A third generation regimen VACOP-B with or without adjuvant radiotherapy for aggressive localized non-Hodgkin's lymphoma: report from the Italian Non-Hodgkin's Lymphoma Co-operative Study Group

The objective of this multicenter prospective study was to determine the clinical efficacy and toxicity of a polychemotherapeutic third generation regimen, VACOP-B, with or without radiotherapy as front-line therapy in aggressive localized non-Hodgkin's lymphoma. Ninety-three adult patients (47 males and 46 females, median age 45 years) with aggressive localized non-Hodgkin's lymphoma, 43 in stage I and 50 in stage II (non-bulky), were included in the study. Stage I patients received VACOP-B for 6 weeks plus involved field radiotherapy and stage II patients received 12 weeks VACOP-B plus involved field radiotherapy on residual masses. Eighty-six (92.5%) achieved complete remission and 4 (4.3%) partial remission. Three patients (3.2%) were primarily resistant. Ten-year probability of survival, progression-free survival and disease-free survival were 87.3, 79.9 and 83.9%, respectively. Eighty-four patients are surviving at a median observation time of 57 months (range: 6-126). Statistical analysis showed no difference between stages I and II in terms of response, ten-year probability of survival, progression-free survival or disease-free survival. Side effects and toxicity were negligible and were similar in the two patient groups. The results of this prospective study suggest that 6 weeks of VACOP-B treatment plus radiotherapy may be the therapy of choice in stage I aggressive non-Hodgkin's lymphoma. Twelve weeks of VACOP-B treatment with or without radiotherapy was shown to be effective and feasible for stage II. These observations need to be confirmed by a phase III study comparing first and third generation protocols in stage I-II aggressive non-Hodgkin's lymphoma.

A semi-automatic computerized method to measure baroreflex-mediated heart rate responses that reduces interobserver variability

Arterial baroreflex sensitivity estimated by pharmacological impulse stimuli depends on intrinsic signal variability and usually a subjective choice of blood pressure (BP) and heart rate (HR) values. We propose a semi-automatic method to estimate cardiovascular reflex sensitivity to bolus infusions of phenylephrine and nitroprusside. Beat-to-beat BP and HR time series for male Wistar rats (N = 13) were obtained from the digitized signal (sample frequency = 2 kHz) and analyzed by the proposed method (PRM) developed in Matlab language. In the PRM, time series were low-pass filtered with zero-phase distortion (3rd order Butterworth used in the forward and reverse direction) and presented graphically, and parameters were selected interactively. Differences between basal mean values and peak BP (deltaBP) and HR (deltaHR) values after drug infusions were used to calculate baroreflex sensitivity indexes, defined as the deltaHR/deltaBP ratio. The PRM was compared to the method traditionally (TDM) employed by seven independent observers using files for reflex bradycardia (N = 43) and tachycardia (N = 61). Agreement was assessed by Bland and Altman plots. Dispersion among users, measured as the standard deviation, was higher for TDM for reflex bradycardia (0.60 ± 0.46 vs 0.21 ± 0.26 bpm/mmHg for PRM, P < 0.001) and tachycardia (0.83 ± 0.62 vs 0.28 ± 0.28 bpm/mmHg for PRM, P < 0.001). The advantage of the present method is related to its objectivity, since the routine automatically calculates the desired parameters according to previous software instructions. This is an objective, robust and easy-to-use tool for cardiovascular reflex studies.

Automatic image-based identification of Saimaa ringed seals

The Saimaa ringed seal is one of the most endangered seals in the world. It is a symbol of Lake Saimaa and a lot of effort have been applied to save it. Traditional methods of seal monitoring include capturing the animals and installing sensors on their bodies. These invasive methods for identifying can be painful and affect the behavior of the animals. Automatic identification of seals using computer vision provides a more humane method for the monitoring. This Master's thesis focuses on automatic image-based identification of the Saimaa ringed seals. This consists of detection and segmentation of a seal in an image, analysis of its ring patterns, and identification of the detected seal based on the features of the ring patterns. The proposed algorithm is evaluated with a dataset of 131 individual seals. Based on the experiments with 363 images, 81\% of the images were successfully segmented automatically. Furthermore, a new approach for interactive identification of Saimaa ringed seals is proposed. The results of this research are a starting point for future research in the topic of seal photo-identification.

