Additional PEEP to 10 cm H2O was added after injury. Animals were randomized to one of the 3 modes of ventilation and followed for 5 hr after injury.We compared gas exchange, respiratory mechanics, and measured bronchoalveolar fluid for inflammatory cytokines, cell counts and surfactant function. Lung injury was scored by light microscopy. Pigs received mechanical ventilation (F2 and respiratory system compliance was significantly greater with biologically variable ventilation compared to the other 2 groups. Mean and mean peak airway pressures were also lower. There were no differences in cell counts in bronchoalveolar fluid by flow cytometry, or interleukin-8 and -10 levels between groups. Lung injury scoring revealed no difference between groups in the regions examined. No differences in surfactant function were seen between groups by capillary surfactometry.PaOIn this porcine model of acute lung injury, various indices to measure injury or inflammation did not differ between the 3 approaches to ventilation. However, when using a low tidal volume strategy with moderate levels of PEEP, sustained improvements in arterial oxygen tension and respiratory system compliance were only seen with BVV when compared to CMV or CMV with a recruitment manoeuvre. T) in patients with acute lung injury (ALI) or acute respiratory distress syndrome (ARDS) is alveolar collapse [T) approach the addition of higher PEEP levels offers no further improvement in outcome [IO2, it remains unclear how best to improve and sustain oxygenation, during low VT ventilation strategies for ALI/ARDS management.A negative consequence of mechanical ventilation using lower tidal volumes , a unique computer-controlled version of control mode ventilation (CMV). With BVV, gas exchange and respiratory mechanics improved in animal models, with [T protocols using an ARDSNet algorithm [T ventilation with a recruitment manoeuvre in ALI/ARDS using a low VT approach.Buchman  and othels, with  and withls, with , during lgorithm  and in hlgorithm . After dlgorithm . A recenlgorithm . Other ilgorithm  and a malgorithm . While plgorithm , not a m2O of continuous positive airway pressure for 40 sec performed hourly for 5 hrs. This approach has been shown to improve oxygenation in patients with early ARDS who do not have any chest wall impairment [Therefore, in this study in pigs with oleic acid lung injury, we compared BVV to conventional CMV or CMV with a recruitment manoeuvre (CMV-RM) of 40 cm Hpairment . A multipairment ,20 at en2 of 35–45 mm Hg. Anaesthesia was maintained with 2% isoflurane in 100% oxygen during surgical preparation. Intravenous rocuronium bromide (1 mg/kg/hr) was administered by continuous infusion for muscle relaxation. Lactated Ringer's solution was given intravenously during the surgical preparation and for the duration of the experiment.Pigs (weighing 20–30 kg) received 0.6 mg atropine, 15 mg midazolam, and 300 mg ketamine intramuscularly for sedation. Isoflurane 5% in 100% oxygen was delivered via facemask to induce anaesthesia. When sufficient depth of anaesthesia was achieved, the pigs were intubated orotracheally with a 6.0 mm cuffed endotracheal tube. Mechanical ventilation was instituted with an Ohio 7000 ventilator  with minute ventilation adjusted to maintain a PaCO® ventilator  capable of delivering either CMV or BVV. The ventilator was set to deliver a square wave inspiratory flow pattern with an I:E ratio of 1:2. Isoflurane was discontinued, and a propofol/ketamine infusion at 10/2.5 mg/kg/hr substituted to maintain anaesthesia.A thermodilution pulmonary artery catheter (7.5-Fr) was inserted and advanced into the right external jugular vein until a satisfactory pulmonary capillary wedge tracing was obtained. Temperature was measured from the tip of the pulmonary artery catheter. The right femoral artery was cannulated for continuous pressure transduction and arterial blood gas (ABG) analysis. A 5-Fr single lumen femoral venous catheter was advanced into the inferior vena cava for infusion of oleic acid. A surgical tracheotomy was performed and the animal was switched to an Esprit2O recruitment manoeuvre for 30 sec, animals were ventilated with a VT of 10 ml/kg at an FIO2 of 0.3, with 5 cm H2O of PEEP. Respiratory rate was adjusted to maintain PaCO2 between 35–45 mm Hg.After a 30 cm HAfter 15 min to stabilize, baseline measurements were obtained. Haemodynamic measurements included mean arterial pressure (MAP), heart rate, central venous pressure (CVP), mean pulmonary artery pressure (MPAP), and pulmonary artery occlusion pressure (PAOP). All haemodynamic data were continuously recorded on a Gould 2600 Oscillograph . Cardiac output (CO) was measured by thermodilution, in triplicate, at stated measurement periods.T intermittently; this data was recorded using an advanced CODAS  data acquisition system.A pneumotachograph  with the sensor immediately proximal to the tracheotomy was used to measure airway pressures and VArterial and mixed venous gases were analyzed using a Radiometer ABL 500 . Arterial and mixed venous oxygen content, oxygen saturation, and haemoglobin concentrations were measured with a Radiometer OSM3 set for porcine blood.T used was that which the animal was receiving at that time.Static respiratory system compliance (Crs) was measured in triplicate by clamping the expiratory limb of the ventilator circuit at the end of inspiration for 1 sec to obtain a plateau pressure. The V2 <60 mm Hg for two consecutive measurements (PaO2/FIO2 <200). Dopamine was started at 5 μg/kg/min and was titrated to keep the MAP >60 mmHg. When the oxygenation target was achieved, the oleic acid infusion was stopped and the PEEP was increased to 10 cm H2O. Ten minutes after the increase in PEEP, an arterial blood gas sample was obtained to determine if PaO2 had increased. PaO2 had to be >75 mm Hg but <90 mm Hg. This was considered to represent adequate lung injury, but indicate that collapsed alveoli could be recruited with the additional PEEP. If the PaO2 did not increase, the experiment was terminated. If the PaO2 increased to >90 mm Hg, additional oleic acid was infused until the PaO2 decreased to <60 mm Hg.Oleic acid was infused via the 5-Fr femoral venous catheter at 0.2 ml/kg/hr until PaOT (7 ml/kg) protocol was initiated and the respiratory rate increased to 30 bpm. After 10–15 min arterial blood gas sampling was done to assess the stability of the PaO2. If the PaO2 remained stable, the animals were then randomized into one of three groups: conventional ventilation with a VT of 7 ml/kg (CMV); conventional ventilation with VT of 7 ml/kg with a 40 sec, 40 cm H2O recruitment manoeuvre performed hourly (CMV-RM). The recruitment manoeuvre was performed at end-expiration with the PEEP level maintained at 10 cm H2O at an FIO2 of 0.3; or biologically variable ventilation (BVV) with a mean VT of 7 ml/kg.A low VFollowing stable oleic acid lung injury, haemodynamic, gas exchange and respiratory system compliance (Crs) measurements were recorded and obtained hourly thereafter. Measurements in the CMV-RM group were obtained 5 min after each recruitment manoeuvre (RM). An additional measure of gas exchange and Crs was made in the CMV-RM group 50 min after the RM, to ascertain the duration of effect of the RM.en bloc. Following removal, the lungs were suspended upside down for 10 min to collect bronchoalveolar (BAL) fluid. Samples of BAL fluid were collected in heparinized saline and then frozen immediately at -80oC. Fluid was then sent for cytokine analysis, measures of surfactant function and flow cytometry. The lungs and previously collected BAL fluid were weighed and the lungs were suspended and aerated overnight. The following day, the lungs were placed in an oven to dry, and following a stable dry measurement, wet:dry weight ratio was calculated.At the end of the experiment, a sternotomy was performed. Animals were sacrificed with a lethal dose of thiopental. The trachea was then clamped at end inspiration