important molecules can be improved. Chapter 1 of this thesis describes a literature overview of what has been accomplished in the field of cross coupling reactions using carboxylic acid derivatives as electrophilic coupling partners. Chapter 2 discloses the first palladium Suzuki-Miyaura couplings of phenyl esters to produce ketones. The method is efficient and robust, giving good yields of useful products. The reaction is proposed to proceed via an oxidative addition to the strong C(acyl)−O bond of the ester. In contrast to previous efforts in this field that use traditional catalysts such as Pd(PPh3)4, the developed reaction requires use of an electron-rich, bulky N-heterocyclic carbene ligand, which facilitates the strong bond activation. Furthermore, a palladium-catalyzed cross-coupling between aryl esters and anilines is reported, enabling access to diverse amides. The reaction takes place via a similar activation of the C−O bond by oxidative addition with a Pd−NHC complex, which enables the use of relatively non-nucleophilic anilines that otherwise require stoichiometric activation with strong bases to react. Chapter 3 discloses a nickel-catalyzed amide bond formation using unactivated and abundant esters. In this transformation, an accessible nickel catalyst can facilitate the activation of diverse aliphatic and aromatic esters to enable direct amide bond formation with amines as nucleophiles. No stoichiometric base, acid, or other activating agent is needed, providing exceptional functional group tolerance and producing only methanol as a by-product. This reaction is of both fundamental and practical importance because it is the first to demonstrate that simple conditions can enable Ni to cleave the C–O bond of an ester to make an oxidative addition product, which can be subsequently coupled with amines. This discovery contrasts industrially-common and wasteful methods that still require stoichiometric activating agents or multistep synthesis. Chapter 4 describes the evaluation of different types of cross-coupling reactions using methyl esters as electrophilic coupling partner. A high-throughput screening technique has been applied to this project. A combination between specific ligands, known by their efficiency to activate strong C−O bonds, and literature-based conditions has been designed for the chosen transformations. Using this strategy, two promising hits have been obtained using the same NHC ligand: a decarbonylative Suzuki-Miyaura and a decarbonylative borylation reaction.

A enorme quantidade de dados que vem sendo gerada por tecnologias modernas de biologia representam um grande desafio para áreas como a bioinformática. Há uma série de programas disponíveis para a análise destes dados, mas que nem sempre são compreendidos o suficiente para serem corretamente aplicados, ou ainda, há problemas que requerem o desenvolvimento de novas soluções. Neste trabalho, nós apresentamos a análise de dados de duas das principais fontes de dados em larga escala: microarrays e sequenciamento. Na primeira, avaliamos se a estatística do método Rank Products (RP) é adequada para a identificação de genes diferencialmente expressos em estudos de doenças complexas, cujo uma das características é a heterogeneidade genética entre indivíduos com o mesmo fenótipo. Na segunda, desenvolvemos uma ferramenta chamada hunT para buscar por genes alvos do fator de transcrição T - um importante marcador de mesoderma com papel chave no desenvolvimento de vertebrados -, através da identificação de sítios de ligação para o T em suas sequências reguladoras. O desempenho do RP foi testado usando dados simulados e dados reais de um estudo de fissura lábio-palatina não-sindrômica, de autismo e também de um estudo que avalia o efeito da privação do sono em humanos. Nossos resultados mostraram que o RP é uma solução eficiente para detectar genes consistentemente desregulados em somente um subgrupo de pacientes, que esta habilidade é mantida com poucas amostras, mas que o seu desempenho é prejudicado quando são analisados poucos genes. Obtivemos fortes evidências biológicas da eficiência do método nos estudos com dados reais através da identificação de genes e vias previamente associados às doenças e da validação de novos genes candidatos através da técnica de PCR quantitativo