In the field of drug and alcohol abuse, health-related quality of life (HRQoL) has been used as an important clinical and research outcome. The aim of this study was to establish score linkages (concordance) among three HRQoL assessment tools: WHOQOL-BREF, DUQOL and HRQOLDA scores, applying a Rasch-based common person equating procedure.One hundred and twenty one adults were recruited from inpatient and outpatient treatment facilities in Sydney West Area Health Service. WHOQOL-BREF, DUQOL and HRQOLDA tests were administered. Item parameters were calculated applying Rating Scale Model, a Rasch model.Fit statistics suggest acceptable goodness-of-fit to the RSM for three instruments. Correlations between HRQOLDA and WHOQOL-BREF and between HRQOLDA and DUQOL scores were 0.719 and 0.613, and the RiU index was 30.4 % and 20.9 %, respectively. All three tests performed adequately for differentiating between individuals whose scores are located at different points along the continuum of the HRQoL construct.The results demonstrated a higher concordance between the HRQoLDA and WHOQOL-BREF than between the HRQoLDA and the DUQOL. However, it cannot be established unequivocally that the scores of these tools are concordant. In this study, the utility of the application of the Rasch model to provide an empirical benchmark for the selection of measurement tools to be used in the context of health care and research is demonstrated. In the field of drug and alcohol abuse, HRQoL has been used as an important clinical and research outcome. HRQoL started to be used as a complementary outcome measure to “hard” indicators, such as criminal behaviours, unemployment, and illicit drug use . The conIn the field of substance use, HRQoL has been measured mainly via generic tests. These tests evaluate representative behaviours from daily activities and most frequent symptoms in normal persons. The World Health Organization Quality of Life (WHOQOL-BREF) is a generic questionnaire, which has been used widely as assessment tool in epidemiological research. The WHOQOL-BREF has been translated to various languages and tested internationally , 5.In recent years, specific tests have been developed to assess quality of life in the context of substance use, including the Injection Drug Users Quality of Life Scale (IDUQOL) , 7; the The HRQoLDA  or TECVAlinking refers to the general class of transformations between the scores from one test to another [equating, scale aligning, and prediction [Numerous methods have been developed over the years for correlating measurement tests and scales. The term  another . Three mediction . The useediction . Equatinediction . Concordediction . Concordediction .The WHOQOL-BREF, DUQOL and HRQoLDA are different tests that measure HRQoL construct, but their operational definitions are distinct. However, the three tests are currently used to assess HRQoL in the field of addiction. In this study, the authors present the results of analyses to assess the concordance of WHOQOL-BREF, DUQOL and HRQoLDA scores via a Rasch-based common person equating procedure. Common person equating procedure is conventionally used to evaluate different tests administered to a common group of research participants. The specific aim of this study was to establish score linkages (concordance), using a Rasch-based common person equating procedure, between the DUQOL and HRQoLDA and between WHOQOL-BREF and HRQoLDA.This study evaluated 121 adults recruited from inpatient and outpatient treatment facilities across the Sydney West Area Health Service (SWAHS) catchment area in western Sydney, Australia. Research sites included Blacktown Hospital, Cumberland Hospital, Nepean Hospital, and the Mount Druitt Centre for Addiction Medicine, all of which are higher education training facilities within Sydney West Area Health Service (SWAHS).Potential participants presenting for treatment were randomly invited to respond to the questionnaires. The inclusion criteria consisted of fulfilment of the DSM-IV criteria for substance abuse disorders (substance dependence and abuse disorders) and the ability to understand the aim of the study, as well as the content of the questions in both questionnaires, which entailed a satisfactory command of English. Exclusion criteria comprised of presentations exclusively due to alcohol abuse and/or involuntary admission for inpatient treatment.This study was granted approval by the SWAHS Human Research Ethics Committee. Prospective participants were provided with a written protocol pertaining to the study and a verbal explanation about the purpose of the study. They were also informed that participation was voluntary, confidential and anonymous. Volunteers were also informed that they could withdraw from this study at any time without any repercussion to their treatments. Research participants were then asked to sign an informed consent form prior to their inclusion in the study.The HRQoLDA Test is a quality-of-life assessment tool specific for drug abuse. It assesses the physical and psychosocial aspects of life through 20 five-choice items in a Likert-type scale, with choices being designated 1 to 5 points. The sum of the 20 scores represents quality of life, such that the higher the score, the better the quality of life.DUQOL Scale: This scale is a specific measure of individual quality of life in drug users. It consists of 22 items relevant to the physical, social, psychological, occupational, and geographical reality of life, rated on a seven-point Likert-type scale ranging from 1 (very dissatisfied) to 7 (very satisfied). Higher test scores indicate better overall QOL.WHOQOL-BREF Questionnaire. This generic questionnaire comprises 26 items, which measure the following broad domains: physical health, psychological health, social relationships, and environment. It consists of 24 questions chosen from the original WHOQOL-100 questionnaire, and 2 questions about satisfaction with Overall Quality of Life and General Health. The items have a five-point Likert-type scale ranging from 1 (lowest agreement) to 5 (highest agreement). Higher score indicates better QOL.Five data collectors underwent a period of training and supervision by the principal investigator prior to administering questionnaires independently. The data collectors met regularly to address any queries and ensure each were following the same procedure.The study participants completed the tests under minimal guidance from the trained examiners, who followed standardized instructional procedures. Interviews took place in a suitable room at the research sites mentioned above. Occasionally, specific questions not considered in the initial instruction procedure were answered on a one-to-one basis. Particular care was taken with non-native English speaking participants in order to ensure a satisfactory understanding.The Rating Scale Model (RSM), a Rasch model for polytomous items, was used in the psychometric analysis . The RSMWhen logit measures are compared between tests (tests of the same construct with different items), their probabilistic meaning is maintained but their substantive meanings may differ. Logit measures underlying different tests must be equated before the measures can be meaningfully compared .Rasch analysis results are interpretable when data fit the model. The residual fit statistics used were the INFIT and OUTFIT indexes for each item and person. The INFIT index is sensitive to unexpected behavior affecting responses to items near the person's measure level (inliers) while the OUTFIT index is sensitive to unexpected behavior by persons on items far from the person's measure level (outliers) . Both stConsidering that Rasch Models assumes unidimensionality, a parallel analysis was conducted to test dimensionality of HRQoLDA, the WHOQOL-BREF and the DUQOL. In parallel analysis, the mean eigenvalues and 95th percentile for the eigenvalues from random data were utilized as a baseline for determining dimensionality. All Factors with values greater than the baseline parameters  were retained. The computer programs for parallel analysis used was developed by Patil, Singh, Mishra, & Donavan . The resr2), where r is the correlation coefficient between both test scores [r = 0, there is a 0 % reduction; when r = 1, there is 100 % reduction. It is reasonable to expect at least 50 % of uncertainty reduction in one score resulted from the other score [In order to check concordance between scores, a Reduction in Uncertainty (RiU) index was utilized . This int scores . When r er score .Table Common-person’s equating of two instruments involves an assessment of the invariance of person’s estimates of a single-sample. The RSM person’s estimates  for each person in both tests are displayed in a scatterplot; the plots should fall on a single line with allowance made for the modeled standard error pairs for each person’s estimates . Figure Before displaying the scatterplot, following the recommended steps for common subject equating , the mea2 = 0.517). The slope of the empirical regression line is 0.309 and the intercept 0.279, when HRQoLDA and DUQOL are compared (R2 = 0.376). Correlations between HRQoLDA and WHOQOL-BREF and between HRQoLDA and DUQOL scores were 0.719 and 0.613, respectively. The RiU index between HRQoLDA and WHOQOL-BREF was 30.4 % and between HRQoLDA and DUQOL was 20.9 %.In Fig. The analyses of the items yielded a severity item range Table  for HRQoThe map of persons and items Fig.  shows thIn general, with Rasch models, an analysis is carried out to compute a separation index for and for items, instead of reliability coefficients. Person Separation Index (PSI) is used to classify people; it represents the number of statistically different performance strata that the instrument can detect in the sample. Low person’s separation (less than 2) indicates that the instrument could be not sensitive enough to classify between people with high and low ability . The HRQItem Separation Index (ISI) is used to demonstrate item hierarchy. The hierarchy of item severities is particularly important given that the planned items severity in the test content specifications can be compared with the order estimated from the data . Low iteThe Rasch reliability (of persons) is comparable to the traditional reliability of the test. The HRQoLDA, WHOQOL-BREF and DUQOL reliability coefficients were 0.90, 0.92 and 0.87, respectively. In Rasch models, each ability estimate has an associated standard error of measurement (SEM). The estimates of the SEM are displayed in Fig. The HRQoL is considered one of the essential measures required