and the heart and lungs were removed Surfactant function was assessed on BAL fluid samples using a capillary surfactometer  in the manner of Enhorning and colleagues ,22. Such1. Raw BAL fluid surfactant function analysis – centrifuging at 200 g for 5 min to rid large debris, then the supernatant spun at 10,000 g and pellet resuspended in 100 μL saline and analyzed using the surfactometer.2. Surfactant resuspended in 100 μL of saline after chloroform/methanol extraction. Chloroform/methanol extraction permits the lipid and phospholipid fraction to dissolve in the organic nonpolar solvent (chloroform) and the solvent evaporated to dryness. Volume of the final ratio for chloroform:methanol:water was 1:1:0.9. Following extraction, the pellet was resuspended and analyzed using the surfactometer.The percentage of time that the capillary tube was open for 2 min was determined for each sample, in triplicate, then averaged. Standards were saline; 0% patent for a 2 min time period and bovine surfactant; >98% patent for a 2 min time period. Each sample was measured in a blinded fashion in both conditions.The BAL fluid sample was passed through a cell strainer and 100 μL was transferred into a 5 × 75 mm tissue culture tube. Red cells were lyses by the addition of 500 μL Optilyse C  and following 15 min incubation at room temperature, the cell suspension was diluted by the addition of 500 μL Isoton II and 100 μL FlowCount Fluorospheres (Beckman Coulter). The cell suspension was immediately analyzed on a Beckman Coulter EPICS Altra cell sorter configured with a high-speed quartz flow cell tip and a water-cooled argon laser emitting 150 mW at 488 nm. Forward and side light scatter signals were employed to derive 2-parameter histograms which clearly defined the fluorescent beads and three populations of cells, subsequently defined as mononuclear cells, neutrophils and eosinophils. At least 20,000 cells were analyzed for each sample. The acquisition software provided with the instrument automatically calculated the concentrations of each cell population based on the number of events in each of the 4 analysis regions.The incubation times and washes were preformed as specified in each respective kit: . Immunoassay kits for swine IL-8 and IL-10 were used. Sample incubation times were kept as constant as possible by pre-plating on a blank 96 well plate before transferring to the coated assay plate. ELISA plates were read at 450 nm by an SLT Rainbow plate reader . Standard curves and concentration calculations were performed according to kit directions.For light microscopy, four blocks of tissue from the right lung – upper lobe, middle lobe, nondependent and dependent lower lobe, fixed in buffered formalin, processed and embedded in formalin. Sections were cut and stained with haematoxylin and eosin. Under light microscopy, a lung injury scoring system modified from Rotta et al. ,20 was uParametric data were analyzed by repeated measures ANOVA using least squares means test matrices to identify differences within and between groups from group × time or group effects. Bonferroni's correction was applied where appropriate. Non-parametric comparison of the lung injury scores was by Kruskal-Wallis test. In all circumstances a p-value ≤0.05 corrected for multiple comparisons was considered significant.Twenty-five experiments were undertaken. One animal was discarded because oleic acid injury could not be established after 1.5 hrs of infusion. In the CMV-RM group, one animal died 2 hr into the experiment but data are included in analysis in this experiment up to time of the animal's demise. Complete experiments were done in twenty-three animals; .Temperature and haemodynamic data are shown in Table 1: see 2 over time . In all groups, the PaCO2 increased following oleic acid injury and was essentially stable at these elevated levels for the remainder of the experiment. The group × time for PvO2 was significant at p = 0.002 with significantly lower PvO2 over time in the CMV-RM group. Shunt fraction was lower in the BVV group (group × time interaction p = 0.003).Table 2: see 2 tended to decrease immediately following a recruitment manoeuvre, but increased over time as measured at 50 min. PaO2 significantly decreased in RM4 and 5 (-11.1 ± 5.2 mm Hg and -5.2 ± 4.4 mm Hg respectively). Following recruitment, PaO2 increased slowly early in the experiment at RM2 and RM3 (10.1 ± 5.5 mm Hg and 11.8 ± 9.1 mm Hg respectively), but failed to do so in the later time periods. For respiratory system compliance, no statistically significant differences were seen at any time period over the course of the experiment in the CMV-RM group.PaO2O with BVV; 15.1 ± 0.2 with CMV-RM and 15.1 ± 1.0 with CMV respectively). In all 3 groups, mean Paw increased following oleic acid. A more pronounced effect was seen with peak Paw  with mean peak pressures over time least with BVV . There was no group × time interaction for VT in ml/kg measured over time (p = 0.617).A group × time interaction for mean Paw was seen (p = 0.002) with Paw lowest with BVV  and exponential (R2 = 0.41) curve fits.The ELISA results to assess the cytokine IL-8 concentration in BAL fluid indicated no statistically significant difference for the 3 groups: 564 ± 551 pg/mL with BVV; 653 ± 639 pg/mL with CMV and 300 ± 235 pg/mL with CMV-RM. As in the measurement of neutrophil counts, there was significant variability with IL-8 levels ranging over a 385-fold concentration difference. Such a broad range of data in both neutrophil counts and IL-8 concentration suggested the possibility of power law behaviour and correlation between these variables. A very strong power law relationship was found between IL-8 pg/mL and absolute neutrophil count/mL for pooled data; y = 77609x-6x1.38; n = 13, R2 = 0.83. In this situation the linear and exponential fits were R2 = 0.61 and R2 = 0.69 respectively. In this analysis, IL-8 concentration is presumed to be the dependent variable – being released by the monocytes (counts on the x-axis).The number of mononuclear cells from cell cytometry of BAL fluid was not different between groups: for BVV, 1346 ± 743 cells/μL; for CMV, 1767 ± 905 cells/μL; and for CMV-RM, 1068 ± 579 cells/μL. These cells presumably in large part represent alveolar macrophages. A power law relationship was seen between pooled data for a correlation between IL-8 concentration in pg/mL and monocyte count/mL – 1.0 × 100.15; n = 13, R2 = 0.07.The IL-10 results from BAL fluid, as well, indicate no statistically significant difference for the 3 groups: 119 ± 173 pg/mL for BVV; 124 ± 146 pg/mL for CMV; and 149 ± 168 pg/mL for CMV-RM. Unlike IL-8 concentrations the range of variation for IL-10 concentrations was significantly less – the maximum range differing by only 16-fold. There was no power-law relationship found between IL-10 and absolute monocyte count for pooled data: y = 7.5xT but at lower peak and mean airway pressure and greater respiratory system compliance.The main finding in this study of acute lung injury in a porcine model is that BVV significantly improved oxygenation and respiratory mechanics with no difference in indices of lung injury, inflammation or surfactant function compared to the more conventional ventilation techniques – CMV or CMV with a standard recruitment manoeuvre. The improvements seen with BVV were sustained over the course of the experiment; an effect not seen with recruitment. Such improvement was obtained at similar measured mean VT model of ALI/ARDS; not in healthy lung. As well, we have confirmed the differences between BVV and CMV seen in other work from the laboratory using the same model [These findings are similar to previously published results from our laboratory showing that BVV was superior to both CMV and CMV with sigh breaths. These sigh breaths were of no advantage in a model of healthy lung recruitment – lung reinflation after a controlled collapse for one hr with contralateral one-lung ventilation . In thatme model . No