Predictive significance of standardized uptake value parameters of FDG-PET in patients with non-small cell lung carcinoma

18F-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) is widely used to diagnose and stage non-small cell lung cancer (NSCLC). The aim of this retrospective study was to evaluate the predictive ability of different FDG standardized uptake values (SUVs) in 74 patients with newly diagnosed NSCLC. 18F-FDG PET/CT scans were performed and different SUV parameters (SUVmax, SUVavg, SUVT/L, and SUVT/A) obtained, and their relationship with clinical characteristics were investigated. Meanwhile, correlation and multiple stepwise regression analyses were performed to determine the primary predictor of SUVs for NSCLC. Age, gender, and tumor size significantly affected SUV parameters. The mean SUVs of squamous cell carcinoma were higher than those of adenocarcinoma. Poorly differentiated tumors exhibited higher SUVs than well-differentiated ones. Further analyses based on the pathologic type revealed that the SUVmax, SUVavg, and SUVT/L of poorly differentiated adenocarcinoma tumors were higher than those of moderately or well-differentiated tumors. Among these four SUV parameters, SUVT/Lwas the primary predictor for tumor differentiation. However, in adenocarcinoma, SUVmax was the determining factor for tumor differentiation. Our results showed that these four SUV parameters had predictive significance related to NSCLC tumor differentiation; SUVT/L appeared to be most useful overall, but SUVmax was the best index for adenocarcinoma tumor differentiation.

Stability and predictive ability of beta

The purpose of this paper is to examine the stability and predictive abilities of the beta coefficients of individual equities in the Finnish stock market. As beta is widely used in several areas of finance, including risk management, asset pricing and performance evaluation among others, it is important to understand its characteristics and find out whether its estimates can be trusted and utilized.

Comparing Predictive Accuracy of Real Estate Pricing Models: An Applied Study for the City of Montreal.

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O6-Methylguanine-DNA-Methyltransferase methylation: prevalence and predictive value in head and neck squamous cell carcinoma

Introduction: Le gène O6-méthylguanine-ADN méthyltransferase (MGMT) code pour une enzyme spécifique réparatrice de l’ADN qui protège les cellules de la toxicité des agents alkylants. Ainsi, l’activité du MGMT est un mécanisme majeur de résistance aux agents alkylants. Il a été démontré qu’une diminution de l’expression du gène MGMT par une hyperméthylation du promoteur résulte en une amélioration de la survie chez les patients avec certains types de tumeurs qui sont traitées avec des agents chimiothérapeuthique alkylants. Objectifs: Déterminer la prévalence de la méthylation du gène MGMT chez des patients avec des cancers épidermoïdes localement avancés de la sphère ORL traités avec chimioradiothérapie et évaluer l’impact de cette méthylation sur la survie. Méthodes: Sur 428 patients consécutifs, traités avec chimioradiothérapie à notre institution et suivis pour un période médiane de 37 mois, 199 spécimens chirurgicaux paraffinés ont été récupérés. L’ADN était extrait et modifié par le traitement au bisulfite. Une réaction en chaîne de la polymérase, spécifique à la méthylation était entreprise pour évaluer l’état de méthylation du promoteur du gène du MGMT. Les résultats de laboratoire étaient corrélés avec la réponse clinique. L’analyse statistique était exécutée à l’aide du test de Fisher pour les données catégoriques et à l’aide des courbes de Kaplan-Meier pour les échecs au traitement. Résultats : Des 199 extraits d’ADN initiaux, 173 (87%) étaient modifiés au bisulfite avec succès. Des ces spécimens modifiés, 71 (41%) ont démontré une hyperméthylation du MGMT. Pour les cas de méthylation et nonméthylation du MGMT, les caractéristiques des patients n’étaient pas significativement différentes. Les taux de réponse étaient 71 et 73% (p=NS) respectivement. Le contrôle locorégional était respectivement 87 et 77% (p=0.26), la survie sans maladie était 80 et 60% (p=0.38), la survie sans métastase à distance était 92 et 78% (p=0.08) et la survie globale était 64 et 62% (p=0.99) à 3 ans. Conclusions : L’état de méthylation du MGMT est fortement prévalent (41%) et semble avoir un possible impact bénéfique sur la survie quand la chimioradiothérapie est administrée aux patients avec des stades avancés de cancers tête et cou.