for the optimal assessment of the results of treatment interventions in drug dependence. Considering that the evaluation of quality of life of substance users is usually performed with different tests, the objective of this study was to establish the concordance among the HRQoLDA, the DUQOL (which is a specific assessment tool for substance use), and the WHOQOL-BREF . Although there are comparative studies with different QoL assessment tools in the context of several specific disorders , 23, to The results here presented indicate moderate to high correlation among all three tests. The results also demonstrated a higher concordance between the HRQoLDA and WHOQOL-BREF than between the HRQoLDA and the DUQOL. However, it cannot be established unequivocally, on the basis of the above-presented results, that the scores of these tools are concordant, given the low values of RiU indexes. It has been advocated that, if a variable cannot reduce uncertainty by at least 50 %, it is unlikely that the predictor can serve as a valid surrogate, via concordance, for the score being predicted .From a psychometric perspective, the advantages of IRT models and Rasch models, in particular, are obtained when data fit to model. The results have shown that data from all three tests fit adequately the RSM. Therefore, in all three tests, the pattern of responses produced by participants follow a common conceptual logic. One of the advantages of the RSM is that, whenever data fit the model, measurement levels area transformed from an ordinal to an interval scale. The construct of HRQoL is usually explored as an outcome in efficacy and effectiveness analyses. Thus, working with scores in an interval scale, instead of an ordinal one, is preferable both for the purpose of improving the interpretation of scores produced by research participants, as in this particular case, and for conducting the statistical analysis of data.On the map of the scale’s items, the location to each item can be identified on the HRQoL continuum. The HRQoLDA is a test that evaluates the widest range within the HRQoL continuum, followed by the WHOQOL-BREF and by the DUQOL. This distribution of items is important to avoid floor and ceiling effects observed in previous studies . It has In terms of accuracy, the DUQOL is the test that has demonstrated a lower error of measurement . Contrarily, the WHOQOL-BREF revealed more accurate scores on the extreme areas of the continuum, which was slightly superior and more accurate than the HRQoLDA on the same area of the continuum. In terms of reliability, all three tests reveal similar and adequate results. The Person Separation Index (PSI) was similar in both the WHOQOL-BREF and the HRQoLDA tests, while superior than the PSI observed for the DUQOL. Yet, according to the proposed psychometric parameters in this field, all three tests perform adequately for differentiating between individuals whose scores are located at different points along the continuum of the HRQoL construct. The three tests showed adequate values of Item Separation Index (ISI). The ISI was significantly higher in the HRQoLDA, which indicates that the HRQoLDA items perform at a superior level along the HRQoL continuum.In summary, the DUQoL is the most accurate instrument for the central area of the distribution of scores, but it is also the test with the narrowest range of item measures. Such characteristic can limit its usefulness in heterogeneous patient samples . The WHOQOL is the best instrument for comparing the scores among groups of patients and for general population use, given its conception and design as a generic instrument. Finally, the results of this study show that the HRQoLDA may be the most suitable tool to be utilized in efficiency and effectiveness studies. The HRQoLDA is the instrument with a widest range of item measures; it presents with less probability of floor and ceiling effects. This is particularly useful in the detection of clinically significant changes for more extreme scores.One of the limitations of this study relates to the sample size (121 participants). In spite of this limitation, it has been demonstrated in simulation studies that Rasch analyses are able to produce precise estimations (items and persons parameters) in analysis with samples with 100 or more participants .The results of this study reveal a high correlation between the scores of the HRQOLDA and WHOQOL-BREF questionnaire and a moderate correlation between the scores of the HRQOLDA and DUQOL questionnaire. There was a higher concordance (like a procedure of transformations between the scores from one test to another) between the HRQoLDA and WHOQOL-BREF than between the HRQoLDA and the DUQOL. However, it cannot be established unequivocally that the scores of these tools are concordant. In this study, the utility of the application of the Rasch model was demonstrated in the process of producing an empirical benchmark for the selection of measurement tools to be used in the context of health care and research.


Due to the semantic gap between visual features and semantic concepts, automatic image annotation has become a difficult issue in computer vision recently. We propose a new image multilabel annotation method based on double-layer probabilistic latent semantic analysis (PLSA) in this paper. The new double-layer PLSA model is constructed to bridge the low-level visual features and high-level semantic concepts of images for effective image understanding. The low-level features of images are represented as visual words by Bag-of-Words model; latent semantic topics are obtained by the first layer PLSA from two aspects of visual and texture, respectively. Furthermore, we adopt the second layer PLSA to fuse the visual and texture latent semantic topics and achieve a top-layer latent semantic topic. By the double-layer PLSA, the relationships between visual features and semantic concepts of images are established, and we can predict the labels of new images by their low-level features. Experimental results demonstrate that our automatic image annotation model based on double-layer PLSA can achieve promising performance for labeling and outperform previous methods on standard Corel dataset. With the advent of the information era, the usage of the Internet is increasingly prevalent and the scale of the multimedia database is fast growing. How to organize, index, and retrieve the image data set has become an important issue and absorbed more attention in recent years. The existence of the semantic gap  leads toAutomatic image annotation is mainly to predict the semantic labels according to the visual content of images, which can be roughly divided into two categories . The firThe first category is developed into the machine translation and multimodel fusion method in recent years from exploiting the simple SVM (support vector machine) or GMM (Gaussian mixture model) for image classification in early years. In 2002, the translation model (TM) was proposed by Duygulu et al. , in whicThe cross media relevance model (CMRM) proposed by Jeon et al.  also appThe most important part of the second category is to learn the link between the low-level visual features and high-level semantic features by the probability topic model. Blei and Jordan  model thPLSA-FUSION  algorithTraditional PLSA based image annotation models usually encounter a problem that the scale of visual and text words do not match . Namely,We propose a new multilabel annotation method of images based on double-layer PLSA model, which applies relevant knowledge of latent topic space for image semantic annotation. In this method, we represent the image visual features by BoW model  and geneThe rest of the paper is organized as follows. Image automatic annotation algorithm based on double-layer PLSA fully utilizes the visual and semantic information of images to construct the annotation model by using PLSA. The second-layer latent semantic topics are looked on as the “bridge” to connect the visual features and semantic concepts. The framework of our annotation model is illustrated in The model of BoW is widely applied in the natural language processing and information retrieval, in which texts (sentences or documents) are taken as unordered data sets and the influence of the word order is ignored. Nowadays this model is widely used in the field of computer vision. In our annotation model, BoW model is also used to represent the image content and the processing procedure is described as follows.t is Nt; then the label information of the image Ii can be represented as a vector with Nt dimensions, illustrated as follows:n is the quantity of the label tj appearing in the given image Ii; usually the values are 0 or 1.In the semantic label space, the limited vocabularies annotated manually are looked upon as a label set, which is originally a series of unordered keywords set and can be represented by BoW directly. Suppose that the number of the given label Nv is the amount of category, which is gained by clustering, each cluster can be represented by a visual word. All visual words make up the vocabulary, and an image Ii can be represented as a visual word histogram, which can be expressed as a vector with Nv dimensions and illustrated as  represents the number of visual word vi in the given image Ii. Unlike the elements of the vector in  can be any integers greater than 0, and the combination of different visual features can be simply connected via feature vectors ,,5], CMRMIn this paper, we analyzed the image content from the perspective of text and proposed an image multilabel annotation model based on a double-layer PLSA model. The low-level features of images are represented by BoW model, which converted continuous visual information into discrete visual histograms to represent the visual content of the image. Then the first-layer PLSA was used, respectively, in the label aspect and visual aspect to get two kinds of latent semantic topics. In the second-layer, PLSA was applied on these two unrelated latent semantic topic spaces to get the top-layer latent topics, which can create the connection between the visual features and labels. Finally, with the double-layer PLSA model, the image annotation was completed effectively. In order to prove the effectiveness of the double-layer PLSA model in image annotation, we completed experiments on Corel5K and compared with other related algorithms. The experimental results illustrate that the double-layer PLSA model can achieve outstanding performance for multilabel automatic annotation and outperform other related algorithms.


Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC) and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation. Cancer is a complex collection of distinct genetic diseases united by different hallmarks . Hanahan and Weinberg  describeAll cells within the tumor compete for oxygen, reduced organic compounds and space, so cancer can be viewed, from the standpoint of the complex system theory and artificial life disciplines, as an ecological system in which cells with different mutations compete for survival. The interaction among cells generates an emergent behavior, that is, a behavior present in systems whose elements interact locally, providing a global behavior which cannot be explained by studying the behavior of a single element, but rather the group interactions . CellulaPrevious works have used CA capabilities for different purposes in tumor growth modeling  8] 9]  [9] 8] [  [9] 8] Given the interrelations among different hallmarks, in addition to the dependence of the hallmarks on some parameters, this modeling at cellular level with CA facilitates the study of the final emergent behavior, which cannot be foreseen in many cases. The objective of the present work is to analyze, by using this CA model, the effect of treatment applications on cancer growth in a cancer stem cell context. On this basis, in the next two sub-sections the cancer stem cell theory and aspects about treatments as well as related works are briefly discussed. The same methodology as in our previous work  is emploThe cancer stem cell theory states that a small fraction of cancer cells is responsible for tumor growth and relapse. These CSCs have been shown to have various characteristics in common with stem cells. For example, they have the capacity to divide indefinitely . AdditioSeveral studies suggest that CSCs are relatively resistant to standard cytotoxic and radiation therapies. For example, Cortes-Dericks et al.  explain The goal of standard therapies like chemotherapy and radiotherapy is to destroy the tumor cells, while maintaining adequate amounts of healthy tissue. Optimality in treatment might be defined in a variety of ways. Some studies have been carried out in which the total amount of drug administered, or the number of tumor cells, is minimized. For example, in the models considered in  23], th, th23], In chemotherapy, the administration of one or more drugs is aimed to kill tumor cells in which the growth rate is faster than normal cells. Within this context, the mathematical modeling of anticancer chemotherapy has existed for more than four decades  25]. Fo. Fo25]. In the work of De Pillis and Radunskaya , the autSeveral models predict that continuous infusion (in particular of cell-cycle phase specific drugs) is more effective than short pulses . Howeverin silico studies about treatments. This present study is related to them although it will analyze the effect of treatments in a cancer stem cell context.These representative examples are not an exhaustive list of the works related to The event model used by Abbott et al.  in theirm) defined by the parameter m, with default value m = 100000 as in   , if, ifIgnorThe simulations begin with an initial grid full of healthy cells. Mitoses are scheduled for these cells . Subsequently, the simulation continuously pops the event from the event queue with the highest priority (the nearest in time), by performing the following processes :RandomIncrease the hallmark mutation rate if genetic instability (GI) is ON.m).Add mutations to the new cells according to the hallmark mutation rate (1/tl in both cells.Decrease Push events. Schedule mitotic events (push in event queue) for both cells: mother and daughter, with the random times in the future.If the three tests indicate possibility of mitosis:Schedule a mitotic event (in queue) for mother cell.If mitosis cannot be applied:Thus, after the new daughter cells are created, mitosis is scheduled for each of them, and so on. Each mitotic division is carried out by copying the genetic information  of the cell to an unoccupied adjacent space in the grid. As indicated, random errors occur in this copying process, so some hallmarks can be activated, taking into account that once a hallmark is activated in a cell, it will be never repaired by another mutation .The parameters have default values which are set only as a reference. Such values, since most establish probabilities, define scenarios where particular hallmarks are more relevant in tumor progression, so we can reason about the emergent behavior in different circumstances, although it is difficult in most cases to determine a particular tumor type in which a hallmark is predominant.There are two models when considering the origin of cancer cells: the hierarchical model assumes that tumors are originated from CSCs that give rise to progeny with self-limited proliferative capacity where most of the cells in the tumor are genetically homogeneous. The second model is the stochastic model or clonal evolution model, which postulates that tumorigenesis is a multistep process that leads to progressively genetic alterations with the transformation of healthy cells into malignant phenotypes .effective immortality (EI) and evade apoptosis (EA). In the simulations, a low number of CSCs in the inner area with growth factor are introduced in order to check their effect on the behavior of the multicellular system evolution.For the simulation of the hierarchical CSC model, the scheme that distinguishes between CSCs and Differentiated Cancer Cells (DCCs) was considered. CSCs have two defining properties: no limit in their proliferation capacity and resistance to apoptosis . In thisps = 0.01 in ps = 0.01), or asymmetrically to produce a CSC and a non-stem cancer cell with probability 1 − ps. Regarding the number of CSCs introduced from the beginning, this corresponds to a small percentage of the grid size (1–5%) since the proportion of identified CSCs varies among different cancers. For example, Ricci-Vitiani et al. [As previously explained, CSCs will divide symmetrically, with the same probability used by Enderling and Hahnfeldt  , since such a low value in parameter g (5) was used. The parameters set in this scenario are the same used by Spencer et al. [ignore growth inhibit (IGI) will have a high ability to invade the surrounding space. Cervical cancer is an example, whereas, on the contrary, the naked mole-rat displays hypersensitivity to contact inhibition which confers upon it an extraordinary resistance to cancer [In order to explain the effect of treatments in a CSC context, a scenario with high invasion potential where the value of parameter r et al.  in theiro cancer .ignore growth inhibit (IGI) in few of such DCCs, which can rapidly proliferate because of their advantage in this situation with practically no free sites . As more mutations appear in this proliferation of DCCs, the apoptotic process begins to be an important limit for their proliferation. Therefore, as an evolutionary and emergent consequence, the hallmark evade apoptosis (EA) also appears in many DCCs to avoid the apoptotic process. The fluctuations in the expansion of DCCs are because most cancer cells have the hallmark IGI acquired. However, when the concentrations or clusters of cells with IGI acquired reach a certain size, then the apoptotic process can decrease their size for a small time, until reaching another lower size where the proliferation continues again.Since there is not practically any free site, most CSCs remain quiescent until they have free space to perform mitoses. Given the low probability of symmetric division the number of CSCs remains stable during the 6000 iterations shown in At time iteration 5000 the 100% of non-stem cancer cells is killed, simulating a (perfect) cancer therapy and causing the drastic drop of the non-stem cancer cells. Nevertheless, since CSCs are more resistant to therapeutic interventions, such as chemotherapy or irradiation, compared with their differentiated counterparts , the CSCt = 5000 shows how these DCCs are eliminated by the effect of treatment. The next snapshots show how the healthy cells that have not performed the maximum number of divisions fill the space rapidly (see for example the cross-sections at t = 5020 and 5250), but the non-stem cancer cells recover quickly because the CSCs not killed produce non-stem cancer cells again. These DCCs produce an evolution pattern similar to the one at the beginning of the simulation, as shown in the cross-sections and in the upper part of The bottom part of Nevertheless, there is an important and evident difference with respect to the first growth pattern of DCCs: this second proliferation on non-stem cancer cells is faster. This is because after the elimination of DCCs, CSCs had more opportunities to proliferate and differentiate in the small amount of time until the grid is completely filled with mostly healthy cells. Therefore the few non-stem cancer cells, after the differentiation, can produce the faster proliferation of non-stem cancer cells. On the other hand, in the first part of the simulation, many iterations were needed to obtain a few DCCs with the hallmark IGI acquired, given the few possibilities of cell division and the low hallmark mutation rate.However, the situation would change if CSCs did not have the opportunity to proliferate and differentiate in the short interval with sufficient available free space after the treatment. The experiment was repeated but this time by considering a situation where the treatment kills DCCs gradually and within a given period. t = 6000 the treatment is ceased and DCCs begin to proliferate again. Nevertheless, the slope in the regrowth is not as high as in the previous case (t = 6000 (1000 iterations after the beginning of the regrowth) and the snapshot at t = 8000 of t = 6000), clearly shows the faster increase of DCCs using a high intensity treatment in a short period. This therefore indicates and explains that this strategy, the application of a treatment against non-stem cancer cells with low intensity and with a longer period, is better regarding the future regrowth of the tumor behavior. It should be noted that this conclusion is a consequence of the higher probability of CSCs proliferating and differentiating which is favored with treatments with high intensity. Moreover, this effect is independent of the particular advantage of DCCs proliferating, although in this example such a scenario, where cells with the hallmark IGI acquired are the most predominant, was chosen.At time iteration ous case  because ous case  and 3 orThis aspect in the avascular phase was analyzed. However, it should be further noted that the analysis will be analogous in a vascular phase or when CSCs evade the main tumor. The inclusion of metastasis and motility for CSCs could provide insights about other aspects, such as possible morphologies of the growing tumor, as studied, for example, in the work of Sottoriva et al.  in orderignore growth inhibit, and another scenario dominated by the hallmark evasion of apoptosis when using an increased mutation rate.The objective of this part of the study is to analyze treatment scheduling in a CSC context by taking into account the effects of treatment intensity and application period in future tumor regrowth. Two representative scenarios were considered: the one previously used where the predominant hallmark is g was set to 5 and the rest of the hallmark parameters were set to their standard values. The number of incorporated CSCs is 5% of the grid size, a larger number with respect to previous cases to show better CSC implications. A treatment is started from the beginning, and considering the four cases shown in In the first case  the treaself-growth (SG) in the outer part of the grid. In this area there is not growth factor, so empty sites appear quickly since only cells with SG acquired can perform mitosis. When a DCC with SG acquired appears in the outer area, a fast increase of DCCs occurs which is not controlled with the treatment. When these DCCs have colonized the outer area, other factors reduce their number, being the main reason that some cells have also acquired the hallmark ignore growth inhibit (IGI), given such rapid proliferation. Therefore the same reason for the oscillations in the number of DCCs in previous Figures appears again.In the first strategy , the simIn the third case , after 5self-growth), when the treatment is applied it kills cells mostly in this area. The empty cells are therefore mostly located in that area and, consequently, only the few CSCs located there can perform the asymmetric divisions. This explains why there is a lower number of asymmetric divisions after time iteration 5000. This effect is clearer when many DCCs are killed, as when the treatment is applied every 100 time iterations killing 75% of DCCs  with respect to the standard value (m = 100000). The parameter m sets the time scale of the simulation as it determines how fast tumor growth behavior can appear, although the onset of tumor growth depends on the parameter values of other hallmarks. Given the increased hallmark mutation rate, the hallmark evade apoptosis (EA) is the most predominant in DCCs in evading the apoptotic process. The experiment was repeated with standard parameters and a higher hallmark mutation rate (As Enderling et al. state  “MathemaIn this case of tumor growth modeling, as indicated by Savage  “ResearcDifferent strategies when a treatment is applied were analyzed by taking into account the implications of CSC presence. These cells are resistant to usual present therapies, so these are the main cause responsible for tumor regrowth after treatments. As stated by Sottoriva et al.  “TherapyVainstein et al.  employedOur results concerning the faster regrowth after a treatment are also in agreement with the results of Hillen et al.  when theFinally, the effects of different treatment strategies were analyzed by using continuous low-intensity treatments and periodic high-intensity treatments. The former presents an advantage as a continuous low-intensity treatment which does not favor CSC proliferation and differentiation, and therefore allows easy control of future tumor regrowth. On the contrary, the latter possibility of discontinuous periodic treatments with high intensity levels favors CSC proliferation and differentiation in the short term, and consequently favors future tumor regrowth. Thus, this analysis indicates that making CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation. As stated by Han et al.  “maintai


Caenorhabditis elegans and Drosophila genomes can be queried on our new web server, PhyloGene. PhyloGene provides intuitive and user-friendly platform to query the patterns of conservation across 86 animal, fungal, plant and protist genomes. A protein query can be submitted either by selecting the name from whole-genome protein sets of the intensively studied species or by entering a protein sequence. The graphic output shows the profile of sequence conservation for the query and the most similar phylogenetic profiles for the proteins in the genome of choice. The user can also download this output in numerical form.Proteins that function in the same pathways, protein complexes or the same environmental conditions can show similar patterns of sequence conservation across phylogenetic clades. In species that no longer require a specific protein complex or pathway, these proteins, as a group, tend to be lost or diverge. Analysis of the similarity in patterns of sequence conservation across a large set of eukaryotes can predict functional associations between different proteins, identify new pathway members and reveal the function of previously uncharacterized proteins. We used normalized phylogenetic profiling to predict protein function and identify new pathway members and disease genes. The phylogenetic profiles of tens of thousands conserved proteins in the human, mouse,  Phylogenetic profiling of a protein specifies the relative sequence conservation or divergence among orthologous proteins across a set of reference genomes. Proteins that function together, for example members of the same pathway or protein complex, often show similar pattern of conservation across phylogenetic clades. As an extreme case, when a species is no longer under evolutionary pressure to maintain a protein complex, pathway, organelle or specific function, the corresponding proteins are lost or show a strong divergence. Phylogenetic profiling based on the binary calls of the presence or absence of orthologs in the surveyed genomes produced impressive results in evolutionary analyses of a wide variety of prokaryotes and of eukaryotic organelles, such as the cilia ,2 and miRecently, we developed Normalized Phylogenetic Profile (NPP) analysis based on a continuous measure of sequence similarity that is adjusted to evolutionary distance between species. The level of protein conservation for the ortholog in a given genome is normalized to the scale of conservation for all proteins in this genome, in effect taking into account the genome-wide distribution of conservation values expected for this individual species. This method captures protein sequence divergence and partial loss in the context of inter-species phylogenetic distances. Starting with query proteins from a few well-studied genomes, we surveyed and compared their phylogenetic profiles across full protein sets from 86 eukaryotic genomes. These analyses revealed novel components in various biological pathways including RNAi, m6A RNA methylation and the MITF pathway, as well as identified novel proteins associated with melanoma and other diseases –11.Here we describe the implementation of the NPP algorithm on a web-based server, PhyloGene, which allows the user to submit protein queries, inspect the output in an interactive graphic format and download the output in numerical format.r are calculated between Z-score profiles for proteins of the query genome, and the top most similar phylogenetic profiles are recorded for each query protein. To estimate statistical significance of the resulting correlation, we use a naive null model of randomly shuffled species (columns of the table). For each pair of the compared profiles, we perform N = 1000 instances of random shuffling of values in one of the profiles and generate the corresponding random Pearson correlation coefficients (r). Based on the distribution of these random coefficients, we calculate a measure of statistical significance as the Z-score for the actual coefficient r.To generate phylogenetic profiles, NPP –11 perfoThe pre-computed top profiles along with the corresponding Pearson correlation coefficients and estimates of their statistical significance are displayed when the query protein is selected from the standard protein list. As a general rule of thumb, we observe that marginal Pearson correlation coefficient of 0.5 typically corresponds to a Z-score of ∼5.0, whereas highly significant Pearson correlation coefficient of 0.95 typically corresponds to a Z-score of ∼8.0. These Z-score values can be used as approximate cutoffs for insignificant and extremely significant similarities, respectively. It is important to mention that the Z-scores can be used only as rough estimation of the biological significance. A complimentary approach should take into account the biological knowledge about the query gene and estimate the significance of its co-evolved genes by the number of genes in the list that are known to interact with it. For example by integrating the PhyloGene results with other data sources like protein-protein interaction maps, results from high throughput screening or validated genetic pathways and find overlap between the lists as we previously showed .When an individual query protein is submitted as a sequence, the workflow is modified: (i) run BLASTP with the submitted sequence as a query against protein databases of multiple eukaryotic genomes and choose the top BLAST hit for each genome; (ii) filter out low scores (BLAST similarity score <50); (iii) normalize BLASTP bit scores by the highest score among genome hits; (iv) transform top bit score against each ‘subject’ genome into a Z-score based on pre-computed mean and standard deviation of scores generated by BLAST searches with all proteins from the selected query genome against this ‘subject’ genome. Finally, Pearson correlation coefficients are calculated between the query Z-score profile and the pre-computed Z-score profiles for proteins from the genome of interest, followed by the selection of the top phylogenetic profiles with the highest similarity to that of the query protein. Pearson correlation coefficients for each of the top profiles and their statistical significance are calculated and displayed as described above.PhyloGene is an intuitive and easy to use web tool that implements both of these modes. At the front page, the user can submit the query in the left panel and view the graphic output as a heatmap of sequence similarity patterns across multiple genomes in the right panel. The numerical output for more detailed analysis can be downloaded using a link to the Excel table in the left pane. The query can be submitted by (i) selecting a protein name from the menu of all proteins for a genome of the user's choice or (ii) submitting a protein sequence by pasting in a window or uploading the sequence file. In the left pane, the user can select the query genome of interest and the number of top most similar phylogenetic profiles to display. The front page also includes the link to a brief tutorial on using the tool.Homo sapiens, Mus musculus, Drosophila melanogaster or Caenorhabditis elegans); (ii) query protein, by either selecting the gene of interest from the list or entering a protein sequence and (iii) the number of most similar phylogenetic profiles to display .The user can submit the query in the left pane of the front page by setting (i) organism of interest  website with the information about this gene.The y-axis of the heatmap corresponds to the proteins from the query genome whose phylogenetic profiles are most similar to the profile of the query protein. These profiles are shown as rows of the heatmap; the number of displayed profiles is selected by the user during submission process. The top row corresponds to the profile of the query protein. Protein names are displayed at the left edge of the heatmap. Hovering over a protein name with the mouse brings up a short description of the gene; clicking on a gene name opens the link to the Ensembl  to dark blue (very high sequence similarity). Hovering over a square brings up the protein name corresponding to this row, the genome in which the homology search was performed, and the sequence similarity value ranging from 0 to 1; this is also the value that the color of the square is based on.r and Z-score.The first two columns of the heatmap are colored in yellow–dark red hue and represent Pearson correlation coefficient and statistical significance of the similarity to the query. Hovering over these columns brings up the values of In addition to visual inspection of the heatmap, the user can download the output in a numerical format as an excel table Figure .The tablr > 0.6, consistent with their known functional association with ALAD. Interestingly, many of the proteins with similar phylogenetic profiles have been implicated in distinct biological processes from heme biosynthesis, such as transaminase activity. For example SETD1A, SETD1B AADAT and SUV39H2 are implicated in lysine degradation; 16 other proteins with phylogenetic profiles similar to heme biosynthesis genes, such as FDXR, GPX1 and GOT2 are associated with the mitochondrion and several proteins are involved in lipid biosynthesis or processing, such as three ORM1-like proteins. These proteins regulate the biosynthesis of sphingolipids; and mutations in these proteins have been associated with the development of childhood asthma  as a query confirms previously known genes in this pathway and suggests new functional links of ALAD with other human proteins Figure . ALAD isd asthma . The simThe PhyloGene web server provides online access to our method of normalized phylogenetic profiling and has several immediate biological applications: (i) analyzing the conservation pattern of a given protein across eukaryotic genomes; (ii) predicting function of previously uncharacterized proteins, based on the phylogenetic profile similarity to proteins with known function; (iii) suggesting groups of proteins that co-evolved together and identifying new pathway members, based on inferred co-evolution with the known members of the pathway and (iv) revealing organismal adaptions to the environment on the level of proteins or pathways, which may provide clues to protein function.