impo2. Thus, lower PvO2 in the CMV-RM group should have minimized shunt but here the shunt fraction is greatest. The lowest shunt with BVV indicates that the numerator of the shunt equation is less in this group, indicating enhanced blood flow in aerated lung units.Shunt fraction was significantly lower with BVV. Lynch et al.  and SandA multimodal approach to assess lung injury, lung inflammation and surfactant function indicated no discernable differences between the 3 approaches to ventilation:1. Light microscopy studies demonstrated no significant differences between groups for lung injury in any region examined – from upper to dependent lower lobes. This finding indicates no difference between groups in lung injury as assessed by histology, with the caveat that only small areas of lung in each region were examined in a condition known to be heterogeneous.2, wet:dry weight ratios, respiratory system compliance, or peak airway pressure. Arold et al. [2. No difference in surfactant function was seen between groups as assessed by capillary surfactometry. Following oleic acid lung injury, surfactant function was markedly depressed when compared to a surfactant standard – see Figure d et al.  have sho3. No difference between groups is seen for cell counts in the BAL fluid. There is considerable variation in this analysis and a full data set is not present. A significant number of studies of cell count could not be undertaken because of the nature of the BAL fluid. When thick with proteinaceous debris the samples often were unable to be prepared for meaningful cytometry analysis. Of the data represented, no difference in the proportion of neutrophils, monocytes or eosinophils is apparent for any of the 3 approaches to ventilation. Allen and Bates  have sho2 = 0.007 in this experiment, n = 24). Failure to reconfirm these findings may, in part relate to the nonlinear relationships highlighted above. Small changes in initial conditions may preclude similar findings at end experiment.4. IL-8 is considered to be the major neutrophil chemoattractant cytokine in lung diseases like ARDS . IL-10 m2 and respiratory system compliance. BVV has been shown to recruit in a pure model of lung collapse – re-expansion of lung following cessation of one lung ventilation [The above observations, collectively, indicate no fundamental differences between the ventilation strategies studied in regards oleic acid or superimposed ventilator associated lung injury. No one technique seems clearly advantageous. However, BVV alone improves oxygenation significantly following acute lung injury over time, an effect that was sustained, suggesting it is the best technique of the 3 studied to recruit atelectatic lung as assessed by greater PaOtilation . With BVtilation .2O to 2 cm H2O above Pflex in an attempt to prevent derecruitment, we maintained PEEP at 10 cm H2O throughout. In a porcine model of lung lavage, lung remained recruited if PEEP was at 10 cm H2O: the value chosen in this study [2 will not increase if the sustained inflation does not restore aeration to the atelectatic regions because a significant fraction of pulmonary blood flow is shunted to nonaerated regions [2O for 60 sec – was not beneficial in another animal model and that a more aggressive recruitment manoeuvre – PEEP 40 cm H2O and pressure control ventilation of 20 cm H2O, with a respiratory rate of 10, and I:E ratio 1:1 for 2 min – was successful only after the second hour. Allen et al. [2O) did not influence the time constants for recovery in elastance both before and after lung lavage. They conclude that for a deep inflation to be beneficial in their model that it may be necessary to apply the inflation several times a minute. Thus, the appropriate PEEP level, with and following recruitment, remains controversial [It could be argued that we have not chosen the optimal recruitment strategy to compare to the two other modes of mechanical ventilation. That said, we have chosen a well recognized approach to recruitment , one assis study . This leis study . Furtheris study . Failure regions . Such ma regions  have shon et al.  have shooversial ,39, but The human variability file for respiratory rate used to program the ventilator is shown in Figure T strategies are used for management of ALI/ARDS. A well accepted recruitment strategy has been compared to BVV in this animal study. It is possible that other approaches for recruitment could be superior to the one chosen. However, all chosen modes of recruitment would increase airway pressures over and above those seen with BVV, potentially increasing the risk of volutrauma.This study shows that BVV with a human variability file was superior to either CMV or CMV with a recruitment manoeuvre (CMV-RM) for sustained improvement in gas exchange and respiratory mechanics in a porcine model of acute lung injury. Prior work has demonstrated an advantage of BVV in a clinical setting of atelectasis . The curD.J.F. was responsible for conduct of the experiments as a fellow in the Anesthesia Laboratory. M.R.G. supervised conduct of the experiments, helped analyze data and helped write the paper. L.G.G. helped with the experiments, data retrieval and collation and table and figure production. J.A.T. did the histological assessments and analysis. B.M.M. supervised the cytokine assays and their interpretation and helped write the paper. E. K-Y. W. conducted the cytokine assays. C.H. did the surfactant assays while a fellow in the Oral Biology Laboratory. J.E.S. supervised and interpreted the results of the surfactant assays. W.A.C.M. conceived the study, analyzed and interpreted data and helped write the paper.Table 1: Temperature and HaemodynamicsClick here for fileTable 2: Respiratory Gas and Derived DataClick here for file


Embryo implantation plays a major role in embryogenesis and the outcome of pregnancy. Plasminogen activators (PAs) have been implicated in mammalian fertilization, early stages of development and embryo implantation. The invasion of trophoblast cells into the endometrium during the implantation process can be blocked by inhibitors of serine proteases, illustrating the role of these enzymes in the invasion process. As in vitro developing embryos resulted in lower implantation rate than those developed in vivo we assume that a reduced PAs activity may lead to it. There is hardly any information regarding qualitative or quantitative differences in expression of PAs in preimplantation embryos, or comparisons between in vivo and in vitro developed embryos. The purpose of this study was to assess the expression of urokinase type (uPA) and tissue type (tPA) plasminogen activators in in vivo and in vitro preimplantation development in rat embryos using immunofluorescence confocal microscopy and computerized image analysis.Zygotes, 2-cell, 4-cell, 8-cell, morula and blastocyst stages of development were flushed from the reproductive tract (control groups) of Wistar rats. Zygotes were flushed and grown in vitro to the above mentioned developmental stages and comprised the experimental groups. Immunofluorescence microscopy and computerized image analysis were used to evaluate both qualitative  and quantitative expression of plasminogen activators.uPA and tPA were found to be expressed in rat embryos throughout their preimplantation development, both in vivo and in vitro. While uPA was localized mainly in the cell cytoplasm, the tPA was detected mainly on cell surface and in the perivitelline space. In blastocysts, both in vivo and in vitro, uPA and tPA were localized in the trophectoderm cells. Total uPA content per embryo was higher in the in vivo as compared with the in vitro developed embryos at all stages measured. Blastocyst uPA content was significantly low as compared with the four-cell, eight-cell, and morula stages. Total tPA content was higher in embryos developed in vivo than those developed in vitro except for the 4-cell and 8-cell stages.In vitro embryo development leads to lower