The consequence of the malignant transformation of melanocytes is cutaneous melanoma (MMC); the frequency of this disease is increasing especially in whites. The increased incidence in recent decades is due to the more intense exposure to the ultraviolet B radiation (UVR-B) , in addiOur study was conducted in the Surgical Clinics of Clinical Emergency County Hospital Oradea and Pelican Hospital from Oradea, in collaboration with Oncology Institute Prof. Dr. Ion Chiricuţă from Cluj Napoca, for a period of 4 years (from 2010 to 2013), on a sample of 151 patients diagnosed with melanoma, in different stages of evolution.The research was conducted in accordance with the WMA Declaration of Ethical Helsinki - Medical Research Involving Human Principles for Subjects. As well, it was approved by the Commission for internal approval of the research-development of the hospitals mentioned above and by the Ethics Commission of the Council of Faculty of Medicine and Pharmacy, University of Oradea, Oradea, Romania. Each patient included in the study signed an informed consent form.As a result of surgical excision of the tumor formation and of the histopathological exam , 8, the The 62 patients with cutaneous melanoma, with Breslow index between 1–4 mm, followed the biopsy procedure of the sentinel lymph node (SLN), in Oncology Institute form Cluj - Napoca. Overall, 45 patients had a positive SLN and 17 patients had negative SLN. The mortality rate was 5% in patients with positive SLN. By evaluating the death rates according to Breslow index, 65% of patients with Breslow index > 4 mm died. These results correspond with those cited in literature, the rate of survival in a Breslow index < 1 mm was between 95–100%, in a Breslow index 1–2 mm was 80–90%, in a Breslow index from 2.1 to 4 mm was 60–75%, and in a Breslow index > 4 mm is 50%  the metastatic melanoma cells in subcapsular sinus as small cluster or large cluster. In some cases, the lymph node invasion was so important that the melanoma cells destroyed most of the normal lymphoide structure. We had a rare case of spindel cell melanoma.Most patients are going to the doctor in an evolutionary stage of the disease, when there already exists a metastasized melanoma.


This paper presents a novel approach to incorporate the non-stationarities characterised in the GCM outputs, into the Predictor-Predictand Relationships (PPRs) in statistical downscaling models. In this approach, a series of 42 PPRs based on multi-linear regression (MLR) technique were determined for each calendar month using a 20-year moving window moved at a 1-year time step on the predictor data obtained from the NCEP/NCAR reanalysis data archive and observations of precipitation at 3 stations located in Victoria, Australia, for the period 1950–2010. Then the relationships between the constants and coefficients in the PPRs and the statistics of reanalysis data of predictors were determined for the period 1950–2010, for each calendar month. Thereafter, using these relationships with the statistics of the past data of HadCM3 GCM pertaining to the predictors, new PPRs were derived for the periods 1950–69, 1970–89 and 1990–99 for each station. This process yielded a non-stationary downscaling model consisting of a PPR per calendar month for each of the above three periods for each station. The non-stationarities in the climate are characterised by the long-term changes in the statistics of the climate variables and above process enabled relating the non-stationarities in the climate to the PPRs. These new PPRs were then used with the past data of HadCM3, to reproduce the observed precipitation. It was found that the non-stationary MLR based downscaling model was able to produce more accurate simulations of observed precipitation more often than conventional stationary downscaling models developed with MLR and Genetic Programming (GP). General Circulation Models (GCMs) are the main tools used for projection of global climate into the future , and theIn dynamic downscaling, GCM outputs are fed into a Regional Climate Model (RCM) as lateral boundary conditions . The higThe projections of hydroclimatic variables produced in statistical downscaling studies are subject to uncertainties that arise from numerous sources . The sources of uncertainties in a downscaling study include: GHG emission scenarios used to force GCMs, GCMs used to provide inputs to downscaling models, various techniques used for developing downscaling models, non-homogeneity in inputs to downscaling models, specific methodologies employed in developing downscaling models , stationarity assumption of PPRs and stationarity assumption of bias/bias-correction approaches , and the quality of observations against which downscaling models are calibrated . These uTo the date some of the above sources of uncertainties have been investigated in detail and in certain instances potential solutions to reduce the uncertainties that arise from those sources have been developed. As examples: use of multiple GHG emission scenarios to quantify the impact of changes in the anthropogenic GHG emissions on catchment scale climate , 13, 14,It has been found that the constants and coefficients in the PPRs developed using multi-linear regression (MLR) technique can be used to detect non-stationarities in the PPRs , 21. HowThis paper presents a novel approach based on the use of a moving window to incorporate the non-stationarities in the large scale climate in the PPRs in statistical downscaling models. The next sections of the paper provide the details of “Study Area and Data”, “Methodology”, “Results” and “Discussion” in relation to a case study.2) of Grampians Wimmera Mallee Water Corporation (GWMWater) is located in the northwestern part of Victoria, Australia. For the demonstration of the methodology, precipitation stations at Halls Gap , Birchip  and Swan Hill  in the operational area of GWMWater were selected. This study area was selected purely for the demonstration of the methodology detailed in the paper. The annual averages of precipitation at Halls Gap, Birchip and Swan Hill are about 950 mm, 375 mm and 360 mm respectively. These 3 stations were selected in such way that they represent relatively wet, intermediate and relatively dry climate regimes in the study area. The selection of stations representative of relatively wet, intermediate and relatively dry climate regimes enabled the testing of the robustness of the downscaling approaches. The locations of the precipitation stations at Halls Gap, Birchip and Swan Hill are shown in The operational area  of the Queensland Climate Change Centre of Excellence for the period 1950–2010. In the SILO database for infilling the missing daily precipitation values, ordinary kriging method has been used to spatially and temporally interpolate daily rainfall [For the calibration and validation  of the statistical downscaling models, observations of the predictand and reanalysis data pertaining to the predictors are required. For this investigation, daily observed precipitation for the observation stations at Halls Gap, Birchip and Swan Hill were obtained from the SILO database  were obtained from the Programme for Climate Model Diagnosis and Inter-comparison (http://www-pcmdi.llnl.gov/) for the period 1950–1999. The monthly 20C3M outputs of HadCM3 were used for reproducing the past observed precipitation as it allows the assessment of the ability of the downscaling models  in reproducing the observed precipitation with GCM outputs. HadCM3 is one of the GCMs that can properly simulate the precipitation over Australia and the El Niño Southern Oscillation [The monthly reanalysis data pertaining to predictors were obtained for the period 1950–2010 from the National Oceanic and Atmospheric Administration / Earth System Research Laboratory (NOAA/ESRL) Physical Sciences Division. The outputs of HadCM3 (a GCM) pertaining to the 20illation . Therefo1(MLR).In the non-stationary downscaling approach, initially, a series of PPRs  were determined with the MLR technique by using a moving window on the past predictor data obtained from the NCEP/NCAR reanalysis data archive and observations of precipitation at each station. Then the relationships between the constants/coefficients in these PPRs and the statistics of past reanalysis data of predictors were determined. The non-stationarities in the climate are characterised by the variations in the statistics of the climate variables over time. Hence, the above process enabled linking the non-stationarities in the climate to the PPRs. These PPRs developed using reanalysis data were then modified according to the statistics of predictor data pertaining to the past climate simulated by the 20C3M outputs of HadCM3, yielding new PPRs corresponding to the past climate characterised by HadCM3. The ability of these PPRs to reproduce the past catchment scale precipitation with the outputs of a GCM was considered as an indication of the success of the non-stationary modelling approach. The series of PPRs developed using the above moving window approach resembles a non-stationary downscaling model and it is denoted as SDM2(MLR) and SDM2(GP), respectively. The stationary downscaling models SDM2(MLR) and SDM2(GP) are denoted as SDM2 in general. The flow chart in The performance of this non-stationary modelling approach was compared with that of a stationary modelling approach. Under the stationary modelling approach, linear and non-linear downscaling models were developed using MLR and Genetic Programming (GP). These stationary downscaling models developed with MLR and GP are denoted as SDM1)  and Development of stationary downscaling models (SDM2).The next sub-sections provide the details of the steps shown in The atmospheric domain in a statistical downscaling study is the region of the atmosphere corresponding to which the large scale atmospheric information is obtained, for providing inputs to a downscaling model. In this investigation an atmospheric domain that covered the region bounded by the longitudes 135°E—150°E and latitudes 30°S—42.5°S was selected, and it is shown in In statistical downscaling, it is the common practice to select an initial pool of predictors called probable predictors that are the most likely to influence the predictand of interest. The set of probable predictors selected for this study consisted of; 500 hPa, 700 hPa, 850 hPa and 1000 hPa relative humidity; 500 hPa, 700 hPa, 850 hPa and 1000 hPa specific humidity; 500 hPa, 700 hPa, 850 hPa, 1000 hPa air temperature; surface air temperature; 200 hPa, 500 hPa, 700 hPa, 850 hPa and 1000 hPa geopotential heights; mean sea level pressure; surface pressure; surface precipitation rate; 850 hPa zonal wind speed; and 850 hPa meridional wind speed. These probable predictors were selected based on the previous downscaling studies over the same study area , 26, 27.Potential predictors are the most influential predictors on the predictand of interest selected from the pool of probable predictors. The potential predictors vary spatiotemporally as the relationships between the large-scale atmospheric conditions and the catchment scale climate can vary over time and space . In ordeAbove predictor selection procedure assisted in avoiding the influx of any redundant information to the downscaling models. These three potential predictors selected for each calendar month are called the best potential predictors. In 1(MLR), for each calendar month, for each station, two 20-year moving windows were defined in such a way that the 1st and the 2nd moving windows initially covered the 1st and the 2nd 20-years of the reanalysis data of the three best potential predictors (refer to st window was moved until it swept over the whole set of data (1950–2010), and for that, 41 1-year movements were required. Once the 1st window was moved to the position where it covered the data of the period 1971–1990, the 2nd window would have covered the last 20-years of data which corresponded to the period 1991–2010. Thereafter, for each movement of the two windows, data were concatenated for the 2nd window by considering data from 1950 onwards. .For the development of SDMrefer to  and the 1(MLR) were determined for each movement of the 1st moving window by minimising the sum of squared errors between the model-reproduced values and observed precipitation. This phase of the model development is called model calibration. The PPRs of SDM1(MLR) had the format given in Y is the predictand and bi is the coefficient of predictor xi, D is the constant and ε is the Gaussian error. Since i = 3 there are three coefficients b1, b2 and b3 corresponding to the three best potential predictors x1, x2 and x3 respectively.For each 1-year movement of the two windows and also for their original positions, the reanalysis data pertaining to the three best potential predictors were standardised using their means and the standard deviations. Then using these standardised data, the constant and the coefficients of PPRs in SDMst moving window were used to reproduce the observed precipitation pertaining to the 2nd moving window as a validation of the performance of SDM1(MLR). The calibration and validation process yielded a series of 42 PPRs for each calendar month for each station  corresponding to the 1st moving window. The use of moving windows at a 1-year step enabled the identification of fine changes in the PPRs even with a short record of data.Then the PPRs developed for the 11(MLR) are shown in st window . According to b1, b2 and b3 in the majority of the calendar months displayed either an increasing or a decreasing trend over time, with significant fluctuations in certain calendar months (e.g. October).The time series of the coefficients and the constant in the PPRs of SDMA test was then conducted to determine the statistical significance of the linear trends  of each 1(MLR) and the statistics of the best potential predictors over time is a potential way to determine the influence of non-stationarities in the climate on the PPRs over time. For determining the relationships between the PPRs in SDM1(MLR) and the statistics of the best potential predictors, initially, for each calendar month, for each 1-year movement of the 1st window, the mean, the standard deviation and the 25th, 50th, 75th, 95th percentiles of the NCEP/NCAR reanalysis data of the three best potential predictors were computed, for each station. In order to achieve this, 42 PPRs for each calendar month were considered for each station. The 1-year movement of the 1st window yielded the time series of statistics of the reanalysis data of the three best potential predictors. By computing the correlations between each of these statistics and each coefficient/constant in the PPRs, the most influential statistic on each coefficient and the constant was determined. 1(MLR) for each calendar month, including their correlation coefficients (CC) for observation station at Halls Gap as an example. It was seen that the majority of the correlations were strong and statistically significant at the 95% confidence level for all stations.The changes in the statistics of global climate over time are regarded as indications of climate change. Hence, it was realised that relating the changes in the PPRs in SDM1(MLR) developed with the NCEP/NCAR reanalysis outputs according to the statistics of 20C3M outputs of HadCM3 GCM. For this purpose, initially, the variations of each coefficient and the constant of the PPRs in SDM1(MLR) and the most influential statistic of the three best potential predictors were visualized using scatter plots. The next step of the modelling process was to modify the coefficients/constant in the PPRs of SDMth century. Therefore, the last time slice was limited to 10 years. Then using the scatter plots , the following example is considered. In January, the 25th percentile of surface precipitation rate at grid location {} was the most influential statistic (correlation coefficient = -0.85) on the first coefficient (b1) of the MLR based PPR for Halls Gap station } computed from the 20C3M outputs of HadCM3 for a certain period of interest (e.g. 1950–1969) be xi. To find the value of the first coefficient (b1) corresponding to xi, initially, the two points in the scatter } closest to xi on either sides of xi are found. Then, by following the solid arrow line shown in b1) pertaining to xi is found as yi.As a demonstration for the application of linear interpolation to derive new values for the coefficients/constant in the PPRs of SDMtion see . As showtter see  which reth percentile of the surface precipitation rate at grid location {} xj is outside the range of the scatter and there is no known value of coefficient b1 in the scatter pertaining to any xk (>xj), hence interpolation is impossible. In such cases, extrapolation of the values of the coefficient/constant corresponding to the given value of the statistic pertaining to the past GCM data is seen as a solution. However, since extrapolation can introduce large errors to the estimated value of the coefficient/constant, it was not practised.If the value of the most influential statistic of the potential predictor computed from the 20C3M outputs of HadCM3 were outside its range computed from NCEP/NACR reanalysis data, then the coefficient/constant determined using the NCEP/NACR reanalysis data was used without any modification. As an example, in Like any other approach such as fitting a linear or a non-linear curve to the scatter between a constant/coefficient and a statistic of a predictor derived from reanalysis data, the linear interpolation between points in the scatter can also introduce uncertainties to the estimation of the values of the constant/coefficients pertaining to the values of the statistic of the predictor derived from the GCM data. In certain instances the uneven scatter (e.g. scatter with higher data density in certain regions than others) between the constant/coefficients and the statistic of predictor derived from reanalysis data was seen e.g. . In the Once the coefficients and constant of the PPRs were determined corresponding to the statistics of the three best potential predictors pertaining to the 20C3M outputs of HadCM3 for the periods 1950–1969, 1970–1989 and 1990–1999, these new PPRs were used to reproduce the observations of precipitation for each calendar month, for each station using 20C3M outputs of HadCM3. Both reanalysis and GCM outputs contain bias, however, in general, GCM outputs tend to contain more bias than reanalysis outputs that are quality controlled and corrected against observations. The bias in the GCM outputs can propagate into the outputs of a downscaling model. Hence, it is an important task to correct the bias in the GCM outputs before any use. In this investigation, using the monthly bias-correction  the biasIn the application of the monthly bias-correction it is assumed that the bias in the variables over any period beyond the baseline period will remain the same as that of the baseline period. As the baseline period of the monthly bias-correction 1950–1969 was considered. Over the baseline period the monthly bias-correction was applied to the 20C3M outputs of HadCM3 by replacing their means and the standard deviations in each calendar month with the corresponding means and the standard deviations derived from the NCEP/NCAR reanalysis outputs pertaining to the same period. Beyond the baseline period (i.e. 1970–1989 and 1990–1999), the bias in the 20C3M outputs of HadCM3 were corrected by standardising these outputs with their means and standard deviations pertaining to the baseline period and rescaling with the corresponding means and standard deviations derived from the reanalysis outputs. Then the bias corrected 20C3M outputs of HadCM3 were used with those PPRs modified according to the statistics of 20C3M outputs of HadCM3 for the reproduction of observed precipitation for periods: 1950–1969, 1970–1989 and 1990–1999.2) were developed: (1) a downscaling model based on MLR called SDM2(MLR) and (2) a downscaling model based on GP called SDM2(GP). The precipitation observations at the Halls Gap, Birchip and Swan Hill stations and the NCEP/NCAR reanalysis data of the three best potential predictors for the periods 1950–1969 and 1970–1989 were considered for the calibration and validation of SDM2(MLR) and SDM2(GP) respectively. For the calibration and validation of SDM2(MLR) and SDM2(GP), the above two periods were selected as it enabled the comparison of performance of SDM2(MLR) and SDM2(GP) with that of SDM1(MLR) which was calibrated, validated and modified for the same periods. SDM2(MLR) and SDM2(GP) comprised of a set of 12 PPRs at a given station .For each station, two different types of conventional stationary downscaling models (SDM2(MLR), for each calendar month, constants and coefficients of MLR-based PPRs were determined for the calibration period by minimising the sum of squared errors between the outputs of the SDM2(MLR) and observations of precipitation. Thereafter, these PPRs were run with the reanalysis data of the three best potential predictors pertaining to the validation period.In the development of SDM2(GP) for each calendar month, for each observation station, the GP [For the development of SDM, the GP  techniqu2(MLR) and SDM2(GP) were calibrated and validated following the above procedure, they were used with the bias-corrected 20C3M outputs of HadCM3 as inputs for the reproduction of observed precipitation over the periods: 1950–1969, 1970–1989 and 1990–1999.Once SDM1(MLR), SDM2(MLR) and SDM2(GP) is presented in Tables A statistical comparison of the performances of SDM1(MLR) for the stations at Halls Gap, Birchip and Swan Hill were run with NCEP/NCAR reanalysis outputs of potential predictors, it displayed the lowest NMSE in all three time slices in comparison to NMSEs of SDM2(MLR) and SDM2(GP). This was due to the fact that unlike SDM2(MLR) and SDM2(GP) which were only calibrated for period 1950–1969, SDM1(MLR) was calibrated using a 20-year moving window moved at a 1-year time step that included the periods: 1950–1969, 1970–1989 and 1990–1999.According to Tables 1(MLR) was run with the 20C3M outputs of HadCM3, it displayed the smallest NMSE over periods 1970–1989 and 1990–1999 in comparison to that of SDM2(MLR) and SDM2(GP). Also, SDM1(MLR) was able to better reproduce the 