Pharmacovigilance is the activity related to the collection, analysis and prevention of adverse drug reactions (ADRs) induced by drugs. This activity is usually performed within dedicated databases , in which the ADRs declared for patients are usually coded with a specific controlled terminology MedDRA . Traditionally, the detection of adverse drug reactions is performed with data mining algorithms, while more recently the groupings of close ADR terms are also being exploited. The Standardized MedDRA Queries (SMQs) have become a standard in pharmacovigilance. They are created manually by international boards of experts with the objective to group together the MedDRA terms related to a given safety topic. Within the MedDRA version 13, 84 SMQs exist, although several important safety topics are not yet covered. The objective of our work is to propose an automatic method for assisting the creation of SMQs using the clustering of semantically close MedDRA terms. The experimented method relies on semantic approaches: semantic distance and similarity algorithms, terminology structuring methods and term clustering. The obtained results indicate that the proposed unsupervised methods appear to be complementary for this task, they can generate subsets of the existing SMQs and make this process systematic and less time consuming. However, this major therapeutic advance is limited by the toxicity of some drugs that may also be dangerous for patients. To minimize the risks associated with drug use, it is necessary to detect as early as possible the adverse drug reactions (ADRs) that may have been unnoticed during clinical trials. This is the role of regulatory authorities and of pharmacovigilance units within pharmaceutical laboratories and hospitals. The main source of knowledge for pharmacovigilance is based on the reporting of the ADRs by health professionals and patients. These case reports are recorded in pharmacovigilance databases. To facilitate the analysis of those data, ADRs are coded using a controlled vocabulary, usually MedDRA  . The detetection ,5. It mai.e. among the SOCs we can find for instance Musculoskeletal and connective tissue disorders, Hepatobiliary disorders, Psychiatric disorders and Cardiac disorders. In Table is-a relations between them. For instance, in Table Arthritisis-a HLT Arthropathies NEC, while the HLT Arthropathies NECis-a HLGT Joint disorders. The situation is different when we consider the relations between PTs and their LLTs [Arthritis is identical to its PT term Arthritis, although other LLTs such as Arthritis aggravated, Atrophic arthritis, Joint inflammation, Finger arthritis, Knee arthritis are subordinated to this PT.The MedDRA terms are structured into five hierarchical levels Table . From their LLTs : these aHaemorrhage SMQ contains MedDRA terms related to bleeding in all parts of the body: it groups terms from a large set of SOCs. The SMQs are developed internationally by experts looking manually in all the MedDRA terms relevant to each SMQ. There are currently 84 SMQs that do not cover the entire drug-induced set of safety topics . This situation leads us to propose methods for automating the clustering of the terms when MedDRA provides no grouping category appropriate for a given safety topic. The lists of MedDRA terms may then be presented for the selection to the experts.A first method to group the MedDRA terms is based on the hierarchical levels in MedDRA: HLT (High Level Terms), HLGT (High Level Group Terms) or SOC (System Organ Class) ,8. Howevontology and ÉvénementsIatrogènesMédicamenteux (Adverse Drug Effects in French) [Other work on the automatic clustering of pharmacovigilance terms relies on a specific resource ontoEIM. ontoEIM stands for  French) . This re French) . The pro French) , in whic French) ,13. Prec French) . The sam French) . In the We address the problem of grouping the MedDRA pharmacovigilance terms in a way that reflects coherent and medically sound safety topics. Although the MedDRA vocabulary is structured according to specific organ-based semantic characteristics of the terms, this organization does not fully capture important semantic relationships among terms. We aim to explore how to group these terms in a way that directly reflects the intuitions captured in manually created SMQs. More precisely, our objective is to work on semantic methods for the automatic creation of groupings of the MedDRA terms. We propose to adapt and to combine two strategies: semantic distance and similarity algorithms, and terminology structuring methods. Special attention is paid to the merging and comparison between these two methods and evaluation of the generated term clusters. In order to measure the ability of our methods to produce clusters similar to the existing SMQs, we evaluate the generated clusters by taking these existing SMQs as a gold standard. Our method relies on two main assumptions: (1) the MedDRA terms can be used for the automatic creation of groupings of terms; (2) the combination of the semantic methods provide complementary results.R (http://www.r-project.org) languages, and several Natural Language Processing (NLP) tools.The method is organized in four main steps Figure : (1) comWe make use of several types of material.PT terms because they are used for building the SMQs and for coding the pharmacovigilance case reports. The ontoEIM resource attempts to improve the MedDRA structuring in two ways: the structure of MedDRA terms becomes similar to the structure in SNOMED CT which makes it more fine-grained ; and the MedDRA terms receive formal definitions (decomposition into their semantic primitives). Thus, in Table Abdominal abscess and Pharyngeal abscess are defined on two axes (Disorders and Body structure). For instance, Pharyngeal abscess is semantically decomposed into the Disorder element Abscess morphology and Body structure element Neck structure. The names of the formal definition elements correspond to the names of the hierarchies of the SNOMED CT. Within the ontoEIM, we have three hierarchical trees  are exploited either as a flat list of terms, in which case the semantic relations between them are computed with terminology structuring methods, or through the ontoEIM resource , in whic09 are exaccord, concordance}, {pain, ache}, {aceperone, acetabutone}, {adenazole tocladesine} or {bleeding, haemorrhage}. These resources are used with the terminology structuring methods.Three kinds of lexical resources are involved in the methods: (1) synonyms extracted from the UMLS ; (2) synonyms acquired from three biomedical terminologies thanks to their compositionality  , Skin and subcutaneous tissue disorders SOC , Eye disorders SOC , etc. The size of the SMQs goes from 47 terms  up to 8,036 terms . The SMQs can be composed of a flat list of terms or can be hierarchically structured.We use the 84 SMQs (2010 version) as the gold standard for the evaluation of the generated clusters of terms. The SMQs contain MedDRA terms relevant to a given safety topic. These terms usually belong to different SOCs. For instance, the Pharyngeal abscess and Abdominal abscess, we follow the path within the ADR hierarchy and obtain the shortest path equal to four edges. In addition to the path length, other criteria may be taken into account: hierarchical depth of terms [Several semantic distance and similarity algorithms can be applied within structured terminological resources -21. In oof terms ,23, infoof terms , the neaof terms , etc. Beof terms , informaof terms , gene anof terms , and terof terms ,29. A reof terms .t1 and t2: (1) the Rada semantic distance [sp; (2) the LCH Leacock and Chodorow semantic similarity [sp and on the maximal depth found within the terminology; (3) the Zhong semantic distance [D and B) to make the semantic representation of the terms more fine-grained. To illustrate, let’s consider Abdominal abscess and Pharyngeal abscess terms from Figure sp: spADR=4, spB=10 and spD=0. The unique semantic distance between the MedDRA terms for each semantic distance measure is computed as follows:In our work, we separately exploit three algorithms to compute the semantic distance and similarity between two terms distance  relies omilarity  relies odistance  relies oADR,D,B} respectively correspond to the MedDRA ADR terms, and the axes Disorders D and Body structure B; t1 and t2 are two MedDRA ADR terms; Wi is the coefficient associated with each of the three axes  is the semantic distance between t1 and t2, computed on a given axis with one of the three semantic distance measures {Rada, LCH, Zhong}. For the example above, the unique semantic distance is 3.5. According to the tested parameters , we build six symmetric matrices with the MedDRA terms from ontoEIM.where {e latter ); and sdThe terminology structuring provides methods for the detection of semantic relations between terms. Two strategies may be distinguished: those which rely on the internal analysis of the terms and those which rely on the contexts within which the terms occur. Because we are working on the terms out of their context, we exploit the terminology structuring methods which rely on the internal analysis of the terms. These methods are applied to a flat list of 18,209 MedDRA PTs. They lead to the detection of hierarchical subsumption and synonymy relations between these terms. The terms are pre-processed: the POS-tagging is done with Genia tagger  and the The basic statement on lexical inclusion hypothesis  states tWe distinguish three steps within this approach: muscle pain results in two components: head component pain and expansion component muscle;● the terms are syntactically analyzed into head and expansion components. For instance, on Figure muscle pain (the whole term) and pain (the head component of the term).● the syntactic and semantic relation is then established between a given term and its head component. For instance, the term on Figure muscle pain is the hierarchical child of the short term pain. Indeed, muscle pain conveys a more specific information;● With these specifications, the identified relations are hierarchical: the long term ● parent and child terms have to be MedDRA terms, otherwise the identified relations are removed.muscle pain is localized in muscle.With the applied specifications of this approach, the identified relations are induced from lexical and syntactic information conveyed by the analyzed terms. Besides, these specifications guarantee that the identified relations correspond to the hierarchical subsumption. In fact, we do not allow the induction of other kinds of relations. For instance, if relations between the whole terms and their expansion components were allowed, the identified relations would be associative, such as localization for example from Figure PT terms. This tool uses several transformation rules, such as insertion , morphological derivation  or permutation (aorta coarctation/coarctation of the aorta). Each transformation rule is associated with hierarchical or synonymy relations: the insertion introduces a hierarchical relation , while the permutation introduces a synonymy relation. When several transformations are involved, such as in gland abscess and abscess of salivary gland (combination of permutation (synonymy) and insertion (hierarchy) rules), the hierarchical relation prevails.We work with Faster  for the The synonymy relations are acquired in two ways: 1. The synonymy relation is established between two simple MedDRA terms if this relation is provided by the lexical resources.2. The identification of synonym relations between complex terms relies on the semantic compositionality . Composipain and ache provided by the lexical resources, the terms muscle pain and muscle ache are also identified as synonyms [In our work, we consider that two complex terms are synonyms if one of their components at the same syntactic position are synonyms and the other components are identical or also synonyms. For instance, given the synonymy relation between synonyms  , we compute whether smaller clusters are included into larger clusters and we merge those clusters which have at least 80% overlap between them.