Automatic recognition of fish from video sequences

The problem of automatic recognition of the fish from the video sequences is discussed in this Master’s Thesis. This is a very urgent issue for many organizations engaged in fish farming in Finland and Russia because the process of automation control and counting of individual species is turning point in the industry. The difficulties and the specific features of the problem have been identified in order to find a solution and propose some recommendations for the components of the automated fish recognition system. Methods such as background subtraction, Kalman filtering and Viola-Jones method were implemented during this work for detection, tracking and estimation of fish parameters. Both the results of the experiments and the choice of the appropriate methods strongly depend on the quality and the type of a video which is used as an input data. Practical experiments have demonstrated that not all methods can produce good results for real data, whereas on synthetic data they operate satisfactorily.

Evidence for divided automatic attention

A long-standing debate in the literature is whether attention can form two or more independent spatial foci in addition to the well-known unique spatial focus. There is evidence that voluntary visual attention divides in space. The possibility that this also occurs for automatic visual attention was investigated here. Thirty-six female volunteers were tested. In each trial, a prime stimulus was presented in the left or right visual hemifield. This stimulus was characterized by the blinking of a superior, middle or inferior ring, the blinking of all these rings, or the blinking of the superior and inferior rings. A target stimulus to which the volunteer should respond with the same side hand or a target stimulus to which she should not respond was presented 100 ms later in a primed location, a location between two primed locations or a location in the contralateral hemifield. Reaction time to the positive target stimulus in a primed location was consistently shorter than reaction time in the horizontally corresponding contralateral location. This attentional effect was significantly smaller or absent when the positive target stimulus appeared in the middle location after the double prime stimulus. These results suggest that automatic visual attention can focus on two separate locations simultaneously, to some extent sparing the region in between.

Method for automatic detection of wheezing in lung sounds

The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data.

Pharmacogenetic polymorphisms in Brazilian-born, first-generation Japanese descendants

Brazil hosts the largest Japanese community outside Japan, estimated at 1.5 million individuals, one third of whom are first-generation, Brazilian-born with native Japanese parents. This large community provides a unique opportunity for comparative studies of the distribution of pharmacogenetic polymorphisms in native Japanese versus their Brazilian-born descendants. Functional polymorphisms in genes that modulate drug disposition (CYP2C9, CYP2C19 and GSTM3) or response (VKORC1) and that differ significantly in frequency in native Japanese versus Brazilians with no Japanese ancestry were selected for the present study. Healthy subjects (200 native Japanese and 126 first-generation Japanese descendants) living in agricultural colonies were enrolled. Individual DNA was genotyped using RFLP (GSTM3*A/B) or TaqMan Detection System assays (CYP2C9*2 and *3; CYP2C19*2 and *3; VKORC1 3673G>A, 5808T>G, 6853G>C, and 9041G>A). No difference was detected in the frequency of these pharmacogenetic polymorphisms between native Japanese and first-generation Japanese descendants. In contrast, significant differences in the frequency of each polymorphism were observed between native or first-generation Japanese and Brazilians with no Japanese ancestry. The VKORC1 3673G>A, 6853G>C and 9041G>A single nucleotide polymorphisms were in linkage disequilibrium in both native and first-generation Japanese living in Brazil. The striking similarity in the frequency of clinically relevant pharmacogenetic polymorphisms between Brazilian-born Japanese descendants and native Japanese suggests that the former may be recruited for clinical trials designed to generate bridging data for the Japanese population in the context of the International Conference on Harmonization.