50th percentile of observed precipitation than that by SDM2(MLR) and SDM2(GP) in all three time slices. However, SDM2(MLR) was able to capture the 75th and 95th percentiles of observed precipitation better than those by SDM1(MLR) and SDM2(GP), in all three time slices when it was run with 20C3M outputs of HadCM3. Also, in all three time slices, the standard deviation of observed precipitation was better simulated by SDM2(GP) than that by SDM1(MLR) and SDM2(MLR) with the 20C3M outputs of HadCM3.As shown in 1(MLR) was able to display the lowest NMSE over the periods 1950–1969 and 1990–1999. However, it was seen that with the 20C3M outputs of HadCM3 no downscaling model was able to outperform the others in better reproducing any of the statistics (e.g. percentiles) of observed precipitation consistently in all three time slices at Birchip or Swan Hill stations.According to Tables 1(MLR)) were able to display the lowest NMSE at all stations in two of the three time slices with the 20C3M outputs of HadCM3. This indicated that the downscaling models based on the non-stationary approach were able to produce more accurate simulations of observed precipitation more often than linear and non-linear downscaling models based on the conventional stationary approach. For all stationary and non-stationary downscaling models when run with the 20C3M outputs of HadCM3 it was seen that the NMSE was relatively higher for the stations located in the dry and intermediate climate in comparison to that for the station located in the wet climate. This hinted that, irrespective of the downscaling approach, higher degree of error is associated with the simulations produced by the downscaling models pertaining to relatively dry climate.When run with the 20C3M outputs of HadCM3 (past GCM outputs) it was seen that no downscaling approach (stationary or non-stationary) was able to consistently outperform the other approaches in all three time slices at any of the three stations, in terms of normalised mean square error (NMSE). However, the downscaling models based on the non-stationary approach (SDM1(MLR) for future climate, the constants/coefficients of PPRs developed using the reanalysis data of predictors and the observations of precipitation should be updated according to the future climate simulated by the GCM for deducing new non-stationary PPRs pertaining to the future. For that purpose, scatter between the statistics of reanalysis data of predictors and constants/coefficients of PPRs for the past climate and statistics of data of predictors simulated by the GCM for the future are used. In such instances, there is a likelihood that the statistics of predictors derived from GCM data for the future lie outside the range of statistics of predictors derived from the past reanalysis data. This issue can make the model less non-stationary, as extrapolation of a value of a constant/coefficient outside the range of reanalysis data is discouraged. Such likelihood, will be higher in the distant future and smaller in the near future and may make the non-stationary downscaling model developed for the distant future to be more stationary rather than non-stationary. However, with time, the continuous updating of the scatter between the statistics of the predictors derived from reanalysis data which is expanding over time and the constants/coefficients in the PPRs, will minimize of likelihood of having the statistics of the predictors derived from GCM data for future to lie outside the range of the reanalysis data. Alternatively, a non-linear regression technique such as Genetic Programming can be used to develop a relationship between the values of a statistic of a predictor derived from the reanalysis data and the values of a coefficient/constant in the PPR of interest. Then this non-linear regression relationship can be used with the values of the statistic of the predictor derived from a GCM database which lie outside the range of past reanalysis data to determine the corresponding values of the coefficient/constant in the PPR. This regression based approach can even be used in conjunction with the already proposed continuous updating of the scatter between the statistics of the predictors derived from reanalysis data and the constants/coefficients in the PPRs.In the application of the SDM


It is possible to understand the process of healing from a holistic perspective. According to the life mission theory, we can stretch our existence and lower our quality of life when we are in crises, to survive and adapt, and we can relax to increase our quality of life when we later have resources for healing. The holistic process theory explains how this healing comes about: Healing happens in a state of consciousness exactly opposite to the state of crises. The patient enters the “holistic state of healing” when the (1) patient and (2) the physician have a perspective in accordance with life, (3) a safe environment, (4) personal resources, (5) the patient has the will to live, (6) the patient and (7) the physician have the intention of healing, (8) the trust of the patient in the physician, and (9) sufficient holding. The holding must be fivefold, giving the patient (1) acknowledgment, (2) awareness, (3) respect, (4) care, and (5) acceptance. The holistic process has three obligatory steps: (1) to feel, (2) to understand, and (3) to let go of negative decisions. This paper presents a theory for the holistic process of healing, and lists the necessities for holistic therapy restoring the quality of life, health, and ability to function of the patient.


The mechanical strength of an Al-30% Si alloy in the mushy zone was estimated by using a novel centrifugation apparatus. In the apparatus, the alloy melt was partially solidified, forming a porous structure made of primary Si platelets (Si foam) while cooling. Subsequently, pressure generated by centrifugal force pushed the liquid phase out of the foam. The estimated mechanical strength of the Si foam in the temperature range 850–993 K was very low (62 kPa to 81 kPa). This is about two orders of magnitude lower than the mechanical strength at room temperature as measured by compressive tests. When the centrifugal stress was higher than the mechanical strength of the foam, the foam fractured, and the primary Si crystallites were extracted along with the Al-rich melt. Therefore, to maximize the centrifugal separation efficiency of the Al-30% Si alloy, the centrifugal stress should be in the range of 62–81 kPa. The solvent refining process has been considered a promising alternative to the Siemens technique or to fluidized bed technique to produce solar-grade Si (SOG-Si) for solar cells . In solv1 to T2 in 2 to T3). After the separation process, a porous Si foam remains in the crucible. Using the novel centrifugal separation technique, we successfully obtained high-purity primary Si from Al–Si–Fe alloys and Al–Si hypereutectic alloys [First, primary Si crystallizes while the Si-metal alloy placed in a crucible solidified . Recovery-1 is the weight ratio of the Si foam to its initial melt, and Recovery-2 is the weight ratio of the Si flakes, obtained after acid leaching the Si foam, to the melt. The morphologies of the Si foam and the Si crystallites were observed by optical microscopy , scanning electron microscopy  coupled with energy dispersive X-ray spectroscopy , and engineering computed tomography . X-ray fluorescence  was used for the elemental analysis of the Si foams. Open pores were determined by measuring the densities and apparent densities of the Si foams. Closed pores were quantified by using the theoretical densities of the Si foams. The theoretical densities of the Si foams were calculated by using both theoretical densities of pure Si (2329 kg/m3) and Al (2700 kg/m3) and the ratio of Al to Si in a Si foam measured by XRF. Size and aspect ratio of the pores in the Si foams were measured by using ImageJ, image analysis software (version 1.48v) [3 using a precision diamond saw. The compressive tests with a static strain rate of 1.25 × 10−3/s were conducted at RT using a universal testing machine . The compressive strength in this study was defined as the maximum strength just before the breakdown of the specimen.A schematic drawing of the novel centrifugal separation apparatus is provided in ure Si 23 kg/m3 anSi foams were produced at various RSs from 300 rpm to 800 rpm. Higher RSs led to the removal of a larger amount of Al-rich melt, based on the analysis of the cross-sectional areas of the foams with OM after cutting them in half, as shown in It is of importance to note that the relatively higher Recovery-2 of the foams fabricated at 300 rpm and 400 rpm was due to the larger amount of Al remaining after acid leaching. This was confirmed by an elemental analysis with XRF, as summarized in P is the pressure at r, i.e., the length from the axis of rotation to the center of the Si foam, ω is the angular velocity. For the calculation, r was set at 9.75 cm based on the geometry of the centrifuge used in this study. The centrifugal stress was almost solely exerted on the foam, which stayed in the crucible once the melt remaining in the crucible was removed. When the centrifuge started rotating, the remaining melt was promptly removed to the container within a few seconds. This is because the centrifugal force was much greater than the capillary force at the outlet channel. The capillary force restrained the melt within the crucible before centrifugation. The estimated mechanical strength of the Si foams during centrifugation in the temperature range of 850–993 K was in the range of 62–81 kPa, which is about two orders of magnitude lower than the mechanical strength of the foam at RT. The mechanical strength of Si foams during centrifugation was estimated by comparing the data sets of the recoveries and the microstructures of Si foams (discussed above) to the centrifugal stresses generated by centrifugal force. As shown in The mechanical strengths of the Si foams fabricated at various RSs were measured at RT by compressive tests, as shown in The Si foams fabricated at various RSs in the present study shows two different mechanical behaviors from general porous materials. First, the mechanical strength of the Si foam fabricated at 800 rpm was not governed by factors known to control the mechanical strength of general porous materials. According to previous reports, the mechanical strength of general porous materials is governed by several factors such as distribution, size, and the aspect ratio of pores and porosity ,34. HoweOne thing should be mentioned here. Most of the average sizes of pores in (1)The mechanical strength of Si foams in the mushy zone was estimated to maximize the efficiency of separating Si from the Al–Si alloy using a novel centrifuge.(2)The estimated mechanical strength of Si foams during centrifugation in the temperature range of 850–993 K was in the range of 62–81 kPa, which is about two orders of magnitude lower than the mechanical strength of the foam at RT (1.3–3.8 MPa).(3)To maximize the separating efficiency of Si from an Al-30% Si alloy, the optimal RS must exert a centrifugal stress in the range of 62–81 kPa.