● Between the clusters computed by the two methods (semantic similarity and terminology structuring), two clusters provided by these methods and which have at least 80% overlap between them are also merged together.We first evaluate the correctness of the generated semantic relations, which is done manually by a computer scientist.P , recall R (percentage of the relevant terms clustered divided by the number of terms in the corresponding SMQ) and F-measure F (the harmonic mean of P and R). The final evaluation values are computed with the thresholds which provide the best results the most frequently during the cross-validation step. We evaluate the clusters from each method separately and after their merging. A qualitative evaluation is done by a medical expert: we perform a failure analysis of our methods. As for the baseline, we chose the most frequently used approach for the grouping of the MedDRA terms, which relies on the hierarchical structure of MedDRA: the exploitation of the hierarchical subsumption of the PTs through the HLT MedDRA level [We then perform quantitative and qualitative evaluation of the generated clusters. The quantitative evaluation is performed thanks to their comparison with the SMQs. A cluster is associated to the SMQ with which it has the maximal F-measure. For the setting of the thresholds of the semantic distance and similarity algorithms and their evaluation, we perform a ten-fold cross-validation: the data are partitioned into ten subsets, one subset is used for the setting up the methods while the remaining nine subsets are used for the evaluation. This process is done ten times with a different training subset each time. Three classical measures are then computed: precision RA level ,8,42.Gastric ulcer and Gastrointestinal ulcer is 1, while the distance between Gastric ulcer and Biopsy tongue is 10, which reflects the semantics of the terms from these two pairs . The flat list of 18,209 MedDRA terms has been processed with the terminology structuring methods for the detection of hierarchical and synonymy relations. The results for the terminology structuring methods are presented in Table PTs, are used.The 7,629 MedDRA terms from ontoEIM have been processed through the three semantic distance and similarity algorithms. An excerpt from the generated matrices is presented in Table Radius clustering 4 for Rada, 4.10 for LCH and 0.02 for Zhong; with the HAC clustering 300 classes. With these thresholds, the number of clusters and their size become larger. We apply these best thresholds to generate the final set of clusters to be evaluated and analyzed by the expert. The impact of the best thresholds on the clusters varies across the SMQs, but the global average results are improved. For the terminology structuring methods the best results are obtained with lexical inclusions, morpho-syntactic variants and synonyms.Table The generated semantic relations and clusters have been evaluated via a comparison with the existing SMQs, with the baseline, and through an analysis provided by a medical expert and a computer scientist. The key observations are that the proposed methods outperform the baseline and that the merging of the methods improves the results. We have also observed several limitations of the methods and results. We discuss the performed analysis and evaluations in the following section.The ontoEIM resource is unique of its kind, but currently it suffers from incompleteness: only 51% of the MedDRA PTs are aligned with the SNOMED CT terms. The main reason for this is that ontoEIM integrates the alignments between these two terminologies which are already proposed by the UMLS. The integration of additional alignments ,44 is planticonvulsant drug level, drug level}, {blood smear test, smear test}, {eye movement disorder, movement disorder}. Thus, within the first pair, there is an ambiguity on drug as two dependencies seem possible: {anticonvulsant drug level, drug level} as proposed with the maximal syntactic head analysis or {anticonvulsant drug level, level} . In our work, we give preference to the syntactic analysis with maximal syntactic heads. But whatever the performed syntactic analysis, the semantic relations remain correct. Nevertheless, we will see that, although the generated semantic relations are deemed correct, the relevance of these relations and of the terms they link is not always perfect to the building of the SMQs. Indeed, some of the terms are seen to be relevant to the SMQs while others do not, which may be due to the difference existing between the linguistically observable semantics of the relations and their domain or medical validity.A manual analysis of the generated hierarchical relations, done by a computer scientist, indicates that these relations are usually correct: the syntactic constraints guarantee correct propositions. Nevertheless, we observed a small number of syntactic ambiguities. They appear within 144 pairs (5%) with maximal syntactic heads and correspond to pairs like: {In Table x axis represents the 84 reference SMQs, the y axis the evaluation results. On the whole, we can observe that precision is usually higher than recall, and that there is an important variation across the SMQs. In our previous experiments [In Figures eriments , we gaveWe also performed an additional analysis of the clusters generated with the terminology structuring which shows the following contribution of the generated semantic relations: 1. the hierarchical relations form the basis of the clusters: they correspond to 96% of the involved terms and show 69% precision. Only three clusters do not contain hierarchical relations;2. the Faster relations are involved in 50% of clusters and show a precision between 75 and 85%;3. one third of the clusters contains synonymy relations, and their precision varies between 55 and 69%;4. the relations acquired with the UMLS resources are involved in 14% of clusters while their precision is only 38%;heart syndrome, nerve degeneration} and {heart injury, nerve damage}). The whole impact of the WordNet synonyms is almost null. Moreover, the involved terms are either proposed by other more contributory methods or do not correspond to correct propositions. The most interesting (and correct) relation is {intestinal gangrene, gastrointestinal necrosis}. It is unique to the WordNet resource output.5. the WordNet-based relations involve only six terms . The synonymy relations may involve greater semantic variations  and this explains their less impressive but still acceptable precision. Moreover, the synonym terms may have a contextual semantic value [i.e. be valid in some but not in all the contexts. As a matter of fact, the pairs {sepsis, infection} and {abdominal, intestinal} have been acquired from terms considered as synonyms in the existing terminologies. However, these synonyms are not deemed to be correct for the creation of the SMQs. Finally, the hierarchical relations convey yet greater semantic variation , although their precision is higher than the precision of the synonym relations. Moreover, the generated hierarchical relations participate very actively in the creation of the clusters of terms. As we previously observed, the generated hierarchical relations bring the majority of terms in the clusters. This is a surprising observation: we did not expect to receive such a great contribution from the hierarchical relations. Another surprising observation is related to the poor contribution of the synonymy relations from WordNet and those extracted directly from the UMLS: both their coverage and precision are weak and they are weakly involved in the creation of the clusters.On the whole, observations of the impact of the methods and resources on their contribution correspond to the expected results but provide also with surprises. Thus, the highest precision is observed with the morpho-syntactic Faster relations: these are based upon the morphological variations of the terms and usually convey minor semantic modifications  and Thrombocytopenia (HLT)) or non ambiguous correspondences  and Acute renal failure (HLT)). We use these 46 SMQs as gold standard with the baseline hierarchical subsumption and with our methods. These 46 SMQs are a subset of the whole set of the 84 SMQs. Similarly to the results presented in the previous paragraph, the average performance on the baseline set is indicated in Table Our baseline is the most common method utilized for the grouping of the PT terms within MedDRA: their hierarchical subsumption through the HLT terms. Among the 1,688 HLTs and 84 SMQs, 46 of them have either direct , as well as the number of common terms between them (com) and the performance  when computed against the reference data Reference and also after the manual analysis performed by the expert . The results obtained with different strategies are indicated: the semantic distance sd, the terminology structuring struc, as well as the merging merg of semantic distance and terminology structuring. We can observe that the performance of the methods varies a lot across the presented SMQs and clusters. Usually, the terminology structuring provides a higher precision and lower recall than the semantic distance measures. The semantic distance and merging approaches generate bigger clusters: they lead to increased recall but they decrease the precision. Usually, the F-measure takes advantage and is improved. The manual evaluation by the expert accepts additional terms, which allows to have a more complete picture of the performance of the proposed methods. This expert evaluation leads also to increased precision, recall and F-measure.In Table We performed a detailed qualitative analysis of seven SMQs and clusters with the medical expert.Angioedema contains 52 terms which mean signs and symptoms of angioedema. The semantic distance algorithm provides a cluster with 56 terms, among which 36 do not belong to this SMQ. Three of them  could be included in the SMQ because they are caused by drugs and are indeed the symptoms of angioedema. Eight more terms  are true false positives because they are not related to angioedema. Finally, other terms, although they mean oedemas, are not caused by drugs. Thus, according to the expert, three of the 36 false positives should be considered for the inclusion in the SMQ. As for the terminology structuring method, it provides a cluster with 31 terms, among which 12 do not belong to the SMQ. According to the expert, this evaluation is correct: the term Injection site oedema has a too broad meaning , while 11 other terms mean oedemas not caused by drugs. With the merging we improve the performance: we obtain two more true positives , while the false positives remain the same. The results are different because the merging is not supervised (it is based upon the intersection between the clusters): the clusters may be different when considered separately for each method and when considered through their merging. As a matter of fact, this is precisely what happens with the Angioedema SMQ: during the merging step, the clusters selected are different from those selected during the evaluation of the individual methods, and we gain one new true positive term.For instance, the SMQ Embolic and thrombotic events, our methods provide 92 false positives with the semantic distance and one with terminology structuring. The analysis of these terms is very similar to what we observe for other SMQs: some of the proposed terms should be considered for inclusion in the SMQ  because they are very close to the already included terms, other terms have a too broad meaning to efficiently contribute to the SMQ . Finally, some other terms (Mesenteric artery stenosis...) are true false positives. Among the false negatives of the Angioedema SMQ, we find terms such as Wheezing, Drug hypersensitivity, Swollen tongue, Penile oedema, and among the false negatives of the Embolic and thrombotic events SMQ, we find terms such as Venous occlusion, Splenic infarction, Subclavian artery thrombosis. The main reasons of the false negatives are: (1) with the semantic distance and similarity algorithms, in addition to the fact that only 51% of the MedDRA terms are included in the ontoEIM resource, when the terms are included they may be too distant in this resource, (2) with the terminology structuring, the methods may be not exhaustive enough to detect all the lexical and syntactic regularities within the terms.For the SMQ We combined several strategies and methods for the clustering of the MedDRA terms with similar or close meaning. We performed a comparison of the results obtained and analyzed their complementarity. A ten-fold cross-validation was carried out in order to test different parameters and select those which positively influence the results. Although the automatic creation of the SMQs is a difficult task, our results indicate that the automatic methods may provide a basis for the creation of the SMQs. The current evaluation has been done against the existing SMQs, but we expect we can apply the same method for the creation of new SMQs with similar performance. Our methods generate clusters which are smaller than the corresponding SMQs and which show their different aspects. For this reason, the precision of the clusters is often high, while their merging leads to the improvement of their completeness.Our future work will address the current limitations of our methods and results. The material, and more particularly the ontoEIM resource, is being improved thanks to a better alignment with the SNOMED CT ,44. MoreThe authors declare that they have no competing interests.MD implemented and performed the semantic distance and similarity computing, the clustering experiences and the quantitative evaluation; LD had the responsibility to evaluate the obtained clusters; TH adapted the terminology structuring methods, generated the results with these methods and evaluated their correctness; NG led the work, proposed the methodology, participated in the evaluation and designed the article. All the authors participated in the writing of the article. All authors read and approved the final manuscript.