Manual and semi-automatic quantification of in vivo ¹H-MRS data for the classification of human primary brain tumors

In vivo proton magnetic resonance spectroscopy (¹H-MRS) is a technique capable of assessing biochemical content and pathways in normal and pathological tissue. In the brain, ¹H-MRS complements the information given by magnetic resonance images. The main goal of the present study was to assess the accuracy of ¹H-MRS for the classification of brain tumors in a pilot study comparing results obtained by manual and semi-automatic quantification of metabolites. In vivo single-voxel ¹H-MRS was performed in 24 control subjects and 26 patients with brain neoplasms that included meningiomas, high-grade neuroglial tumors and pilocytic astrocytomas. Seven metabolite groups (lactate, lipids, N-acetyl-aspartate, glutamate and glutamine group, total creatine, total choline, myo-inositol) were evaluated in all spectra by two methods: a manual one consisting of integration of manually defined peak areas, and the advanced method for accurate, robust and efficient spectral fitting (AMARES), a semi-automatic quantification method implemented in the jMRUI software. Statistical methods included discriminant analysis and the leave-one-out cross-validation method. Both manual and semi-automatic analyses detected differences in metabolite content between tumor groups and controls (P < 0.005). The classification accuracy obtained with the manual method was 75% for high-grade neuroglial tumors, 55% for meningiomas and 56% for pilocytic astrocytomas, while for the semi-automatic method it was 78, 70, and 98%, respectively. Both methods classified all control subjects correctly. The study demonstrated that ¹H-MRS accurately differentiated normal from tumoral brain tissue and confirmed the superiority of the semi-automatic quantification method.

Semi-automatic measurement of visual verticality perception in humans reveals a new category of visual field dependency

Previous assessment of verticality by means of rod and rod and frame tests indicated that human subjects can be more (field dependent) or less (field independent) influenced by a frame placed around a tilted rod. In the present study we propose a new approach to these tests. The judgment of visual verticality (rod test) was evaluated in 50 young subjects (28 males, ranging in age from 20 to 27 years) by randomly projecting a luminous rod tilted between -18 and +18° (negative values indicating left tilts) onto a tangent screen. In the rod and frame test the rod was displayed within a luminous fixed frame tilted at +18 or -18°. Subjects were instructed to verbally indicate the rod’s inclination direction (forced choice). Visual dependency was estimated by means of a Visual Index calculated from rod and rod and frame test values. Based on this index, volunteers were classified as field dependent, intermediate and field independent. A fourth category was created within the field-independent subjects for whom the amount of correct guesses in the rod and frame test exceeded that of the rod test, thus indicating improved performance when a surrounding frame was present. In conclusion, the combined use of subjective visual vertical and the rod and frame test provides a specific and reliable form of evaluation of verticality in healthy subjects and might be of use to probe changes in brain function after central or peripheral lesions.

Alternative pathways for angiotensin II generation in the cardiovascular system

The classical renin-angiotensin system (RAS) consists of enzymes and peptides that regulate blood pressure and electrolyte and fluid homeostasis. Angiotensin II (Ang II) is one of the most important and extensively studied components of the RAS. The beneficial effects of angiotensin converting enzyme (ACE) inhibitors in the treatment of hypertension and heart failure, among other diseases, are well known. However, it has been reported that patients chronically treated with effective doses of these inhibitors do not show suppression of Ang II formation, suggesting the involvement of pathways alternative to ACE in the generation of Ang II. Moreover, the finding that the concentration of Ang II is preserved in the kidney, heart and lungs of mice with an ACE deletion indicates the important role of alternative pathways under basal conditions to maintain the levels of Ang II. Our group has characterized the serine protease elastase-2 as an alternative pathway for Ang II generation from Ang I in rats. A role for elastase-2 in the cardiovascular system was suggested by studies performed in heart and conductance and resistance vessels of normotensive and spontaneously hypertensive rats. This mini-review will highlight the pharmacological aspects of the RAS, emphasizing the role of elastase-2, an alternative pathway for Ang II generation.