This paper presents a novel experimental design for complex structural health monitoring (SHM) studies achieved by integrating 3D printing technologies, high-resolution laser displacement sensors, and multiscale entropy SHM theory. A seven-story structure with a variety of composite bracing systems was constructed using a dual-material 3D printer. A wireless Bluetooth vibration speaker was used to excite the ground floor of the structure, and high-resolution laser displacement sensors (1-μm resolution) were used to monitor the displacement history on different floors. Our results showed that the multiscale entropy SHM method could detect damage on the 3D-printed structures. The results of this study demonstrate that integrating 3D printing technologies and high-resolution laser displacement sensors enables the design of cheap, fast processing, complex, small-scale civil structures for future SHM studies. The novel experimental design proposed in this study provides a suitable platform for investigating the validity and sensitivity of SHM in different composite structures and damage conditions for real life applications in the future. In recent years, 3D printing technologies have emerged as a promising method for creating complex materials and structures. Such technologies not only provide an affordable means of creating complex models, but they also enable the design and construction of complex geometric objects ,2,3. TheScholars have shown that 3D printing technologies enable the fabrication of complicated 3D microstructures with a broad range of materials. For example, polylactide (PLA), acrylonitrile butadiene styrene, and a wide range of polymer materials have been used extensively in low-cost 3D printers. Furthermore, an innovative selective laser sintering approach has been reported to have enabled the production of ceramics and metals with a resolution of less than 30 μm ,5,6. AnoDespite recent developments in 3D printing technologies, controlling the geometry of objects is usually simple, whereas controlling their mechanical properties is difficult. However, recent studies have shown that the elastic properties of materials can be controlled by designing microstructures ,11,12. WThe standard process of SHM can be categorized into four levels: detection of the presence of damage, assessment of the damage location, quantification of the damage, and prediction of service life . Many reAlthough many damage detection algorithms based on measured vibration data are developed to detect possible damages in lab structures, the issue of how to conduct complex damage conditions in the experiments has always been a tough challenge. In this study, the idea is to utilize the advantage of high-resolution laser displacement sensors and precise 3D printing technology in damage simulation to demonstrate that a novel structural health monitoring system can be developed for studying complex damage conditions in SHM. We used 3D printing technologies to create a seven-story specimen and a variety of composite bracing systems to demonstrate the capability of realizing high-resolution complex structural models. A Bluetooth wireless vibration speaker was attached to the base of the 3D-printed structure to excite the structure. High-resolution laser displacement sensors (1-μm resolution) were used to monitor the displacement history of the different floors. A multiscale entropy SHM method was used to demonstrate that the novel experimental approach provides an effective platform for SHM studies for complex structures and composite materials under various damage conditions. This platform also serves as a systematic method of studying novel composite materials for civil engineering applications  and investigating their damage.A seven-story structure was designed based on an experimental model in a previous study . The dimA dual-material 3D printer, Ultimaker 3 Extended , with two 0.4 mm nozzles was used to print the seven-story structure and the bracing systems. The structure was printed using PLA. Supporting materials between floors were printed using polyvinyl alcohol (PVA). CURA 2.5 (Ultimaker B.V.) was used to slice the model. The structure of the supporting material and the slicing results are shown in As shown in A Bluetooth vibration speaker  was used to excite the specimen. Two high-resolution laser displacement sensors  were used to monitor the displacement history. The measuring range was 30 ± 5 mm, and the resolution was 1 μm. The data were transferred to a computer via an amplifier  and a data acquisition (DAQ) system , and they were collected using LabVIEW , as shown in A 3D-printed foundation was designed to connect the structure and the vibration speaker. The seven-story structure was fixed on top of the foundation, with the vibration speaker attached to the left side of the foundation for the input of horizontal displacements. A mass of 202 g (±2.17 g) was placed on each floor to simulate the actual structural characteristics. Structural damage was simulated by removing the installed bracing systems from selected floors or by replacing the bracing on the first floor with composite bracing systems. In all experiments, white noise was the input to simulate the ambient vibration in the horizontal direction. In the experiments, 60 s of data were collected 1–2 min after the input of white noise. The displacement of the monitoring floor was determined with a sampling rate of 500 Hz. The measuring point of each floor was set on one column of the structure, at the height of the floor, as shown in the As the entropy-based method has been demonstrated to be more sensitive in detecting minor damage, compared to the traditional SHM method, it is adopted in this study. The multiscale concept was applied to convert an original vibration time history into signals at different time scales. First, a new time series The similarity of a system can be quantified by calculating the entropy value of a measured time series. For the time series Other templates can be substituted for similarity comparisons with template i, and the average degree of similarity can be further calculated as follows:These steps are repeated to obtain the average degree of similarity Cross-sample entropy (Cross-SampEn) is utilized to evaluate the degree of asynchrony or dissimilarity between two sensors from the same system. The similarity degree between templates The average similarity probability of the template of length m can be calculated using the following equation:By assembling templates with length m + 1, the average similarity probability A damage index (DI) is proposed, and the location of damage in a structure can be determined. For a structure with N stories, the MSCE of each story is expressed as the Cross-SampEn curve of the adjacent upper story to each story at a different scale. The MSCE curves for the healthy and damaged conditions of the structure are represented as H and D, respectively, and the subscripts depict the floor numbers; for example, The DI can be calculated as follows:A positive DI value indicates the existence of damage on the floor as the involved structural damage causes an increase in dissimilarity in the individual structural responses, and a negative value indicates no damage on the floor.The proposed algorithm was first applied to detect the damage condition of the scaled-down specimen by removing sold bracing which was the same damage scenario induced in the previous experimental study . Ten damAs shown in In the case of two-story damage, a similar trend to that of the single-story damage case was observed. The three damage curves (for the cases with damage on the first and second floors (1&2F), the third and fourth floors (3&4F), and the sixth and seventh floors (6&7F)) are shown to be higher, reflecting an increase in complexity from the vibration signal. It demonstrates that the structure was prone to instability due to the removal of the bracing. The 3&4F and 6&7F damage case curves are shown to deviate considerably from the reference healthy curve, thereby providing an easy method of detecting possible damage to the structure.A notable phenomenon can be observed in In the case of four-story damage, the MSE curve for cases with damage on the first, second, third, and fourth floors (1&2&3&4F) exhibits the highest peak, indicating that the corresponding four floors had the highest damage levels. The gap between the two curves (1&2&3&4F and 4&5&6&7F damage cases) is enlarged, indicating a major difference between damage occurring on the superstructure and on the substructure.The 10 damage cases were further used to verify the feasibility of replicating the complicated laboratory or on-site experiments through the proposed SHM method.In the case of single-story damage, as shown in Three damage cases were simulated by removing the bracing from the two stories; thus, the damage was located on the 1&2F, 3&4F, and 6&7F. The MSCE diagrams for 4F/7F and the corresponding DI values are shown in To thoroughly examine the proposed method, two damage cases were further simulated by removing the bracing from three stories; thus, the damage was located on the 1&2&3F and the 5&6&7F. The MSCE diagrams for 4F/7F and the corresponding DI values are illustrated in The most severe damage cases were simulated by removing the bracing from four stories; thus, the damage was located on 1&2&3&4F and 4&5&6&7F. The MSCE diagrams for 4F/7F and the corresponding DI values are depicted in The degree of damage was examined using the composite material as the bracing element. Four composite structures were introduced: the honeycomb infill bracing, the honeycomb sandwich bracing, the damaged honeycomb infill bracing, and the honeycomb bracing. In contrast to the cases described in the previous section, sensors were deployed on the ground and fourth floors. The damage was simulated by replacing the two bracing systems on the first story with composite bracings, and the case of the honeycomb infill bracing was treated as the reference case for damage degree detection. The MSCE curve (G/4F) and the corresponding DI values are shown in In this paper, 3D printing technologies are demonstrated to provide a fast and low-cost fabrication method for creating complicated composite structures. A seven-story specimen with various types of composite bracing was printed for SHM experiments in this study. High-resolution (1 μm) laser displacement sensors enabled the monitoring of the dynamics of the specimen under white noise excitation from a Bluetooth vibration speaker. The results reveal that the MSE derived from single laser displacement monitoring on the uppermost story could distinguish the damage of the specimen. Furthermore, the MSCE derived from the fourth story and the ground floor could specify the damage in the substructure of the specimen. This experimental setup provides a novel platform for future fundamental SHM studies using 3D printing technologies. We believe that the integration of 3D printing technologies into SHM studies could advance the understanding of existing SHM theories. For example, it is possible to reconstruct a 3D image of a real damaged structure in real life applications and fabricate the reconstructed model by using 3D printing technologies in order to investigate the accuracy and performance of existing SHM theories.