ANSYS CFD into which the three-dimensional model of turbodrill is input. In light of the distribution law of the pressure and flow field, the functions of the turbodrill blade are improved and optimized. The turbodrill blade optimization model was verified based on laboratory experiments. The results show that the design meets the deep hard rock mineral exploration application and provides good references for further study.Turbodrill is a type of hydraulic axial turbomachinery which has a multistage blade consisting of stators and rotors. In this paper, a turbodrill blade that can be applied in crystallized section under high temperature and pressure conditions is developed. On the basis of Euler equations, the law of energy transfer is analyzed and the output characteristics of turbodrill blade are proposed. Moreover, considering the properties of the layer and the bole-hole conditions, the radical size, the geometrical dimension, and the blade profile are optimized. A computational model of a single-stage blade is built on the  Turbodrill has been used in oil and gas industry over one century, yet it remains relatively obscure , 2. As g CFD modeling [Turbodrill is a type of hydraulic axial turbomachinery which has a multistage blade consisting of stators and rotors. It converts the hydraulic power provided by the drilling fluid to mechanical power through turbine motor while diverting the fluid flow through the stator vanes to the rotor vanes . The turmodeling . The turThe turbine drilling tool can be configured to match the application variables as required to optimize performance. Different types of blades can be used to produce different performances . UnfortuTurbodrill blade converts the hydraulic power provided by the drilling fluid to mechanical power through turbine motor while diverting the fluid flow through the stator vanes to the rotor vanes. D) which has the average speed of turbine blade performance which is similar to considering all cylindrical layer flow movement performances of turbine blades. This method is called the unit theory method. So the average diameter is calculated as follows:The mud flows into the passages among turbodrill blades which can be regarded as different pieces of coaxial cylindrical movement. Different distances of each layer of liquid particles to the central axis result in different speed. There must be an average diameter  the fluid is ideal; (2) turbodrill blade is infinitely thin; (3) turbodrill blade is countless; and (4) the flow and pressure losses can be neglected. So the fluid flow can actually move as expected without any friction.When the fluid flows through the stator vanes, there is no mechanical energy. The pressure energy is transformed into kinetic energy with partial hydraulic losses. However, most energy will be transformed into mechanical energy with partial hydraulic loss when the fluid goes into the rotors vanes.c2 = c0. So the whole output mechanical energy of single-stage turbine blade is as follows:The different height of drilling fluid can be ignored due to small values between the two sections. Because the flow through each level of the turbine blades is approximately equal and all levels of the length and the structures of the turbine blade are the same, there is no flow law. The flow rate between the turbines at the same level is also similar, meaning that In terms of the single-stage turbine blade, the torque transformed to the rotors is equal to the torque fluid received in different directions. Based on the law of moment of momentum, the output torque of single-stage rotors is calculated asThe transfer power consumption of single-stage blade isAccording to the energy conservation, the drilling fluid pressure energy can be transformed into mechanical energy. So the energy conversation formula can be expressed asThe transformed mechanical energy of the pressure head isZ is the numbers of the multistage turbodrill blades. The output torque of single-stage rotors, the energy, and the pressure head are calculated as follows:The turbodrill blade is a series of the connections in the shell of the turbodrill. Suppose that The output mechanical energy of turbodrill is related to the numbers of blades stages, radius size, and blade profile. However, the feasible method is increasing the different value of the circumferential speed because of uncomfortable use of the turbine when enlarging the length and radius size of the turbodrill. So it is important to optimize the profile, structure angle, and solidity of the turbodrill blade.β1) should be equal to the inlet structure angle (βk1) in stators blade. α2 = αk2 is also satisfied in rotors blade, in which working condition is called the no-impact status.The field conditions must be taken into account when optimizing the turbodrill blade. The value of the circumferential speed of the turbodrill blade changes with the variation of the weight on bit (WOB). ma), and circulation flow coefficient Three dimensionless parameters, such as the axial velocity factor cz) and the circumferential speed of the blade (u0), which is related to the blade structure angle. The axial velocity factor is established as  is increasing, the pressure drop will be reducing simultaneously. The hydraulic efficiency is also related to the axial velocity and circulation flow coefficient. However, considering the hydraulic efficiency, it is recommended that the axial velocity factor and circulation flow coefficient should be adjusted within proper domain.The equation shows that the output torque under the premium working condition is proportional to circulation flow coefficient. The bit rotation speed is only opposite to the axial velocity factor. The specialized function of the turbodrill blade can be translated by adjusting the axial velocity factor and circulation flow coefficient. When the hydraulic efficiency , x is the dorsal arc along the surface profile from the origin (O), and y is the vertical distance from the normal line of the surface profile. u and v are the corresponding speeds of the two directions, respectively.The blade runner field is changed mainly by influencing the speed and pressure of the flow near the blade surface. In order to keep a higher efficiency, the speed and pressure should be changed smoothly, reducing the fluid friction, flow separation loss, and blade end pressure loss. Since then, 2D orthogonal curvilinear coordinates are established to research the influence of the blade line on the law of the fluid move on the blade surface. The fluid field can be changed by affecting its speed and pressure. That smooth speed and the pressure distribution ensure high efficiency. On the basis of the primary motion equation about the steady flow boundary of the incompressible fluid, the massive conservation and momentum conservation can be expressed asR) influences the fluid parameter most. A continuous derivative of curvature can ensure smooth distribution. Suppose that the profile of the turbodrill blade is y = f(x) and its curvature and third derivative are, respectively,The equations indicate that boundary curvature radius (yp = f(x) and ys = g(x). ConsiderAlthough combined profile can meet continuous shrinkage, it has no continuous curvature derivative. This can cause sudden change of the fluid speed and pressure and damage hydraulic property of the turbodrill. As a result, we use quintic polynomial combined with computer-aided design to develop profile of the turbodrill. Suppose that the pressure side and negative pressure side of the blade are Based on the angles of the inlet and outlet, the four special points can be calculated. Put the four special points, first derivative, and second derivative into their equations, and the pressure side and negative pressure side of the blade can be described asa0, a1, a2, a3, a4, a5, b0, b1, b2, b3, b4, and b5 can be solved by the two linear equations (n0 = 500 rpm and output torque M0 = 1000 Nm which are given by the corresponding relationship between torque and speed.The parameters of  quations  and 20)a0, a1,After checking the blade line, it shows that there are no reflection points on pressure surface and suction surface. This constitutes a continuous flow path contraction. It proves that the line has a relatively flow loss, meeting all the design requirements. Finally, according to the axial length of size constraints, a leading edge circle and a trailing edge circle are established on its tangent line at both ends of the blade so as to make the blade closed. SolidWorks a single cycle turbine blade airfoil-dimensional model  has emerged as an effective optimization tool for the experiments because of its diverse applications in industry , 20. Draal model , we can  ANSYS is used to research the differences between the flow fields. The curve of the blade is complex—short runner and relatively fast flow rate. After calculating Reynolds (Reynolds number), it proves to be turbulent. Different models need to set different solution control and execution control. Because this three-dimensional simulation of flow field is continuously differentiable turbulent flow, the calculation of control theory should be turbulence model theory. The default equation is Reynolds averaged equations. For unsteady turbulent flow, ANSYS analysis cites false concept of homeostasis without regard to the circumferential direction of the flow field changes, so at this mode of analysis it should be TRAN steady flow. The input flow and output flow are stable when the blades are applied, resulting in flow between the stator and the rotor blades relatively stable.The blade is characterized by irregular shape, demanding an automatic mesh generation. In this simulation, a minimum unit meshing by free division ensures accurate results. There are 142 units meshing the finite element model in  ANSYS program system. After completing the relevant definitions and settings, we use Run Flotran to solve the corresponding analysis of the results. In the ANSYS postprocessor tune the corresponding calculation results are obtained using the PLOT function blade flow velocity and pressure fields for analysis.For the drilling fluid of the turbine blade, with certain density and viscosity, we can select fluid and then analyze and define these two worthy constants when we set fluid conditions. Other parameters generally use the defaults of CFD analysis of the two different turbine blades on the basis of the preliminary profiles was completed for low speed high torque flow field simulation. Figures