PAs expression in a stage dependent manner as compared with in vivo developing controls. The enzymes studied vary probably in the ratio of their active and inactive forms as there is no correlation between their content and the activity observed in our previous study. The localization of both PAs in the blastocysts' trophectoderm supports the assumption that PAs plays a role in the implantation process in rats. The inv failure ,13. In t failure .In the implantation process, two major factors participate: the uterus undergoes changes that prepare it for the arrival and implantation of embryos, and the embryos undergo cellular reorganization that enables them to penetrate the endometrium and to form the placenta. We assume that one of the reasons for low implantation rate of embryos developed in vitro involves reduced PAs activity.In a previous study we demonstrated differences in PAs activities between in vivo and in vitro preimplantation developed embryos. In both, uPA activity increased from the zygote towards the blastocyst stage while tPA activity remained relatively unchanged. However, tPA and uPA activities were lower in in vitro developed embryos as compared with in vivo developing ones, at all developmental stages, which may lead to a reduced implantation rate of in vitro developed embryos .There is hardly any information regarding qualitative or quantitative differences in expression of PAs in preimplantation embryos, or comparisons between in vivo and in vitro developed embryos. Therefore, the purpose of this study was to investigate the PAs expression and localization during embryo development in vivo and in vitro by immunofluorescence confocal microscopy.The following study was approved by the Institutional committee for animal care and ethics at Ben-Gurion University of the Negev, Beer-Sheva, Israel.Mature female Wistar rats 2–3 months old, weighing 180–230 g were used. The animals were kept in a temperature-controlled room maintained at 22–24°C with lighting regimen of 14 hours light 10 hours dark (light on 5:00 AM – 7:00 PM). The rats were allowed free access to rat chow and tap water.Daily vaginal smears were taken at 10:00 AM, and the stage of estrous cycle was determined. Overnight caging of a proestrous female with a male of proven fertility induced pregnancy. The next day, the presence of a vaginal plug or spermatozoa in the vaginal smear was designated as day 1 of pregnancy.Zygotes, two-cell, four-cell, eight-cell embryos and morulae were flushed with rat 1-cell embryo culture medium (R1ECM)  from oviZygotes in their cumulus mass were flushed and the cumulus cells were removed by gentle aspiration through a micropipette  several times in R1ECM containing 80 U/mL of hyaluronidase. Clean zygotes were washed 3 times by transfer into fresh R1ECM to remove traces of hyaluronidase. Flushed embryos were collected with a mouth-controlled micropipette .Blastocysts were flushed from the uterine horns by insertion of a 23-gauge needle attached to a syringe containing R1ECM. Flushed, free-floating blastocysts were collected into a polypropylene tube inserted through the vagina and pushed gently to surround the cervical openings. Tubes were removed, and their contents were poured into Petri dishes. Blastocysts were washed and collected as described for zygotes and embryos. These embryos developed in vivo were the control groups.2 in air. This medium was shown by Miyoshi et al. [As described for the in vivo embryos, clean zygotes were grown in vitro to the same developmental stages as controls; these were the experimental groups. Each group of embryos consisted of 25–35 embryos collected from six pregnant females. This was repeated three times for each developmental stage . Groups of 25–35 zygotes were placed into 35-mm-diameter culture dishes  containing 50μL of R1ECM medium under a layer of mineral oil  and cultured at 37°C under 5% COi et al.  to enablThe method used was basically that of Dubey et al.  with varThe distribution and concentration of PAs in the embryos were visualized by fluorescent microscopy on a Zeiss laser scanning confocal microscope equipped with an X100 objective. Z-sections and XZ-sections were obtained from 3D scanning by using LSM510 software  The PAs density for each embryo was computed by image analysis based on the same principles as manual counting described elsewhere . The embData are expressed as means ± SEM. Statistical analysis was performed with two-way analysis of variance, followed by the least significant differences test for multiple comparisons using computer software . P < 0.05 was defined as statistically significant difference.Immunohistochemical staining for the location of tPA and uPA in preimplantation embryos developed in vivo and in vitro are shown in figure 3, respectively, Fig. 3, respectively).Quantitative measurement of total uPA in an embryo at each stage showed significantly lower expression (p < 0.01) in in vitro developed embryos from the 4-cell stage up to the blastocyst stage compared with the in vivo developed corresponding timepoint. The highest expression of uPA was found in in vivo developed embryos from 4-cell to the morula stage (90.58, 78.78 and 79.35 Pixels per embryo × 103, respectively, Fig. Total tPA expression in a whole embryo showed highest expression in in vivo developed embryos at the 2-cell, 8-cell, morula and blastocyst stages (61.59, 52.71, 48.03 and 52.34 Pixels per embryo × 10Our study demonstrates that uPA and tPA are expressed throughout all stages of preimplantation development of rat embryos. Zhang et al.  reportedThe results show localization of immunoreactive uPA in the embryonic cell cytoplasm and plasma membrane in all developmental stages both in vivo and in vitro, while tPA is detected on the cell membrane and in the perivitelline space. In the blastocyst stage, PAs are localized mainly in the trophectoderm. In our previous study  we showePro-uPA is synthesized as an inactive single chain that can be stored or secreted. The secreted pro-uPA can be cleaved to produce the two-chain active molecule, uPA, by the aid of limited proteolytic activity of plasmin . The secHigh tPA expression was detected at the zygote stage which is in accordance with high tPA activity found in this stage . This isThe embryonic extracellular matrix is in a continuous turnover during the embryonic development. The 8-cell stage is characterized by structural changes taking place in the embryo during the compaction process. It is therefore very likely that such changes at the 8-cell stage could be associated with increased tPA expression and activity which is known to participate in tissue remodeling [Lower expression of uPA was observed in in vitro developed embryos as compared with in vivo ones from the 4-cell up to the blastocyst stage while tPA expression was lower only in the morula and blastocyst stages. This could be explained by reduced metabolic activity in the in vitro developed embryos as suggested by Krisher et al. . In addiAdditional studies addressing the regulation of PA/Plasmin system by adding exogenous factors may provide insights into its role in early embryo development and implantation.The purpose of the study was to determine the relative importance of tPA and uPA in preimplantation embryo development. In vitro embryo development leads to lower PAs expression in a stage dependent manner as compared with in vivo developing ones. The localization of both PAs in the blastocysts' trophectoderm supports the assumption that PAs may play a role in the implantation process in rats.EDA participated in the planning of the project, carried out the animal experimentation, immunohistochemistry and the image analysis studies. USM participated in the planning of the project, animal experimentation and participated in preparation of the manuscript. GP participated in preparation of the manuscript. IHV participated in the planning of the project, statistical analysis and in preparation of the manuscript.