Neoceratodus forsteri and Protopterus dolloi) and a urodele amphibian . We aimed to get insights into the possible organization of the forebrain in the common ancestor of all tetrapods because of the pivotal phylogenetic significance of these two groups, being lungfishes the closest living relatives of tetrapods, and representing urodeles a model of simple brain organization with most shared features with amniotes. These transcription factors display regionally restricted expression domains in adult (juvenile) brains that are best interpreted according to the current prosomeric model. The regional patterns observed serve to identify regions and compare between the three species studied, and with previous data reported mainly for amniotes. We corroborate that Nkx2.1 and Isl1 expressions have very similar topologies in the forebrain. Common features in all sarcopterygians (lungfishes and tetrapods) have been observed, such as the Isl1 expression in most striatal neurons, whereas Nkx2.1 is restricted to migrated interneurons that reach the ventral pallium (VP). In the pallidal derivatives, the combination of both markers allows the identification of the boundaries between the ventral septum, the bed nucleus of the stria terminalis (BST) and the preoptic commissural region. In addition, the high Isl1 expression in the central amygdala (CeA), its boundary with the lateral amygdala (LA), and the scattered Nkx2.1 expression in the medial amygdala (MeA) are also shared features. The alar and basal hypothalamic territories, and the prethalamus and posterior tubercle (TP) in the diencephalon, have maintained a common pattern of expression. This regional distribution of Isl1 and Nkx2.1 observed in the forebrain of urodeles and lungfishes contributes further to our understanding of the first terrestrial vertebrates and their ancestors.Expression patterns of Nkx2.1 and Islet-1 (Isl1), which encode transcription factors that are key in the regionalization of the forebrain, were analyzed by combined immunohistochemical methods in young adult specimens of two lungfishes ( Developmental processes occurring from the neural plate stages entail drastic morphological changes and the topological arrangement of the forebrain subdivisions is a consequence of the location of their primordia in the neural plate. This organization is driven by the combination of basic genetic codes, which are strongly conserved in the different animal models, and the mechanisms leading to the formation and patterning of the brain are highly conserved in evolution. This is specially clear when the forebrain organization of different vertebrates is interpreted according to the prosomeric model based on detailed comparison of diverse developmental gene expression patterns  and the African genus Protopterus (four species). The brains of lungfishes also exhibit substantial variation and although lepidosirenid lungfishes have extremely simple brains that look in many ways like those of urodeles, Neoceratodusforsteri has more complex brain organization. Actually, in early comparative neuroanatomy the brain of urodeles was chosen to focus on the species with the simplest brains . Of note, the brains of anuran amphibians are substantially more complex than those of urodeles, which show poorly differentiated brain structures probably due to secondary simplification , which are very conserved in the evolution, has been shown to be an excellent tool to highlight details of telencephalic and hypothalamic regionalization that are readily comparable across species  and the lungfishes Protopterus dolloi (n = 9) and Neoceratodus fosteri (n = 6) were used. The specimens of the urodele were obtained from laboratory stock in the Department of Cell Biology, University Complutense, Madrid. The African lungfish (P. dolloi) were purchased from commercial suppliers , and the Australian lungfish (N. forsteri) were obtained from Jindalee International Pty Limited in Milton, Queensland, an approved breeder and exporter. The original research reported herein was performed according to the regulations and laws established by the European Union (2010/63/EU) and Spain  after approval from the Complutense University to conduct the experiments described. In addition, the N. forsteri specimens were handled by Dr. Glenn R. Northcutt  and the initial steps of perfusion and fixation were conducted in the USA (the brains were then shipped to Spain) following the standards established by the Institutional Animal Care and Use Committee at the University of California, San Diego, for the care and handling of animals in research.For the present study, juveniles of the urodele amphibian 4, 3.7% formaldehyde). The brains were removed and kept in the same fixative for 2–3 h. Subsequently, they were immersed in a solution of 30% sucrose in PB for 4–6 h at 4°C until they sank, then embedded in a solution of 20% gelatin with 30% sucrose in PB, and stored for 6 h in a 3.7% formaldehyde solution at 4°C. The brains were cut on a freezing microtome at 30–40 μm in the transverse or sagittal plane, and sections were collected and rinsed in cold PB.The animals were deeply anesthetized by immersion in 0.01% tricaine methanesulfonate solution  and perfused transcardially with physiological saline followed by 200 ml of cold 4% paraformaldehyde in a 0.1 M phosphate buffer , or MEMFA  first incubation was conducted for 48 h at 4°C in the dilution of each primary antibody: mouse anti-Isl1 primary antibody , Iowa City, IA, USA. Clone: 39.4D5) or rabbit anti-Nkx2.1 ; and (2) second incubations were for 90 min at room temperature with either Alexa 488-conjugated goat anti-mouse  or Alexa 594-conjugated goat anti-rabbit .To study the relative distribution of the two markers in the same sections, the two-step protocol for immunofluorescence was used with cocktails of pairs of primary and secondary antibodies, at the same dilutions and conditions previously specified: (1) first incubation for 48 h at 4°C in the cocktail mouse anti-Isl1/rabbit anti-Nkx2.1; (2) second incubation for 90 min at room temperature in the cocktail Alexa 488-conjugated goat anti-mouse/Alexa 594-conjugated goat anti-rabbit.In all cases, antibodies were diluted in PB containing 0.5% Triton X-100. After the immunohistochemical steps, the sections were rinsed and mounted on glass slides, which were coverslipped with fluorescence mounting medium, containing 1.5 μg/ml 4′,6-diamidino-2-phenylindole (DAPI) for DNA counterstaining .The antibodies were previously tested in the species used in this study and many of them were used as territory markers in the forebrain  and representative photomicrographs of brain regions with significant labeling were taken and presented in Figures The nomenclature used is essentially the same followed in previous recent studies of urodele and lungfish brains , located medial to the BST Figures , 3H,I. IFinally, the preoptic area (POA) in both animal models was defined by the vz expression of Nkx2.1, whereas Isl1 was restricted to the adjacent mantle zone Figures , 7A–C.Neoceratodus Isl1 expressing cells were found scattered in the outermost portion, probably arising from adjacent territories  of this animals is a very reduced structure .In the medial wall of the telencephalic hemispheres, the septum is greatly reduced in urodeles , would also reflect a down-regulation in its expression.Interestingly, genetic studies in mammals have shown that development of the bulk of cortical interneurons depends on Nkx2.1 function  along to its vomeronasal connections and the distinct expression of the homeodomain transcription factor Orthopedia , strengthening a common pattern in the alar region , is defined by the lack of Nkx2.1/Isl1, whereas ventrally the SC within the subparaventricular area (SPa) is rich in Isl1 in all the vertebrates analyzed , like in all the vertebrates studied . This situation is similar to that observed in anuran amphibians, reptiles and mammals , in alar (Isl1) and basal (Isl1 and Nkx2.1) regions (see Moreno et al., Finally, basal forebrain expression of Nkx2.1 has been demonstrated to extend back to include the p3 basal plate in the mouse (Puelles et al., In this study, we have conducted a detailed analysis of the regional expression of Isl1 and Nkx2.1, two transcription factors of fundamental relevance in the organization of numerous regions of the forebrain. Although we are aware that these markers do not fully define histological domains, their expressions have been described in homologous regions in different species, and they are useful in the attempt of recognizing particular domains. Given the difficulty for obtaining lungfish embryos, we have taken advance of the fact that the proteins encoded by these two genes are easily detected by immunohistochemistry even after development is completed. Furthermore, since both lungfishes and urodeles show little neuron migration, the localization of the expression is largely comparable to the situation during development.The regional patterns observed have served to identify regions and compare between the three species studied and with previous data reported mainly for amniotes. We have corroborated that the expression of the genes that encode the transcription factors Nkx2.1 and Isl1 have very similar topologies in their forebrain expression. Thus, major features shared for all sarcopterygians have highlighted the putative primitive condition of the organization of the telencephalon, especially the subpallium. Particularly, in the striatum the Isl1 expression is found in most cells, primarily projection neurons, whereas Nkx2.1 is restricted to migrated interneurons that reach the VP. In the pallidal derivatives, the combination allows the identification of the boundaries between the ventral septum, the BST and the preoptic commissural region. In addition, the high Isl1 expression in the CeA, its dorsal boundary with the LA, and the scattered Nkx2.1 expression in the MeA are also shared features. The alar and basal hypothalamic territories, and the prethalamus and TP in the diencephalon, have maintained a general pattern of expression.All authors had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. AG and NM devised the study. JL and RM designed and supervised the experiments with lungfishes and urodeles, respectively, and were the primary contributors to the data analysis. SJ and DL performed most of the experiments. NM led the figure preparation and wrote the majority of the article, further completed and edited by AG. All authors approved the article.