em tempo real. Já o programa hunT identificou 4.602 genes de camundongo com o sítio de ligação para o domínio do T, sendo alguns deles já demonstrados experimentalmente. Identificamos 32 destes genes com expressão alterada em um estudo onde avaliamos o transcriptoma da diferenciação in vitro de células tronco embrionárias de camundongo para mesoderma, sugerindo a participação destes genes neste processo sendo regulados pelo T / The large amount of data generated by modern technologies of biology provides a big challenge for areas such as bioinformatics. In order to analyze these data there are several computer programs available; however these are not always well understood enough to be correctly applied. Moreover, there are problems that require the development of new solutions. In this work, we present the data analysis of two main high-throughput data sources: microarrays and sequencing. Firstly, we evaluated whether the statistic of Rank Products method (RP) is suitable for the identification of differentially expressed genes in studies of complex diseases, which are characterized by the vast genetic heterogeneity among the individuals affected. Secondly, we developed a tool named hunT to search for target genes of T transcription factor - an important mesodermal marker that plays a key role in the vertebrate development -, by identifying binding sites for T in their regulatory sequences. The RP performance was tested using both simulated and real data from three different studies: non-syndromic cleft lip and palate, autism and sleep deprivation effect in Humans. Our results have shown that RP is an effective solution for the identification of consistently deregulated genes in a subgroup of patients, this ability is maintained even with few samples, however its performance is impaired when only few genes are analyzed. We have obtained strong biological of effectiveness of the method in the studies with real data by not only identifying genes and pathways previously associated with diseases but also corroborating the behavior of novel candidate genes with the real-time PCR technique. The hunT program has identified 4,602 mouse genes containing the binding site for the T domain, some of which have already been demonstrated experimentally. We identified 32 of these genes with altered expression in a study which evaluated the transcriptome of in vitro differentiation of mouse embryonic stem cells to mesoderm, suggesting the involvement of these genes in this process regulated by T

Thesis advisor: Charles S. Hoffman / In this thesis, I describe the development of a screening platform for detecting PDE8A inhibitors using the cAMP-dependent glucose sensing pathway of the fission yeast Schizosaccharomyces pombe, which led us to discover several PDE8A selective inhibitors. In this system, the only PDE of the fission yeast is replaced with mammalian PDE8A1 in strains that have been engineered such that PDE inhibition is required to allow cell growth. Using this system, I screened 56 compounds obtained from PDE4 and PDE7 high throughput screens (HTSs) and identified a PDE4-PDE8 dual specificity inhibitor. Using this as a positive control, I developed a robust high-throughput screen (HTS) for PDE8A inhibitors and screened 240,267 compounds at the Harvard Medical School ICCB Screening Facility. Approximately 0.2 % of the screened compounds were potential PDE8A inhibitors with 0.03% displaying significant potency. Secondary assays of 367 of the most effective compounds against strains expressing PDE8A (both full length and catalytic domain), PDE4A and PDE7A or PDE7B led to the selection of structurally diverse compounds for further testing. To profile the selectivity of twenty-eight of these compounds, dose response assays were conducted using 16 yeast strains that express different PDE isoforms (representing all PDE families with the exception of the PDE6 family). These assays identified compounds with different patterns of inhibition, including structurally-distinct PDE8A-specific inhibitors. By evaluating the effects of these compounds for steroid production in mouse Leydig cells, biologically active compounds that can elevate steroid production were identified. / Thesis (PhD) — Boston College, 2011. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Biology.