Predictive values of neurological examination, otoscopic examination and brainstem auditory evoked response (BAER) in calves with otisis media-interna

Présentement, le diagnostic d’otite moyenne-interne chez le veau est basé sur la présence de signes cliniques appropriés ainsi que les tests diagnostiques tels que la radiographie et la tomodensitométrie. L’objectif de cette étude prospective était d’évaluer les valeurs prédictives de l’examen neurologique, l’examen otoscopique et le test des potentiels auditifs évoqués (PAE) dans le diagnostic d’otite moyenne-interne chez le veau, en utilisant la tomodensitométrie comme test standard. Le deuxième objectif était de définir les valeurs de référence pour le PAE chez le veau normal et d’en décrire les anomalies chez des veaux atteints d’otite moyenne-interne. Dix-sept veaux de race Holstein entre 5-7 semaines d’âge ont été inclus. Tous les veaux ont eu un examen neurologique, un examen otoscopique et une évaluation des PAEs. Les veaux ont été tranquillisés avec de la xylazine intraveineuse (0,05-0,15mg/kg) pour la tomodensitométrie des bulles tympaniques afin d’évaluer pour la présence d’otite moyenne-interne. Selon les résultats de la tomodensitométrie, 11 des 17 veaux étaient atteints avec otite moyenne, 4 de façon unilatérale et 7 bilatéralement. Cinq ondes ont été identifiées de façon constante sur les tracés des PAEs des 6 veaux normaux. Les valeurs positives prédictives pour le PAE, l’examen neurologique et l’examen otoscopique étaient 94,7%, 91,7% et 66,7% respectivement. D’un point de vue clinique, le test le plus fiable dans le diagnostic d’otite moyenne-interne chez le veau est le PAE. Les anomalies ont été observées au PAE avant le développement des signes neurologiques chez certains veaux.

The predictive role of parenting practices and family functioning on the core symptoms of ADHD

Cette étude vise à examiner la relation entre les pratiques parentales utilisées durant la période de l'enfance et les dimensions principales du du trouble déficitaire de l'attention avec hyperactivité (TDAH) à l'adolescence, soit l’inattention, l’hyperactivité et l’impulsivité. Les pratiques spécifiques parentales (engagement, pratiques parentales appropriée, supervision, punitions corporelles, discipline appropriée, discipline sévère et incohérente, discipline verbale positive, félicitations et récompenses, et les attentes claires) et les aspects du fonctionnement familial (communication, résolution de problèmes, rôles dans la famille, sensibilité affective, engagement affectif, contrôle comportemental) ont été examinés par rapport à l'inattention et d'hyperactivité. Trente-six enfants de 6 à 9 ans et leurs parents ont participé à une étude longitudinale de 5 ans. Il y a un manque d'études longitudinales dans ce domaine et cette étude vise à combler cette lacune. Les résultats ne montrent pas de résultats significatifs dans la relation entre les pratiques parentales utilisées dans l'enfance et les symptômes principaux de l'hyperactivité et l'inattention à l'adolescence. Les études futures devraient se concentrer sur la relation entre la psychopathologie parentale et les principaux symptômes du TDAH de l'enfance à l'adolescence, ainsi que l'impact des pratiques parentales sur ces principaux symptômes.

PSWT Based Linear Predictive Coding and Development of a Parallel Multiple Subsequence Structure for DWT Computation

During 1990's the Wavelet Transform emerged as an important signal processing tool with potential applications in time-frequency analysis and non-stationary signal processing.Wavelets have gained popularity in broad range of disciplines like signal/image compression, medical diagnostics, boundary value problems, geophysical signal processing, statistical signal processing,pattern recognition,underwater acoustics etc.In 1993, G. Evangelista introduced the Pitch- synchronous Wavelet Transform, which is particularly suited for pseudo-periodic signal processing.The work presented in this thesis mainly concentrates on two interrelated topics in signal processing,viz. the Wavelet Transform based signal compression and the computation of Discrete Wavelet Transform. A new compression scheme is described in which the Pitch-Synchronous Wavelet Transform technique is combined with the popular linear Predictive Coding method for pseudo-periodic signal processing. Subsequently,A novel Parallel Multiple Subsequence structure is presented for the efficient computation of Wavelet Transform. Case studies also presented to highlight the potential applications.