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The colorectal neoplasm is the fourth most common malignancy among males and the third among females. In the Western world is estimated that 5% of the population will develop it, making this disease a major public health problem. . To analyze the prevalence of the polymorphism -765G / C region of the COX-2 gene in colorectal cancer patients compared to a control group, analyzing the possible association between this polymorphism and susceptibility to colorectal cancer This is a case-control study with 85 participants. Were selected 25 with colorectal cancer (case group) and 60 participants without colorectal neoplasia (control group). The molecular genetic analysis was perform to identify the polymorphism -765G / C COX2 gene with standard literature technique. In addition, patient’s clinical and pathological data were analyzed.  There was a light increase in prevalence between men in the case group, although this difference was not statistically significant. The results showed a high prevalence of GC and CC genotype in individuals with colorectal cancer, demonstrating an association between the presence of the polymorphism in the COX2 gene and susceptibility to colorectal cancer in this pattern (p=0.02). Similarly, there was also difference in allele frequencies in the groups. When patients with cancer were separated by tumor location, there was a higher prevalence of polymorphism in the left colon (p=0.02).  The polymorphism in the COX2 gene is associated with increased susceptibility to colorectal cancer, specially rectosigmoid tumors. The colorectal neoplasm is one of the most common malignancies diseases in the world, being the fourth among male and the third in female, revealing to be an important public health problemIt is believed that prostaglandins are involved in the genesis of CRC. Prostaglandins are small molecules derived from arachidonic acid, which are produced from the enzyme cyclooxygenase (COX). This enzyme is subdivided into COX-1, responsible for physiological activities and therefore is called constitutive, and COX-2 expressed after stimulation of cytokines, growth factor and mitogensIn physiological conditions, COX-2 is expressed in tissue of the gastrointestinal tract at very low levels. However, there is an increase of its expression in CRC, The changes in the COX-2 gene may imply changes in enzyme function and contribute to the inflammatory response or to the increase risk of developing CRCIn this context, the present study aims to estimate the allele and genotype frequencies of the COX-2 gene polymorphism, in order to evaluate the possible association between these frequencies and the susceptibility to CRC.This study was reviewed and approved by the Research Ethics Committee (Protocol no. 884/397) of the Institution. This was a case-control study, conducted in partnership with the Institute of Cancer of Londrina. All patients were previously informed about the objectives and procedures to be performed and had signed the Informed Consent Term.The patients included had CRC with surgical indication. Those who lost follow-up shortly after surgery were excluded. For the control group, individuals without colorectal neoplasm and matched by gender and age group were included in relation to the case group. On the other hand, individuals with a history of other neoplasms or with the presence of polyps during colonoscopy were excluded from the sample.From the clinical information of the patients, demographic and anthropometric data were extracted: gender, age, BMI, history of smoking and alcoholism. Blood analysis provided information on lymphocytometry, hemoglobin, calcium, transferrin, albumin, initial and post-operative carcinoembryonic antigen, from lymphocyte copy (absolute) of the leukogram both at admission and at discharge. In addition, it was evaluated the results of the anatomopathological study and staging of the tumor provided by the pathological report and/or the oncologist. Pre-operative rectosigmoidoscopies/colonoscopies were analyzed, containing the description of the size of the preoperative lesion and the site of the tumor. Also, it was taken into consideration the treatments and operations made, the description of the procedure if it was performed and if it was necessary second or third intervention. In order to obtain information about death and survival, telephone contact with patient or family was used to identify the patient’s current situation.Was performed in peripheral vein in vacuum tubes containing anticoagulant (EDTA). The tubes were centrifuged and the nucleated cells (leukocytes) were separated for further DNA extraction or stored in freezer storage at -80° C until the time of extraction. The patterns were transferred to sterile flasks and DNA was obtained after enzymatic digestion in buffer containing proteinase K and SDS and subsequent extraction with organic solvents (phenol/chloroform).After DNA extraction from the samples, the analysis of the polymorphism -765G / C region of the COX-2 gene was evaluated by the technique of PCR of restriction fragment length polymorphism (PCR-RFLP), being the primer for PCR selected according to the genome database . Amplification conditions are determined by these conditions of temperatures and times: 94° C - 3 min; 94° C, 59° C and 72° C for 60 s each, with 35 cycles and 72° C for 5 min. For the proline allele detection, the parameters will be used: 94° C - 3 min; 94° C, 57° C and 72° C for 30 s each, with 35 cycles and 72° C for 5 min. After PCR the products were subjected to cleavage with the restriction enzyme called BstUI (Bsh 1236I) for 8 h at 37° C. The amplified products were subjected to separation by electrophoresis and 2% agarose gel and were stained by Sybr Safe. Amplified fragments of 134 and 23 base pairs (bp) will indicate homozygous for the wild-type allele (-765GG). A single fragment of 157 base pair will indicate homozygosis for the C allele (-765CC) and the presence of three fragment of 157, 134 and 23 base pair will indicate heterozygosis (-765GC).This study had 85 participants. Were selected 25 of them with CRC (age 56.3±12.2 years) and 60 participants of the control group (age 60.5±6.8 years ). Regarding gender, there was a slightly increase on the prevalence of men in the case group , although this difference was not statistically significant.There was a high prevalence of GC and CC genotype in individuals with CRC, noting the association between the presence of COX2 gene polymorphism and susceptibility to CRC in this sample  with the control group, the GC and CC genotypes prevailed in the individuals carrying the CRC. This association was also preserved by subdividing the neoplasm group according to the site of the occurrence of the primary tumor in the right colon and left colon; however, was more strongly significant in lesions from the left colon. These results are consistent with data from some of previous studies, including the meta-analysis of Cao et al and Peng et al, which analyzed 6774 cases of CRC and 9772 controls,,,There is hypothesized that the COX-2 enzyme is involved in the stimulation of cell proliferation and angiogenesis, in the inhibition of apoptosis and in immunological suppression, all events with carcinogenic potential ,,There are many evidence of the influence of the polymorphism -765 G / C region on the genesis of several tumors, such as prostate, breast, ovary, lung, liver cancer and CRCIn Brazil, COX-2 polymorphism studies and the occurrence of colorectal tumors are scarce, and this study is one of the first reports comparing not only the susceptibility to cancer but also the association with tumor topography. In this context, this study contributes to the characterization of the association of the polymorphism in the COX2 gene with the CRC in the Brazilian population, notably more significant in the retossigmoid lesions. Polymorphism research can provide significant future advances, as it will enable the identification of the individuals most susceptible to the risk of tumors, allowing individualization in the therapeutics. Regarding colorectal neoplasm, polymorphic patients with the C allele were potential candidates to the treatment with anti-inflammatory drugs, especially in cases of left colon cancer.Polymorphism in the COX-2 gene is associated with increased susceptibility to colorectal cancer, especially in tumors of the rectosigmoid segment.