Hepatocellular carcinoma (HCC) is one of the most worldwide frequent primary carcinomas resulting in the death of many cirrhotic patients. Unfortunately, the molecular mechanisms of this cancer are not well understood; therefore, we need a good model system to study HCC. The dog is recognized as a promising model for human medical research, namely compared with rodents. The objective of this study was to establish and characterize a spontaneous canine tumor cell line as a potential model for studies on HCC.Histomorphological, biochemical, molecular biological and quantitative assays were performed to characterize the canine HCC cell line that originated from a dog with a spontaneous liver tumor. Morphological investigations provided strong evidence for the hepatocytic and neoplastic nature of the cell line, while biochemical assays showed that they produced liver-specific enzymes. PCR analysis confirmed expression of ceruloplasmin, alpha-fetoprotein and serum albumin. Quantitative RT-PCR showed that the canine HCC cell line resembles human HCC based on the measurements of expression profiles of genes involved in cell proliferation and apoptosis.We have developed a novel, spontaneous tumor liver cell line of canine origin that has many characteristics of human HCC. Therefore, the canine HCC cell line might be an excellent model for comparative studies on the molecular pathogenesis of HCC. Hepatocellular carcinoma (HCC) is one of the most worldwide frequent primary tumors in man, with an estimated 564,000 new cases and almost as many deaths in 2000 . It almoHowever, the study of those mechanisms is hampered because the liver tissue of patients with HCC has only limited value and primary hepatocytes are difficult to maintain in culture. Furthermore, primary hepatocytes rapidly lose detoxifying P450 isoenzymes. In addition, and because of the heterogeneity of the molecular genetic changes that can lead to HCC across species, molecular genetic studies in animals have not yet provided a precise general model for the molecular pathogenesis of HCC in humans. The dog is a valuable model for human comparative studies, since it has a comparative life span and habitat and thus similar risk factors and its domestication started over 10,000 years ago [Here, we describe the establishment and morphological, immunohistochemical, biochemical, and molecular characterization of the first canine hepatocyte cell line derived from a spontaneous HCC of a dog. The objective of this study was to investigate whether this cell line could be used as a potential model for studies on human HCC. Therefore, we investigated whether this canine hepatocyte tumor cell line had features similar to human HCC with respect to mutations in the hepatocyte growth factor receptor (c-MET) gene and the differential gene expression of several oncogenes, proto-oncogenes and proteins involved in proliferation, apoptosis and cell survival.The primary neoplasm was histologically characterized by broad trabeculae, 2 – 6 cells in thickness, of well-differentiated hepatocytes and separated by sinusoidal structures lined by endothelium. The hepatocytes had uniform moderately sized nuclei and small nucleoli; mitotic figures were very rare. Regularly areas with marked steatosis or glycogen accumulation within the neoplastic hepatocytes were observed. Locally within this well differentiated tumor there was a carcinomatous area characterized by broad trabeculae of more basophilic cells with large nuclei, moderate anisokaryosis, usually one or more large nucleoli and 3–5 mitotic figures per high power field Figure . The nonDirectly after establishment of the initial cell suspension , the cells appeared pleiomorphic. After approximately 10 weeks of culturing, the cells formed clusters as rounded, vital cells, which are non-adherent. This characteristic has remained ever since. Freezing and re-culturing of the cell line had no effect on cell growth. A 1:10 splitting and medium refreshment of the culture by careful trypsinization once a week (a "passage") is optimal. The tryspinized cell clusters were further cultured with fresh DMEM culture medium. The cells rather grow in these smaller clusters and not as single cells.The cell clusters were collected, fixed and handled as described. As shown in Figure The activity of ALT, GLDH and AST was measured to investigate whether the cHCC cells produced liver characteristic enzymes. In order to compare the amount of hepatic enzymes produced by the cHCC cell line, those measurements were also performed for the widely used human hepatocyte cell line HepG2 (enzyme activity of HepG2 was set at 100%), and the commonly used canine kidney cell line MDCK. The results showed the cHCC cell line produced 25% of the highly liver-specific ALT compared to HepG2, whereas the MDCKs did not produce ALT at all Table . Of anotTo further examine whether the cell line truly consists of hepatocytes, we isolated RNA from the cHCC, made cDNA, and performed PCRs for the gene expression of hepatocyte markers. The cHCCs proved to be PCR-positive for canine serum albumin, alpha-fetoprotein and ceruloplasmin. All obtained products were sequence confirmed.Mutations in exons 15–21 of the c-MET gene have been described in human HCC. A PCR was therefore performed with primers based on this region of the c-MET gene. The products were analyzed and aligned with known canine and human c-MET sequences . At nucleotide position 4089, a thymine (T) instead of an adenine (A) was observed, which resulted in a serine in the cHCC cell line versus a threonine in healthy tissue at codon 1363 (T1363S) . Then, the dog was immediately euthanized.2 and 95% air under a humidified atmosphere in non-coated flasks. It was observed every day for any changes. The medium was refreshed twice a week.Immediately after resection, the liver samples were kept in DMEM culture medium supplemented with 10% fetal calf serum , penicillin and streptomycin  and were kept on ice. Under sterile conditions, liver samples of various areas were cut into small pieces (5 × 5 mm) and trypsinized with 30 ml of trypsin/EDTA  in a sterile Erlenmeyer flask placed on a stirring platform for 30 minutes. The cell suspensions were filtered with a 70 μm nylon filter . Erythrocytes were lysed from the filtered suspension. The remaining cell suspension was resuspended in DMEM supplemented with 10% FCS and P/S and was cultured at 37°C with 5% CO2 flask with the cHCC cell culture was harvested by transferring the entire contents of the flask to a tube, which was centrifuged for 10 minutes at 1,500 g. The supernatant was replaced by freshly made fixation fluid for 4 hours. For optimal immunohistochemical staining, four different fixatives were used: zinc sulfate formalin, Bouin, Carnoy, and 10% neutral buffered formalin. The fixated cell pellet was transferred to a foam leaf-protected plastic embedding cassette. After fixation, samples were manually dehydrated and embedded in paraffin. Sections (3 μm thick) were cut and stained with hematoxylin and eosin (HE). For immunohistochemical staining, paraffin sections were mounted on poly-L-lysine coated slides, post-fixed into ice-cold acetone fixation fluid for 10 minutes, air dried and stored at room temperature (RT) until use.After 3 weeks of culturing with medium refreshment only and no splitting of the culture, the content of a T80 cm2O2, in methanol, for 30 minutes at RT. After washing with PBS buffer containing 0.1%Tween-20, background staining was blocked by incubating the sections with normal goat serum (1:10 diluted in PBS), for 30 minutes. Sections were incubated overnight at 4°C with the primary antibody HepPar1  diluted 1:50 in PBS. After washing in PBS-Tween, slides were incubated in DAKO EnVision™ + reagent, HRP-labeled  for 45 minutes at RT. After washing in PBS buffer, sections were developed using 3,3-diaminobenzidine as chromogen, and counterstained with hematoxylin.For the detection of HepPar1, slides were deparaffinized, immersed in 10 mM Tris, 1 mM EDTA buffer (pH 9), heated in a microwave oven for 10 minutes for antigen retrieval, cooled down for 10 minutes at RT and washed in PBS buffer. Endogenous peroxidase activity was blocked by 0.3% HFor the detection of CK7, the slides were treated as described above but without antigen retrieval, and incubated overnight at 4°C with mouse anti-human CK7, clone OV-TL 12/30 (Dakocytomation), diluted 1:25 in PBS with 1% bovine serum albumin. For both HepPar1 and CK7, formalin-fixed paraffin-embedded canine liver and kidney tissue controls were incubated with and without the primary antibody. In contrast to the cell culture, in the liver tissue antigen retrieval for CK7 was necessary and, therefore, a 40-minute proteinase-K (Dakocytomation) digestion at RT was performed before blocking of