Modified Block Adaptive Predictive Coder For Speech Processing

This thesis investigated the potential use of Linear Predictive Coding in speech communication applications. A Modified Block Adaptive Predictive Coder is developed, which reduces the computational burden and complexity without sacrificing the speech quality, as compared to the conventional adaptive predictive coding (APC) system. For this, changes in the evaluation methods have been evolved. This method is as different from the usual APC system in that the difference between the true and the predicted value is not transmitted. This allows the replacement of the high order predictor in the transmitter section of a predictive coding system, by a simple delay unit, which makes the transmitter quite simple. Also, the block length used in the processing of the speech signal is adjusted relative to the pitch period of the signal being processed rather than choosing a constant length as hitherto done by other researchers. The efficiency of the newly proposed coder has been supported with results of computer simulation using real speech data. Three methods for voiced/unvoiced/silent/transition classification have been presented. The first one is based on energy, zerocrossing rate and the periodicity of the waveform. The second method uses normalised correlation coefficient as the main parameter, while the third method utilizes a pitch-dependent correlation factor. The third algorithm which gives the minimum error probability has been chosen in a later chapter to design the modified coder The thesis also presents a comparazive study beh-cm the autocorrelation and the covariance methods used in the evaluaiicn of the predictor parameters. It has been proved that the azztocorrelation method is superior to the covariance method with respect to the filter stabf-it)‘ and also in an SNR sense, though the increase in gain is only small. The Modified Block Adaptive Coder applies a switching from pitch precitzion to spectrum prediction when the speech segment changes from a voiced or transition region to an unvoiced region. The experiments cont;-:ted in coding, transmission and simulation, used speech samples from .\£=_‘ajr2_1a:r1 and English phrases. Proposal for a speaker reecgnifion syste: and a phoneme identification system has also been outlized towards the end of the thesis.

Feature Extraction Methods Based on Linear Predictive Coding and Wavelet Packet Decomposition for Recognizing Spoken Words in Malayalam

Speech signals are one of the most important means of communication among the human beings. In this paper, a comparative study of two feature extraction techniques are carried out for recognizing speaker independent spoken isolated words. First one is a hybrid approach with Linear Predictive Coding (LPC) and Artificial Neural Networks (ANN) and the second method uses a combination of Wavelet Packet Decomposition (WPD) and Artificial Neural Networks. Voice signals are sampled directly from the microphone and then they are processed using these two techniques for extracting the features. Words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. Training, testing and pattern recognition are performed using Artificial Neural Networks. Back propagation method is used to train the ANN. The proposed method is implemented for 50 speakers uttering 20 isolated words each. Both the methods produce good recognition accuracy. But Wavelet Packet Decomposition is found to be more suitable for recognizing speech because of its multi-resolution characteristics and efficient time frequency localizations

Social network measures for "nosduocentered" networks, their predictive power on performance

Our purpose in this article is to define a network structure which is based on two egos instead of the egocentered (one ego) or the complete network (n egos). We describe the characteristics and properties for this kind of network which we call “nosduocentered network”, comparing it with complete and egocentered networks. The key point for this kind of network is that relations exist between the two main egos and all alters, but relations among others are not observed. After that, we use new social network measures adapted to the nosduocentered network, some of which are based on measures for complete networks such as degree, betweenness, closeness centrality or density, while some others are tailormade for nosduocentered networks. We specify three regression models to predict research performance of PhD students based on these social network measures for different networks such as advice, collaboration, emotional support and trust. Data used are from Slovenian PhD students and their s

Bullying and cyberbullying : Overlapping and predictive value of the co-occurrence

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Local model predictive control experiences with differential driven wheeled mobile robots

This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields

A Gain Scheduling Model Predictive Controller for Blood Glucose Control in Type 1 Diabetes

This paper presents a control strategy for blood glucose(BG) level regulation in type 1 diabetic patients. To design the controller, model-based predictive control scheme has been applied to a newly developed diabetic patient model. The controller is provided with a feedforward loop to improve meal compensation, a gain-scheduling scheme to account for different BG levels, and an asymmetric cost function to reduce hypoglycemic risk. A simulation environment that has been approved for testing of artificial pancreas control algorithms has been used to test the controller. The simulation results show a good controller performance in fasting conditions and meal disturbance rejection, and robustness against model–patient mismatch and errors in meal estimation