Missing items are common in quality of life (QoL) questionnaires and present a challenge for research in this field. The development of sound strategies of replacement and prevention requires accurate knowledge of their type and determinants.We used the 2003 French Decennial Health Survey of a representative sample of the general population -- including 22,620 adult subjects who completed the SF-36 questionnaire-- to test various socio-demographic, health status and QoL variables as potential predictors of missingness. We constructed logistic regression models for each SF-36 item to identify independent predictors and classify them according to Little and Rubin .The type of missingness was missing at random for half of the items of the SF-36 and missing not at random for the others. None of the items were missing completely at random. Independent predictors of missingness were age, female sex, low scores on the SF-36 subscales and in some cases low educational level, occupation, nationality and poor health status.This study of the SF-36 shows that imputation of missing items is necessary and emphasizes several factors for missingness that should be considered in prevention strategies of missing data. Similar methodologies could be applied to item missingness in other QoL questionnaires. A detailed understanding of their determinants is therefore required to devise appropriate prevention strategies. Some studies have suggested that determinants of missing data in QoL questionnaires are multiple and diverse, and may be socio-demographic  or related to health status  . Howe. Howe3]]e, etc.) ,7-9. TheThe Decennial Health Survey was conducted by the French National Institute of Statistics and Economic Studies (INSEE), between October 2002 and October 2003; a representative sample of the French population was surveyed to provide data on the health status of this population and its demand for health services . The samThe French SF-36 questionnaire ,15 . We also used the socio-demographic and health status variables recorded in the 2003 Decennial Health Survey to distinguish between the MAR and MCAR types: if the probability of missingness for an item was found to depend on a predictor variable but not on its subscale score, the item non-response was classified as "MAR", whereas its was classified as "MCAR" if the probability of missingness depended neither on its subscale score nor on any  predictor variable.The type of missingness was defined according to Little and Rubin ,18: whenLogistic regression models  were conTable Multivariate predictors of missingness are presented in Table Age had a strong and similar effect on missingness for almost all items, with an increase in the proportion of missing data of 10 to 50% per 10 years of age. Data was more frequently missing for women than men for most items but the difference was less systematic than that observed between age groups. Nevertheless, for some items , the risk of missingness was twice as high, or higher, for women than men. Other socio-demographic variables  were also significantly correlated with the risk of missingness: the proportion of missing data for PF5, RP1, VT1, MH3 increased with decreasing educational level. Similarly, missing data was more frequent for PF4, PF5, VT2 and RE3 for "blue collar workers" than other groups and for PF6, PF7, RP4 and GH4 for non-national than French subjects.Missingness increased only for some items with poorer health status: subjects having been hospitalized in the year had higher proportion of missing data for PF1, GH3 and GH5; those with chronic disease(s) for PF9; and subjects with depression as classified by the CES-D for GH1, VT1 and MH4. Subjects with vision problems had higher proportion of missing data for and VT1 and MH3.Low scores on the SF-36 subscales predicted missingness for more than half of the items belonging to their scales . However, there were some more diffuse or "collateral" effects on items belonging to different sub-scales. For example, a low RE subscale score increased the risk of missingness for RE1 and RE3 (MNAR items) and also for RP1 and RP3; a low VT score increased the risk of missingness for PF4, PF5, PF10, RE2 and MH4. The atypical findings for the item BP1 are interesting: for this item ("How much bodily pain...") both univariate and multivariate analyses revealed that the proportion of missing data increased with increasing score on the BP subscale i.e. with decreasing perceived pain. The number of missing items was predictive of missingness for all items, with the OR range being from 1.42 (for BP1) to 2.65 (for PF8).We exploited the French 2003 Decennial Health Survey to investigate diverse socio-demographic, health status and QoL variables as potential predictors of item missingness in the SF-36 questionnaire; we also used the classification proposed by Little and Rubin to characterize missing data processes operating during administration of this questionnaire. In this large representative sample of the French population the proportion of missing items varied between 2% and 7%. The type of missingness was missing at random for 18 items  and missing not at random for the others . No item was missing completely at random (MCAR). MCAR is the only "ignorable" missing data process , so our However, prevention is undoubtedly the optimal approach to the issue of missing data . ConsequFinally, the present study has various limitations that need to be considered. The only moderate fit of some final models indicates that not all the predictors of missingness were identified. An additional limitation is that only an indirect approach could be used to identify the MNAR process. However, direct identification would have required contacting all the subjects to ask them to fully fill in the missing items (which was clearly impossible in this large population-based study).In conclusion, our analysis shows that imputation of missing items in the responses to the SF-36 questionnaire is necessary and identifies several factors that should be carefully considered when designing strategies for the prevention of missing data in the SF-36. Methodologies similar to that we describe here could be used to address the issue of item missingness in other QoL questionnaires.MCAR: Missing completely at random; MAR: Missing At Random; MNAR: Missing Not At Random; QoL: Quality of life; SF-36: Medical Outcome Study 36-item short-form health survey.The authors declare that they have no competing interests.HP participated in the design of the study, performed the statistical analysis and drafted the manuscript. JC and AL conceived the study, participated in its design and helped to draft the manuscript. JC provided administrative, technical and logistic support. All authors read and approved the final manuscript.Scales, items of the SF-36 questionnaire and their scores.Click here for fileUnivariate analysis for factors associated with the missingness for each item of the SF-36.Click here for fileMultivariate analysis for factors associated with the missingness for each item of the SF-36.Click here for file


In Arabidopsis six genes group into the gene family of the organic cation transporters (OCTs). In animals the members of the OCT-family are mostly characterized as polyspecific transporters involved in the homeostasis of solutes, the transport of monoamine neurotransmitters and the transport of choline and carnitine. In plants little is known about function, localisation and regulation of this gene family. Only one protein has been characterized as a carnitine transporter at the plasma membrane so far.AtOCT4, 5 and 6 are up-regulated during drought stress, AtOCT3 and 5 during cold stress and AtOCT 5 and 6 during salt stress treatments.We localized the five uncharacterized members of the Arabidopsis OCT family, designated OCT2-OCT6, via GFP fusions and protoplast transformation to the tonoplast. Expression analysis with RNA Gel Blots showed a distinct, organ-specific expression pattern of the individual genes. With reporter gene fusion of four members we analyzed the tissue specific distribution of OCT2, 3, 4, and 6. In experiments with salt, drought and cold stress, we could show that Localisation of the proteins at the tonoplast and regulation of the gene expression under stress conditions suggests a specific role for the transporters in plant adaptation to environmental stress. Controlled transport processes across membranes of different compartments and between organs are essential for plant nutrient and ion distribution. Changing environmental conditions, like altered nutrient availability, water supply and temperature, require adequate responses by the plant in primary and secondary metabolism. The plant vacuole is a central compartment for this complex process of adaptation to altered environmental conditions. The transport of ions and solutes across the tonoplast is a rapid way to adjust and maintain the required concentrations in the cytoplasm and to avoid the accumulation of toxic substances or ion concentrations -3. For sPhaseolus vulgaris, PvOCT1  is based on the consensus of 11 prediction programmes. For AtOCT1 and AtOCT6 13 transmembrane domains are predicated, for AtOCT2, AtOCT3, and AtOCT4 12 transmembrane domains and for AtOCT5 11. Numbers score the probability of each predicted membrane domain of the AtOCTs.Click here for fileAtOCT2-AtOCT6 using RNA-Gel blot analysisOrgan specific expression . RNA-gel blot analysis showed a specific expression of the individual AtOCTs in Arabidopsis. AtOCT2 revealed a weak expression in flowers and siliques, AtOCT4 and AtOCT6 showed a predominant expression in roots, and AtOCT6 is also expressed in the stem. AtOCT 5 expression was strongest in sink leaves and weaker in mature leaves. AtOCT3 expression is strongest in siliques and a weak signal is detected in flowers, AtOCT2,3, and 5 also showed a weak signal in siliques. As a loading control blots were probed with actin.Click here for fileAtOCT2 PromoterTissue-specific GUS activities under the control of the . In reproductive organs, pollen grains and stigma (A and B) as well as the veins of siliques and young siliques show GUS staining (C and D). Staining in leaves was present in cauline leaves (E) and rosette leaves (F). In mature leaves the signal is found in the vasculature (G), most probably in the phloem (K) whereas in younger leaves the vasculature was not stained, but the leaf blade was (H). Cross sections of young leaves show staining of the epidermis and parenchyma cells (I) and parenchyma cells around the phloem in older leaves (J). In roots the GUS signal was visible in two strands of the central cylinder, the initiation of lateral roots and at the root tips .Click here for file


A statistical model has been proposed in an attempt to integrate coincidental (or synchronous) diagnoses of multiple primary cancers into a general method of analysis. In the context of population-based surveys, such diagnoses form an integral part of the pattern of incidence within the population. Because of clinical surveillance, the diagnosis of subsequent tumours may be advanced in time in comparison with a first primary diagnosis. The model has been used to predict the altered pattern of diagnosis in order to adjust the value of expected numbers. Data from a previously reported survey of bilateral breast cancer have been used to illustrate the model. Analysis in terms of the model showed a 2.6-fold increase in risk for a second primary tumour in the contralateral breast in a series of nearly 22,000 breast-cancer patients. The corresponding risks for 3 main age-ranges (at the time of diagnosis of the first primary) were 5.3 (age 15-44), 3.3 (45-49) and 1.5 (60+). In addition, a maximal risk of 5.0-fold was observed in the series as a whole during the third year after the diagnosis of the first primary.


A number of tests have been described which are thought to be capable of identifying carcinogens without using the actual induction of cancer as an endpoint. This study compared the performance of 6 such tests on a selection of 120 organic chemicals. The tests studies were: (1) mutation of Salmonella typhimurium; (2) cell transformation; (3) degranulation of endoplasmic reticulum; (4) sebaceous gland suppression; (5) tetrazolium reduction and (6) subcutaneous implant. A further 4 tests were examined briefly, but were not included in the complete evaluation. The chemicals were classified into carcinogens (58) and non-carcinogens (62) on the basis of published experimental data, and into 1 of 4 broad chemical classes. There was considerable variation between tests in their ability to predict carcinogenicity, with the cell-transformation test and the bacterial-mutation test being the most accurate (94% and 93% accurate respectively). These 2 tests were considered to be of general use in screening, since they were clearly more accurate than the others. Statistical consideration of various combinations of these tests showed that the use of cell transformation and bacterial mutation together, provide an advantage over the use of either test alone. The inclusion of the other 4 tests in a screening battery predictably resulted in a great increase in overall inaccuracy and loss of discrimination, even though the detection of carcinogens is improved. All the tests were shown to generate both false positive and false negative results, a situation which may be controlled by the use, where possible, of appropriate chemical-class controls, to identify the test which is optimal for the class of chemical under test. Structural analogy may have a part to play in the rapid detection of environmental carcinogens, and some general guidelines for its use are given.