the endogenous peroxidase, in methanol.2 flask with the cHCC cell culture was harvested, spun down for 5 minutes at 1,500 g, the cell pellet was washed in 10 ml PBS, centrifuged for 5 minutes at 1,500 g and the cells were resuspended in 1 ml PBS. Two hundred μl of the cell suspension were lysed and homogenized with a pestle in RIPA buffer containing 1% Igepal, 0.6 mM phenylmethylsulfonyl fluoride, 17 μg/ml aprotinine and 1 mM sodium orthovanadate , for 30 minutes on ice. Total protein concentrations were calculated using a Lowry-based assay .The content of a T80 cmFor the liver enzyme measurement, 800 μl of the cell suspension was centrifuged at 12,100 g for 5 minutes. The pellet was lysed in milliQ by vortexing, centrifuged again for 5 minutes at 12,100 g and the supernatant was analyzed in a Beckman Synchron CX7 analyzer. The following enzymes were measured: ALT, AST and GLDH. AST and ALT were measured at 37°C with the Tris-pyridoxal phosphate method with Beckman-Coulter reagent. GLDH was measured with Roche reagent. All samples were subjected to the external quality control mission of the Dutch Foundation for Quality Assessment in Medical Laboratories.2 flask) under standard culturing conditions, as described for the cHCC cell line.As comparison, the widely used human hepatoma cell line HepG2  and MDCK canine kidney cell line (own collection) were used. These were grown to 80–100% confluency  according to the manufacturer's instructions. The RNA samples were treated with DNase-I (Qiagen RNase-free DNase kit). In total 3 μg of RNA was incubated with poly (dT) primers at 42°C for 45 min, in a 60 μl reaction, using the reverse transcription system .Taq polymerase (Invitrogen), 2 mM MgCl2 (Invitrogen) and 250 μM of each nucleotide . The PCR conditions were: initial denaturation at 95°C for 4 min, followed by 40 cycles consisting of denaturation at 95°C for 1 minute, annealing at 60°C for 1 minute, elongation at 72°C for 1 min, and, finally, an elongation step at 72°C for 10 min. The PCR products were analyzed on a 1.5% agarose gel, and the DNA fragments were visualized with ethidium bromide. The primers used for these PCRs are depicted in Table To examine whether the cell line consisted of hepatocytes, we isolated total RNA and made cDNA as described above. PCRs were performed to investigate the gene expressions of hepatocyte  markers. All reactions were performed in a 50 μl volume with a thermal cycler . Reaction mixtures contained 0.2 μM of each oligonucleotide primer , PCR buffer , 2.5 U of Platinum To investigate mutations in the tyrosine kinase domain of c-MET, a PCR was performed with two overlapping primer sets for this domain Table , both reQuantitative gene expression measurements of the cHCC cell line were compared with a group of four healthy liver tissues. Liver biopsies from the healthy dogs, which included two Cairn terriers (breed of the donor dog), were obtained under local anesthesia with a 16G biopsy needle and immediately snap-frozen and stored at -70°C until further analysis.® green I, BMA, Rockland, ME) was performed in triplicate in a spectrofluorometric thermal cycler . Per reaction, 1.67 μl of cDNA was used in a 50 μl volume containing 1 × manufacturer's buffer, 2 mM MgCl2, 0.5 × SYBR® green I, 200 μM dNTP's, 0.4 μM of each oligonucleotide primer, 1.25 units of AmpliTaq Gold (Applied Biosystems), on 96-well iCycler iQ plates (BioRad). Primers ; AST – aspartate aminotransferase; CK7 – cytokeratin 7; GLDH – glutamate-lactate dehydrogenase; HCC – hepatocellular carcinoma; HepPar1 – hepatocyte paraffin-1; HGF – hepatocyte growth factor; HPRT – hypoxanthine phosphoribosyl transferase; MDCK – Madin-Darby canine kidney cells; ODC – ornithine decarboxcylase; P27KIP – kinase inhibitor protein 27 kDa; PTEN – phosphatase and Tensin homolog deleted on chromosome TEN; SOCS3 – suppressors of cytokine signalling type 3; TGF-alpha – transforming growth factor alpha.SYB carried out the establishment, the biochemical and molecular characterization, and the mutations in c-Met study. BS carried out the quantitative RT-PCR, whereas JY and RK carried out the histomorphological part. TvdI performed the description of the initial tumor. SYB, HFE, TvdI, JR and LC participated in the study design and coordination of the study. All authors read and approved the final manuscript.


A 'spike-in' experiment for Affymetrix GeneChips is described that provides a defined dataset of 3,860 RNA species. A 'best route' combination of analysis methods is presented which allows detection of approximately 70% of true positives before reaching a 10% false discovery rate. As more methods are developed to analyze RNA-profiling data, assessing their performance using control datasets becomes increasingly important.We present a 'spike-in' experiment for Affymetrix GeneChips that provides a defined dataset of 3,860 RNA species, which we use to evaluate analysis options for identifying differentially expressed genes. The experimental design incorporates two novel features. First, to obtain accurate estimates of false-positive and false-negative rates, 100-200 RNAs are spiked in at each fold-change level of interest, ranging from 1.2 to 4-fold. Second, instead of using an uncharacterized background RNA sample, a set of 2,551 RNA species is used as the constant (1x) set, allowing us to know whether any given probe set is truly present or absent. Application of a large number of analysis methods to this dataset reveals clear variation in their ability to identify differentially expressed genes. False-negative and false-positive rates are minimized when the following options are chosen: subtracting nonspecific signal from the PM probe intensities; performing an intensity-dependent normalization at the probe set level; and incorporating a signal intensity-dependent standard deviation in the test statistic.A best-route combination of analysis methods is presented that allows detection of approximately 70% of true positives before reaching a 10% false-discovery rate. We highlight areas in need of improvement, including better estimate of false-discovery rates and decreased false-negative rates. Since their introduction in the mid 1990s , expressThe most useful control datasets to date for evaluating the effectiveness of analysis methods for Affymetrix arrays are cRNA spike-in datasets from Affymetrix and Gene Logic. The Affymetrix Latin square dataset  is a serHere we present a new control dataset for the purpose of evaluating methods for identifying differentially expressed genes (DEGs) between two sets of replicated hybridizations to Affymetrix GeneChips. This dataset has several features to facilitate the relative assessment of different analysis options. First, rather than containing a limited number of spiked-in cRNAs, the current dataset has 1309 individual cRNAs that differ by known relative concentrations between the spike-in and control samples. This large number of defined RNAs enables us to generate accurate estimates of false-negative and false-positive rates at each fold-change level. Second, the dataset includes low fold changes, beginning at only a 1.2-fold concentration difference. This is important, as small fold changes can be biologically relevant, yet are frequently overlooked in microarray datasets because of a lack of knowledge as to how reliably such small changes can be detected. Third, our dataset uses a defined background sample of 2,551 RNA species present at identical concentrations in both sets of microarrays, rather than a biological RNA sample of unknown composition. This background RNA population is sufficiently large for normalization purposes, yet also enables us to observe the distribution of truly nonspecific signal from probe sets which correspond to RNAs not present in the sample.versus average log signal intensity (A)), and if necessary, performing a normalization at the probe-set level to center this plot around M = 0; and third, choosing the best test statistic . The cRNAs were divided into two samples - 'constant' (C) and 'spike' (S) - and each sample was hybridized in triplicate to Affymetrix GeneChips . The S sample contains the same cRNAs as the C sample, except that selected groups of approximately 180 cRNAs each are present at a defined increased concentration compared to the C sample  clone sOur dataset design provides the rare knowledge of virtually all of the RNA sequences within a complex sample  of clones for which only partial sequence was available, and the possible rare mistakenly assigned or contaminated clone). We can therefore evaluate various absent/present call metrics on the basis of their ability to distinguish between the known present and absent RNAs. We investigate this issue at both the probe pair level and probe set level. For the probe pair level