Y-component of fluid velocity, X-component of fluid velocity, Z-component of fluid velocity, fluid velocity, and turbulent energy dissipation.In order to select an optimum blade shape and verify its effectiveness, theY-component and X-component of fluid velocity are the drilling fluid dominant orientation. These two kinds of fluid velocity become larger smoothly and gradually, which proves the reasonable design of the surface profile. (2) The Z-component of fluid velocity of both types of blade is very small, which shows the little energy dissipation. The Z-component of fluid velocity of the I-type blade is smaller than the II-type blade, which indicates that the former has less energy dissipation. (3) The drilling fluid flows into the turbine blades of the stator. The fluid impacts pressure surface and the suction surface after flowing into the blade. Then it will accelerate along the flow channel. The rotor work flow and pressure energy can be translated into kinetic energy of the rotor mechanical kinetic energy. (4) The pressure field surface pressure distribution from the inlet to the outlet ends in smooth descending order. The turning point of the leading edge of the blade is greater than the blade suction, from the description of the pressure gradient of the output torque of the size. The greater pressure gradient of the I-type leaf blade shows that it has more torque gradient than the II-type blade. (5) The small turbulent energy dissipation conforms to the Z-component of fluid velocity. The turbulent energy dissipation of the I-type blade is smaller than the II-type blade, which indicates that the former is better. In summary, the overall smooth flow and the low eddy current loss prove that both types of turbine blades correction are feasible. The results meet all the requirements. After careful comparative analysis, the I-type blade turns out to be more reasonable and suitable to manufacture the physical prototype for test.The flow field simulation figure shows the following. (1) The Turbodrill blade is processed using fine casting molding. First, based on the blade structure and its curvature, a fine model  is proceThe turbodrill prototype is composed of two turbine sections, which has one hundred turbine blades. In order to verify the effect of the turbodrill coring blade design, the single turbine section was tested on the drill test bench in Tianjin Dagang mechanical manufacturing companies on July 14, 2013. As shown in 3) as the drilling fluid, the maximal output torque and maximal rotational speed of the single turbine section are 394 N·m and 564 rpm, respectively. Considering the actual density of the drilling fluid is the 1.25–1.3 times of water and that the output torque is proportional to the density of the drilling fluid, the maximal output torque of the turbodrill prototype with two turbine sections can reach up to 985–1025 N·m, which is equal to the design goal. With the increase of the drilling fluid, the rotational speed will decrease slightly. The test results are equal to the design goals, which can verify the accuracy in surface profile indirectly.Considering high pressure and temperature, hydraulic units with high torque and low speed are applied. The turbodrill is developed with optimized parameters. The surface profiles of the turbodrill are designed on the basis of dimensionless coefficients.The effect of the blade profile's change on the first curvature is figured out: the first curvature of the blade front virtually affects the blade front end. Lower curvature leads to higher front and smoother flat. First curvature of the blade back virtually affects the blade back end. Lower curvature leads to higher turbodrill blade profile. ANSYS CFD. The effects of different fluid discharge and viscosity on hydraulic property are performed. The optimized design fitting curve is confirmed.The single-period model is developed throughThe basic design methodology and method of coring turbodrills used in crystallized section are efficacious. The results show that the design meets the deep hard rocks mineral exploration application and provides good references for further study.


Background: Lithiasis during pregnancy can be a serious problem representing a danger to both the mother and the fetus. Surgical intervention is needed in approximately one-third of patients reporting pain despite analgesia and/or signs of persistent infection and obstruction, but there is a lack of consensus in the scientific literature as to the use of the most appropriate procedure to treat this condition.Case Presentation: We describe our experience in the treatment of a complicated reno-ureteral lithiasis in a 27-year-old patient in the first trimester of pregnancy. The patient had a calcified ureteral stent with associated stone formation in the right kidney and a bladder stone at the distal extremity of the stent. She was treated by a combined approach by percutaneous nephrolithotripsy and transurethral cystolithotripsy. The procedure we performed was effective.Conclusion: Our experience reinforces the feasibility and safety of the kidney stone removal by the percutaneous approach also in a pregnant patient and supports the recommendations of the European guidelines: “in experienced centers, where necessary, percutaneous nephrolithotripsy should be considered.” The technical precautions taken have proven to be valid and are supported by the current literature. Therefore, we feel they can be recommended. Renal colic, infection, and obstruction are associated with premature rupture of membranes, which carry an increased risk of morbidity and mortality to the newborn.1K2 However, surgical intervention is needed in approximately one-third of patients, who report pain despite analgesia and/or show signs of persistent infection and obstruction.The majority of pregnant patients with symptomatic calculi (50%–80%) pass their stones spontaneously.4 The decision rests with the individual surgeon and these procedures should be performed only in experienced centers. Therefore, according to the EAU guidelines, these procedures can be defined as feasible but cannot be recommended. We want to contribute to the scientific debate describing our experience in one case of complicated reno-ureteral lithiasis in a pregnant patient at the end of the first trimester.There is a lack of consensus in the scientific literature as to the use of the most appropriate procedure to treat this condition. According to the European Association of Urology (EAU) Guidelines (2015), if spontaneous passage does not occur, or if complications develop, placement of a ureteral stent or a percutaneous nephrostomy tube is necessary. Unfortunately, these treatments are often poorly tolerated and require a number of replacements during pregnancy, given the high likelihood of rapid encrustation. To avoid these problems, according to the EAU guidelines, in the case of renal calculi or pushed-up upper ureteral calculi, retrograde endoscopic and percutaneous nephrolithotripsy may be performed during pregnancy.The patient is a 27-year-old woman, who had previously suffered from bilateral kidney stones, was hepatitis C virus (HCV) positive, and had a history of recreational and pharmacologic drug abuse.In 2012 the woman had been first referred to our center with a complaint of right-side reno-ureteral colics associated with same-side hydronephrosis and fever (38°C). Abdominal CT scan showed an obstructive stone formation at the level of the ureteropelvic junction (13 mm) and an 11 mm stone in the middle calix.We treated the patient with antibiotics and with the placement of a Double-J ureteral stent. The patient was discharged 2 days after the procedure. At the time of discharge, she was placed on waiting list for definitive treatment of the renal lithiasis.However, all subsequent attempts to contact the patient by phone, starting from 1 month after discharge, were unsuccessful.In October 2014, the patient returned to our center complaining of a recurrence of right-side reno-ureteral colics accompanied by some episodes of hematuria, irritation of the lower urinary tract, and high fever (as much as 39°C).The patient was in the 13th week of pregnancy: renal and bladder echotomography revealed the presence of a stone formation of about 4 cm in the renal pelvis and in the mid and lower renal caliceal group that was encrusted on the calcified proximal end of the Double-J stent. The right-side kidney was also affected by second-degree hydronephrosis. Another large stone of about 4.5 cm was found at the distal (bladder) end of the stent, around its tail. There were also multiple calcifications along the ureteral tract.The patient was admitted to our unit, and on the same day she underwent urgent pyelo-caliceal puncture of a posterior lower pole calix under ultrasound guidance, with positioning of a nephrostomy tube. On the third day after admission, fever had resolved, but the patient still reported flank and hypogastric pain and had marked symptoms of bladder irritation. The patient had also expressed concern about the need for frequent replacement of the nephrostomy tube.To address these issues, we opted for a definitive solution, by means of percutaneous lithotripsy of the kidney and bladder stones and removal of the ureteral stent after the necessary lithotripsy of the stones along the ureter.The patient was placed in a supine position with legs slightly spread ; we perfWe then performed laser lithotripsy by means of antegrade flexible ureteroscopy on the many calcifications along the Double-J ureteral stent that anchored it to the ureter. This second phase lasted 20 minutes.Maintaining the patient in the same position, the rigid cystoscope was then inserted into the bladder and the stone on the distal end of the Double-J stent was fragmented through ballistic and ultrasound energy probe. The ureteral catheter was then removed percutaneously. This third phase lasted 40 minutes.©) and a vesical catheter were put in place.Finally, a re-entry Malecot nephrostomy catheter 16F  of percutaneous nephrolithotripsy in pregnant patients. Our case report confirms that the approach we used is feasible and safe and supports the recommendations of the European guidelines: in experienced centers, where necessary, more invasive approaches like percutaneous nephrolithotripsy should be considered in the treatment of renal lithiasis during pregnancy. The technical precautions taken have proven to be valid; therefore, we believe they can be recommended in clinical practice.