We have investigated in detail the effects of buthionine sulfoximine (BSO), a selective glutathione (GSH) depleting agent, on the GSH contents of a number of normal tissues and three experimental tumours in mice. Significant variations in the rate and degree of GSH depletion and recovery were observed among the normal tissues. Following a dose of 2.5 mmol kg-1 BSO, GSH nadirs were reached by approximately 5 h for the liver and kidney, 8 h for the lung and bone marrow, 12 h for red blood cells (RBCs) and by 24 h for the heart. The degree of depletion was greatest for the kidney (80%), liver (74%) and bone marrow (83%), intermediate for the heart (54%) and lung (40%), and least for RBCs (13%). Recovery of GSH content was fastest for the liver followed in descending order by the kidney, the lung, the bone marrow, RBCs and the heart. In contrast, the rate and extent of GSH depletion and recovery showed considerably less variation among the 3 murine tumours. In the tumours GSH nadirs were reached by 10-12 h. The extent of depletion was about 55-65%. Recovery of GSH levels in the tumours required 48 h or more, a longer period than required by the liver, kidney and lung but shorter than that needed for the bone marrow, heart and RBCs. Attempts to preferentially deplete tumour GSH by exploiting the differences in recovery rates between normal tissues and tumours were only partially successful. Multiple BSO dosing at 16 h intervals allowed the liver to recover between doses, but the recovery in the kidney, lung and bone marrow was only partial and no recovery was seen in the heart. Finally, dose-depletion relationship investigations showed that, with the exception of the lungs, GSH depletion could be achieved in tumours with doses of BSO lower than those required for normal tissues.


Background and purpose External fixators allowing movement during fracture healing are commonly used for treatment of unstable distal radius fractures. The dynamic Dynawrist fixator with the distal pins in metacarpal bone may avoid fixation problems in comminuted fractures and may reduce the risk of nerve injury. We compared anatomical and functional outcome for the well-established Hoffmann compact II non-bridging fixator and for the Dynawrist fixator.Patients and methods 75 patients with unstable distal radius fractures were randomized to treatment with either the Hoffman compact II fixator (the H-group) or the Dynawrist fixator (the D-group). Anatomical and functional variables were recorded preoperatively, postoperatively, and at 6, 12, 24, and 52 weeks. Pain was assessed using the VAS score and function was assessed using DASH score.Results Postoperatively, radial tilt, inclination, and radial length all improved statistically significantly in both groups. At time of removal of the fixators, the H group had superior volar radial tilt. At the 52-week follow-up, there were no statistically significant differences between the groups regarding anatomical variables. At 6 weeks, flexion was greater in the D group but at 12, 24, and 52 weeks flexion was similar in the two groups, as were the other wrist and forearm movements. There were no statistically significant differences between the groups according to VAS and DASH scores. 3 nerve injuries occurred in the H group and 1 in the D group (p = 0.4), all of which were transient.Interpretation The Dynawrist bridging but dynamic fixator gives radiographic and functional outcome similar to that of the Hoffman II compact non-bridging fixator. Different types of external fixation are used for fractures of the distal radius. These include static bridging fixators , non-briNon-bridging fixators, with pins only in the radius, permit wrist movement, but the distal pins may be difficult to insert in comminuted fractures and they may also injure the superficial branch of the distal radial nerve. To avoid these problems, we developed a bridging but dynamic device, the Dynawrist fixator .We compared the radiographic and functional outcome of the well-established non-bridging Hoffman II compact fixator  with thaThis was a consecutive, randomized series of patients with unstable fractures of the distal radius, suitable for non-bridging external fixation. All patients had an AO-type A3 fracture, with an intact volar cortex of the distal fragment of at least 1 cm. The patients were treated at one of 2 hospitals between January 2004 and December 2005.Patients who were included were at least 18 years old, and had one or more of the following fracture deformities: more than 10 degrees of dorsal angulation and/or radial shortening of more than 2 mm compared to the uninjured wrist at the initial radiography. Patients treated with closed reduction and cast were included if they had radiocarpal malalignment of more than 5 mm, a dorsal angulation of more than 5 degrees, or a shortening of the radius of more than 2 mm at the 10-day follow-up. 32 patients were initially treated with plaster cast, which failed to maintain the reduction and required surgery. If surgery was delayed for more the 14 days after the fracture, the patient was not included. Patients who were suffering from dementia or psychiatric diseases, or who had a history of previous fracture in one of the wrists were also excluded.75 patients (64 women) were included. Their mean age, which was similar in both groups, was 62 (20–92) years. 39 patients had fractures of the non-dominant wrist. Mean time from injury to surgery was 4 (0–14) days. All patients were treated with closed reduction; after randomization, 37 patients were treated with the Hoffman II fixator (the H group) and 38 patients were treated with the Dynawrist fixator (the D group).The Regional Ethics Committee approved the study and informed consent was obtained from all patients.In the H group, 2 longitudinal incisions (1 cm long) were made on the dorsum of the wrist, one on either side of Lister’s tubercle. 2 longitudinal incisions were made in the extensor retinaculum, taking precautions to avoid injury to the extensor pollicis longus tendon. 2 Apex pins were then placed parallel to the joint surface in the distal radial fragment, from dorsal to volar, engaging the volar cortex. 2 pins were placed in the radial shaft with open technique. The fracture was reduced using the distal pins as levers .In the D group, 2 Apex pins were placed in the second metacarpal bone parallel to the palm. By open placement technique and with the use of a guide, 2 pins were placed in the radial shaft, parallel to the palm with the forearm in neutral rotation. The springs were adjusted until the radial length was acceptable and the pins in the shaft were parallel to those in the second metacarpal bone .Fluoroscopy was used with both techniques peroperatively, to confirm the placement of the Apex pins and the reduction of the fractures. The surgery was performed in plexus anesthesia. Postoperative radiographs were taken within 24 h of surgery. The operated arm was kept elevated for the first 48 h. All patients had compression bandages around the Apex pins, covering the incisions. The mean fixation time, which was similar in both groups, was 43 (33–59) days.The patients were followed up at 6, 12, 26, and 52 weeks after the operation. An independent observer performed all postoperative measurements.Pre- and postoperatively, at the time of removal of the fixator, and 1 year after the injury, standard anteroposterior and lateral radiographs were taken of the injured wrists. They were compared to the radiographs of the uninjured side taken preoperatively. Radial tilt, ulnar variance, and radial inclination before and after fixation were measured according to standard descriptions  Figure .Range of motion  of the injured wrist and forearm was measured at 6 weeks , and at 12, 26, and 52 weeks. The difference in movement was calculated by measuring ROM of the uninjured side and then subtracting the ROM of the injured side.The total upper extremity function was assessed by self-evaluation, using a Scandinavian translation of the DASH score . We reco2 patients died after the 6-week follow-up, and 2 patients did not want to attend after the 6-week follow-up. These 4 patients were in the H group.A sample size calculation showed that in order to show a difference with a 5% significance level and 80% power, 35 individuals in each group would be needed for radial tilt as outcome, while more than 8,000 individuals would be needed with inclination as the outcome.The patients were randomly allocated into one of the two groups using closed envelopes, which were opened after the patients had given their informed consent.The 95% confidence intervals were calculated as mean values ± 1.96 times the standard errors. To account for the repeated measures, we used a mixed model for repeated measures with an autoregressive correlation structure, to estimate the mean differences between the two products for all time points. The mean differences, 95% confidence intervals, and p-values for comparisons of the mean values at 6-, 12-, 26-, and 52-week follow-ups when evaluating functional measures, and postoperatively, at time of removal, and at 1-year follow-up when evaluating anatomical measures, were calculated using dummy variables for each of the time points in the mixed models. Parameters for the baseline measures were not included in the models dealing with the anatomical variables. However, the baseline measures were accounted for in the calculation of the standard errors and hence the 95% confidence intervals and the p-values.The statistical package SPSS for Windows, release 14, was used for the analyses. We considered p-values less than 0.05 to be statistically significant.Complete data were collected from 71 patients, and partly from 4 patients who dropped out .Preoperatively, the median radial tilt was 29 degrees of dorsal angulation in the H group and 32 in the D group. Postoperatively, the median tilt was 8 degrees of volar angulation in the H group and 2 degrees volar in the D group (p = 0.002).At the time of removal of the fixators, there was still a statistically significant difference in radial tilt: 9 degrees of volar angulation in the H group and 4 degrees in the D group (p = 0.04). At 1 year, the difference was no longer statistically significant. For the other anatomical variables, no statistically significant differences were found .At 6 weeks, the mean loss of flexion was 34 degrees in the H group and 24 degrees in the D group (p = 0.001). At the other times, the differences between the groups were not statistically significant. There were no statistically significant differences between the groups concerning loss of extention, radial and ulnar deviation, supination, or pronation at the different times .There were no statistically significant differences in mean values of the VAS score between the groups at any time (data not shown).At 52 weeks, the mean (CI 95%) DASH score was 9 (3–14) in the H group and 13 (8–20) in the D group.Injuries of the superficial branch of the radial nerve occurred in 3 patients in the H group and 1 in the D group . The symptoms were transient and disappeared within 6 months. Superficial pin-track infections occurred in 9 patients in the H group and in 9 patients in the D group. There were no deep infections and no patients developed a complex regional pain syndrome.Several external fixators that allow early exercise have been developed to prevent joint stiffness and shorten the period of rehabilitation . ClyburnSome years later, In the bridging but dynamic Dynawrist fixator, the center of joint rotation is not disturbed . Like thIn recent years, the popularity of volar fixed-angle plates has increased—with promising early results . This opWe found the same anatomic and functional outcome in patients treated with the Dynawrist bridging but dynamic fixator and in patients treated with the non-bridging Hoffman II fixator. Since the surgical technique is simpler and the indications for application are wider, the Dynawrist fixator seems to be a good alternative to the Hoffman II fixator.