assessment, we first identify the probe pairs which we expect to show signal, and those which should not. We thus define two classes of probe pairs: first, perfect probe pairs, whose PM probe matches perfectly to a target RNA sequence, and neither PM nor MM probe matches to any other RNA in the sample with a BLAST E-value cutoff of 1 and word size of 7, and second, empty probe pairs, whose PM and MM probes do not match to any RNA sequence when using the same criteria.2(PM/MM), PM-MM, , and log2(PM) - to distinguish between perfect and empty probe pairs, by calculating receiver-operator characteristics (ROC) curves using the perfect probe pairs as true positives and the empty ones as true negatives. Each point on a curve depicts the specificity and sensitivity for RNA detection, when using a specific value of the corresponding metric as a cutoff for classifying probe sets as present or absent. Instead of depicting the false-positive rate (the fraction of true negatives that are detected as present) on the x-axis, which is customary for these types of graphs, we show the false-discovery rate (the fraction of detected probe sets which are true negatives), which distinguishes between the metrics more effectively for the top-scoring probe sets. Figure 2(PM/MM) and PM-MM, are the most successful at distinguishing perfect from empty probe pairs. This indicates that the PM signal alone is a less effective indicator of RNA presence, probably because the probe hybridization affinity is highly sequence-dependent. However, even with the more successful metrics, only about 60% of the perfect probe sets are detected before reaching a 10% false-discovery rate, indicating that there is still a high level of variability in probe pair sensitivity, even when using the MM signal to estimate the probe hybridization affinity.On the chip, which contains 195,994 probe pairs, there are 50,859 perfect probe pairs and 117,904 empty ones. Observation of the signal for these probe pairs Figure  clearly p-values from this test are used to generate the ROC curves in Figure 2(PM/MM), performs best. Therefore, the MM signals are important in generating accurate presence/absence calls. In our dataset, about 85% of the true positives could be detected before having a 10% false-discovery rate. The detection of perfect probe pairs is not improved when we include additional information from replicates. The 15% of probe sets which are called absent may represent truly absent RNAs, owing to failed transcription or labeling . However, as we do not have an independent measure of failed transcription for the individual cRNA sequences in the target sample, we cannot completely rule out the possibility that they are the result of non-responsive probes or a suboptimal absent/present metric that fails to score low-abundance cRNAs. Regardless, as non-responsive probes or missing target cRNAs should affect both the C and S chips identically, these factors should not limit the value of this dataset in making relative assessments of different analysis methods.When signals from the 14 probe pairs in each probe set are combined to create a composite absence/presence call, a much larger fraction of the spiked-in RNA species can be detected reliably. To obtain absent/present calls at the probe-set level, we perform the Wilcoxon signed rank test using each of the metrics listed above . The p-vPerfect Match [gcrma [The first task in analyzing Affymetrix microarrays is to combine the 14 PM and 14 MM probe intensities into a single number ('expression summary') which reflects the concentration of the probe set's target RNA species. Generating this value involves several discrete steps designed to subtract background levels, normalize signal intensities between arrays and correct for nonspecific hybridization. To compare the effectiveness of different analysis packages at each of these steps, we created multiple expression summary datasets using every possible  combination of the options described below. Algorithms were chosen for their popularity with microarray researchers and their open-source availability, and were generated using the implementations found in the Bioconductor 'affy' package . Figure ct Match  and gcrmh [gcrma ). The coMAS background [RMA) algorithm [An estimate of the background signal, which is the signal due to nonspecific binding of fluorescent molecules or the autofluorescence of the chip surface, was generated using two possible metrics. The ckground  is calculgorithm  subtractConstant is a global adjustment by a constant value to equalize the chip-wide mean (or median) signal intensity between chips. Constantsubset is the same global adjustment but equalizing the mean intensity for only the probe sets with fold change equal to 1. Invariantset [Invariantsetsubset is the same as invariantset but the rank-invariant set is selected as a subset of the probe sets with fold change equal to 1. Loess normalization [Loesssubset normalization is the same as loess but using only the probe sets with fold change equal to 1. Quantile normalization [Quantilesubset normalization is the same as quantile but normalizes the spiked-in and non-spiked-in probe sets separately.The signal intensities are normalized between chips to allow comparisons between them. Because in our dataset, a large number of RNAs are increased in S versus C (and none are decreased), commonly used methods often result in apparent downregulation for spiked-in probe sets in the 1x change category. We thus added a set of modified normalization methods which used our knowledge of the 1x probe sets. The following different methods were applied. riantset  is a nonlization  is a nonlization  enforcessubtractmm). The second is the method used in MAS 5.0, in which negative values are avoided by estimating the nonspecific signal when the MM value exceeds its corresponding PM intensity [PM only (no correction). The subtractmm and MAS methods are compatible only with the MAS background correction method; that is, it does not make sense to combine these with RMA background correction.We chose three ways to adjust the PM signal intensities to account for nonspecific signal. The first is to subtract the corresponding MM probe signal (ntensity . The thiMAS 5.0); median polish (RMA); or the model-based Li-Wong expression index (dChip). Analyses including the subtractmm PM correction method require dealing with negative values when PM is less than MM, which occurs in about a third of the cases. Within Bioconductor, the Li-Wong estimator can handle negative values, but the other two metrics mostly output 'not applicable' (NA) for the probe set when any of the constituent probe pairs has negative PM - MM. The result for MAS and median polish is NA for about 85% of the probe sets on the chip. To study the consequence of losing so many probe sets, we modified one of these two metrics (median polish) to accept negative (PM - MM) (medianpolishna), and added this metric whenever subtractmm was used.The 14 probe intensity values were combined using one of the following robust estimators: Tukey-biweight  when the probe sets in the lowest quartile of signal intensity are filtered out. The expression summary datasets which involve correcting the PM signal by subtracting the MM signal (subtractmm) have the highest correlation coefficient, because low-intensity probe sets have been filtered out during processing, as described above. We therefore suggest that an important feature of a successful microarray analysis is to account for probe sets with low signal intensity, either by filtering them out or by using a signal-dependent metric for significance. Several ways of accomplishing such filtering are described below.For each of the 150 expression summary datasets that we generated, fold changes between the S and C samples were calculated and then compared with the actual fold changes. Most expression summary datasets show good correlation between the observed and actual fold changes  [t-statistic has a constant value added to the standard deviation. This constant 'fudge factor' is chosen to minimize the dependence of the t-statistic variance on standard deviation levels. The second is CyberT [basic (Student's) t-statistic. For CyberT and the basic t-test, we performed the tests on the expression summaries after log transformation, as well as on the raw data. As shown in the example ROC curve, the CyberT statistic outperforms the other statistics for the vast majority of expression summary datasets  does not effectively filter out these same false-positive probe sets . Upon further inspection, we observed that the SAM algorithm favors using large values for the constant fudge factor, so that the t-statistic depends more on the fold change value, than on the noise level. The basic t-statistic