Berberine induces apoptosis via ROS generation in PANC-1 and MIA-PaCa2 pancreatic cell lines

Pancreatic cancer is the fourth leading cause of cancer death. Gemcitabine is widely used as a chemotherapeutic agent for the treatment of pancreatic cancer, but the prognosis is still poor. Berberine, an isoquinoline alkaloid extracted from a variety of natural herbs, possesses a variety of pharmacological properties including anticancer effects. In this study, we investigated the anticancer effects of berberine and compared its use with that of gemcitabine in the pancreatic cancer cell lines PANC-1 and MIA-PaCa2. Berberine inhibited cell growth in a dose-dependent manner by inducing cell cycle arrest and apoptosis. After berberine treatment, the G1 phase of PANC-1 cells increased by 10% compared to control cells, and the G1 phase of MIA-PaCa2 cells was increased by 2%. Whereas gemcitabine exerts antiproliferation effects through S-phase arrest, our results showed that berberine inhibited proliferation by inducing G1-phase arrest. Berberine-induced apoptosis of PANC-1 and MIA-PaCa2 cells increased by 7 and 2% compared to control cells, respectively. Notably, berberine had a greater apoptotic effect in PANC-1 cells than gemcitabine. Upon treatment of PANC-1 and MIA-PaCa2 with berberine at a half-maximal inhibitory concentration (IC50), apoptosis was induced by a mechanism that involved the production of reactive oxygen species (ROS) rather than caspase 3/7 activation. Our findings showed that berberine had anti-cancer effects and may be an effective drug for pancreatic cancer chemotherapy.

Sentence Compression with Supervised Machine Learning

The subject of the thesis is automatic sentence compression with machine learning, so that the compressed sentences remain both grammatical and retain their essential meaning. There are multiple possible uses for the compression of natural language sentences. In this thesis the focus is generation of television program subtitles, which often are compressed version of the original script of the program. The main part of the thesis consists of machine learning experiments for automatic sentence compression using different approaches to the problem. The machine learning methods used for this work are linear-chain conditional random fields and support vector machines. Also we take a look which automatic text analysis methods provide useful features for the task. The data used for machine learning is supplied by Lingsoft Inc. and consists of subtitles in both compressed an uncompressed form. The models are compared to a baseline system and comparisons are made both automatically and also using human evaluation, because of the potentially subjective nature of the output. The best result is achieved using a CRF - sequence classification using a rich feature set. All text analysis methods help classification and most useful method is morphological analysis. Tutkielman aihe on suomenkielisten lauseiden automaattinen tiivistäminen koneellisesti, niin että lyhennetyt lauseet säilyttävät olennaisen informaationsa ja pysyvät kieliopillisina. Luonnollisen kielen lauseiden tiivistämiselle on monta käyttötarkoitusta, mutta tässä tutkielmassa aihetta lähestytään television ohjelmien tekstittämisen kautta, johon käytännössä kuuluu alkuperäisen tekstin lyhentäminen televisioruudulle paremmin sopivaksi. Tutkielmassa kokeillaan erilaisia koneoppimismenetelmiä tekstin automaatiseen lyhentämiseen ja tarkastellaan miten hyvin erilaiset luonnollisen kielen analyysimenetelmät tuottavat informaatiota, joka auttaa näitä menetelmiä lyhentämään lauseita. Lisäksi tarkastellaan minkälainen lähestymistapa tuottaa parhaan lopputuloksen. Käytetyt koneoppimismenetelmät ovat tukivektorikone ja lineaarisen sekvenssin mallinen CRF. Koneoppimisen tukena käytetään tekstityksiä niiden eri käsittelyvaiheissa, jotka on saatu Lingsoft OY:ltä. Luotuja malleja vertaillaan Lopulta mallien lopputuloksia evaluoidaan automaattisesti ja koska teksti lopputuksena on jossain määrin subjektiivinen myös ihmisarviointiin perustuen. Vertailukohtana toimii kirjallisuudesta poimittu menetelmä. Tutkielman tuloksena paras lopputulos saadaan aikaan käyttäen CRF sekvenssi-luokittelijaa laajalla piirrejoukolla. Kaikki kokeillut teksin analyysimenetelmät auttavat luokittelussa, joista tärkeimmän panoksen antaa morfologinen analyysi.