Direct Analysis in Real Time (DART) ionization/mass spectrometry allows for the high throughput analysis of a wide range of materials including but not limited to: solids, liquids, powders, tablets, and plant materials. The ability to detect cocaine was established in a reproducible manner with the use of a DART ionization source (IonSense Inc., Saugus, MA) interfaced to a modified single quadrupole mass spectrometer. Development of a methodology for the detection of cocaine within contrived street quality drug mixtures involved the optimization of the ionization source, sample introduction mechanism, ion guide, and mass analysis parameters. An analytical method was created that utilized ionized helium carrier gas heated to 300°C and an automated sample introduction apparatus consisting of a Linear Rail Enclosure that holds consumable QuickStrip^TM sample cards. Ionized molecules were then fragmented by manipulation of voltage levels within the ion guide to gain more structural information prior to detection by a single quadrupole mass spectrometer. Cocaine was detected by the modified DART/MS analytical platform and gave two peaks within the mass spectrum at m/z 304 and 182. Optimization of in-source fragmentation by manual adjustment of the skimmer focus voltage allowed for the reproducible fragmentation of cocaine and the ability to increase or decrease the amount of fragmentation seen between the two peaks detected for cocaine. With the use of fragmentation, this analytical platform can be classified as a Category A technique as defined by the Scientific Working Group for the Analysis of Seized Drugs. The robust detection of cocaine was demonstrated for reference samples at concentrations as low as 10 ng/μL (50 ng) with high signal abundance greater than ten times the signal to noise ratio. Furthermore, the detection of cocaine at 10 ng/μL was demonstrated for multi component mixtures of up to 14 additional components containing common adulterants and diluents found within street quality samples. In total, 25 common excipients were tested using the same method parameters as optimized for cocaine analysis. Of these 25 excipients tested, five were not detected in positive ion mode (one could be detected in negative ion mode). Of the twenty excipients that could be detected by mass spectrometry, two pairs of excipients (levamisole/tetramisole and creatine/creatinine) could not be differentiated from each other. There were no excipients tested that had equivalent m/z values as those of cocaine. Experimentation into the effects of various excipients at multiple concentrations on the abundance of the two cocaine peaks was performed. Regardless of excipient amount (up to 10 times more concentrated than cocaine) and the number of components (up to 15 total components) the ratio of abundance between the m/z 304 to 182 peaks did not vary greater than 22% relative standard deviation. A match criteria protocol was developed for the ability of an analyst to confirm the presence of cocaine within unknown forensic case samples that have previously tested positive for the presumptive identification of cocaine. The identification of cocaine was based on various factors such as the signal to noise ratio at m/z 304 and 182, the ratio of abundance between those two peaks as well as positive and negative controls. This match criteria protocol was utilized for 25 double blind mock forensic casework samples was performed. Determination for the presence of cocaine within these unknown samples gave an analyst error rate of 0%, with no false positives or false negatives predicted. To further aid human interpretation and identification of compounds within mixtures, the advanced chemometric software, Analyze IQ, was utilized. Development of predictive classification models using a combination of pre-processing steps, principle component analysis and machine learning techniques was achieved. Models were built using 381 unique samples for the purposes of identifying the presence of cocaine within unknown samples. Of all methods available within the Analyze IQ software, the optimization of a model using principle component analysis with support vector machine regression with a radial basis function kernel yielded an initial error rate of 0% for 72 samples tested. Furthermore, of the samples tested against the model, 20 samples were comprised of excipients that were not incorporated into the initial model development process. The inclusion of these samples (10 spiked with cocaine, 10 absent of cocaine), shows that predictive modeling based software can provide an accurate, robust, and evolving approach to the identification of cocaine within sample compositions that have not previously been tested and stored in a database of known reference samples. Predictive modeling has advantages over current mass spectral libraries, which are limited to the identification of pure compounds. To further test the abilities of predictive models, optimized machine learning models were applied to 25 double blind mock forensic casework samples. The predictive modeling error rate was identical to the human interpretation rate for the double blind mock casework samples with a 0% error rate. Using the DART/MS analytical platform, 25 mock forensic casework samples along with positive and negative controls were analyzed and identified for the presence of cocaine within 30 minutes. On the order of 15 to 30 times faster than modern GC/MS and LC/MS methods, the ability to analyze and identify samples faster would allow for an increase in samples being processed on a daily basis and allow for the reduction of case backlogs that currently plague controlled substances sections of forensic science laboratories throughout the United States.