is prone to false positives resulting from artificially low standard deviations, owing to the limited number of replicates in a typical microarray experiment  outperforms several other methods. Because the CyberT statistic clearly performs the best, we use only this statistic to compare the options for the other steps in microarray analysis, below.Because a typical microarray experiment contains a large number of hypotheses here 14,010) and a limited number of replicates (in this case three), high false-positive rates are a common problem in identifying DEGs. An important factor in minimizing false positives is to incorporate an appropriate error model into the signal/noise metric. We compared three ys (SAM) , in whic,010 and s Figure . Inspecth Figure . As showy = 0 when necessary. Owing to the significant improvement seen when the second normalization is used, the subsequent figures , or using the MAS 5.0 correction method, is better than using uncorrected or RMA-corrected PM values (PM-only). The MAS 5.0 method performs the best because it does not create any negative values. This result is in apparent conflict with the conclusions of Irizarry et al. [et al. use a test statistic that takes the variance into account, PM-only and MM-corrected methods (MAS) have similar sensitivity/specificity  because PM-only does not try to correct for nonspecific hybridization in a probe-specific fashion. In contrast, for the Latin square datasets used in [PM-only works just as well as MM-corrected methods because the contribution of nonspecific hybridization is constant. Therefore, datasets which compare substantially different RNA samples (such as two different tissue types) should probably be processed using the MAS 5.0 method for PM correction.With respect to adjusting the PM probe intensity with an estimate of nonspecific signal, Figure median polish (RMA) and the Tukey Biweight methods (MAS 5.0) perform the best. Figure Figure We were concerned that some of our analyses might be confounded by a possible correlation between low fold change and low expression summary levels, which could affect the interpretations of Figure perfect match and gcrma) to the control dataset. With respect to detecting the true DEGs, these two models perform reasonably well, although slightly less well than the MAS 5.0 PM correction method. When we consider only the low signal DEGs , gcrma outperforms perfect match, and is similar in effectiveness to the top analysis option combinations.Models dependent on probe sequence provide a promising route to improving the accuracy of nonspecific signal measures. Here, we applied two different models , which is the fraction of false positives within a list of genes exceeding a given statistical cutoff. We used our control dataset to compare the actual q-values for the 10 optimal expression summary datasets with q-value estimates from the permutation method implemented in SAM. As shown in Figure q-value calculations using each of the top ten datasets underestimate the actual q-value for a given cutoff. We attempted to reduce the contribution of biases inherent in any given data-processing step by combining the results from the top 10 expression summary datasets. The goal is to pinpoint those genes that are called significant regardless of small changes in the analysis protocol . To identify these 'robustly significant' genes, we created a combined statistic from the top 10 datasets depicted in Figure q-value estimate than any of the individual datasets. However, there is still considerable difference between the estimated and actual q-values. For example, if we estimate q = 0.05, the corresponding CyberT statistic has an actual q = 0.18, and if we estimate q = 0.1, then the actual q = 0.3. Therefore, until more accurate methods for estimating the false-discovery rate are developed, we recommend that a conservative choice of false-discovery rate cutoff be used (for example < 1%) to prevent actual numbers of false-positive DEG calls  from being too high.We have identified a set of analysis choices that optimally ranks genes according to significance of differential expression. To decide how many of the top genes to investigate further in follow-up experiments, it would be useful to have accurate estimates of the false-discovery rate (FDR or q) increases from 10% to 30%. Taking an upper acceptable bound for q as 10%, the maximum sensitivity obtained is about 71%. Thus, under the best-performing analysis scheme, roughly 380 (29%) of the 1,309 DEGs are not detected as being differentially expressed, with the number of false positives equaling about 105. At q = 2%, sensitivity reduces to around 60%, meaning that more than 520 DEGs are missed, albeit with fewer than 20 false positives.As the identities and relative concentrations of each of the RNAs in the experiment were known, we were able to assess directly the sensitivity and specificity obtained by the best-performing methods. Examination of the ROC curves in Figure q = 10%, sensitivity is increased to 93% when only cRNAs that differ by twofold or more are considered as DEGs . The reduction in sensitivity is almost wholly due to the low-fold-change genes: less than 50% of DEGs with fold change 1.5, and none of the DEGs with fold change 1.2, are detected at q = 10% , this is likely to prove a very real limitation to detecting DEGs. In cases where pure cell populations can be obtained, for example by laser capture microdissection, the numbers of cells are often small and RNA needs to undergo amplification in order to have enough for hybridization. Here, non-linearities in RNA amplification might also lead to observed fold changes that fall below the twofold level. We used three microarray replicates for this study, as this is frequently the number chosen by experimentalists because of cost and limiting amounts of RNA. One possible extension of this work would be to examine how many replicates are necessary for reliable detection of DEGs at a given fold change level.We have compared a number of popular analysis options for the purpose of identifying differentially expressed genes using an Affymetrix GeneChip control dataset. Clear differences in sensitivity and specificity were observed among the analysis method choices. By trying all possible combinations of options, we could see that choices at some steps of analysis are more critical than at others; for example, the normalization methods that we considered perform similarly, whereas the choice of the PM adjustment method can strongly influence the accuracy of the results. On the basis of our observations, we have chosen a best route for finding DEGs Figure . As any Drosophila Gene Collection release 1.0 cDNA clones [Drosophila arrays (DrosGenome1) using standard Affymetrix protocols. We chose to hybridize each replicate chip from an aliquot of a single C (or S) sample, resulting in technical replication; thus this dataset does not address the noise introduced by the labeling and mixing steps. The clones comprising each pool can be found in Additional data file 8, and the resulting Affymetrix chip intensity files (.CEL) files are available in Additional data files 6-7.PCR products from A clones  were genA clones . Each PCThe total amount of labeled cRNA that was added to each chip (approximately 18 μg) was comparable to a typical Affymetrix experiment (20 μg). Although we do not know the individual RNA concentrations, we estimate that these span the average RNA concentration in a biological GeneChip experiment. Our biological RNA samples typically result in about 40% of the probe sets on the DrosGenome1 chip called present, so the mean amount of individual RNA is 20 μg/ = 0.003 μg/RNA. In the C chips, the average concentration of individual RNAs in the different pools range from 0.0008 to 0.007 μg/RNA, so the concentrations are roughly similar to those in a typical experiment. We note, however, that there is no way to ensure that the concentration distribution is truly reflective of a real RNA distribution. This is especially true with respect to the low end of the range, as it is usually unknown how many of the absent genes on an array are truly absent versus weakly expressed and thus poorly detected by the analysis algorithms used. Therefore, our analysis possibly favors methods that perform best when applied to highly expressed genes.et al. [t-statistic variant: for the SAM statistic, false discovery rates from the authors' Excel Add-in software was used, whereas for the CyberT and basic t-statistics, the Bioconductor false-discovery rate implementation was applied, which includes an extra step to enforce monotonicity of the ROC curve. In our experience, this extra step does not qualitatively alter the results. All scripts generated in this study are available for use [All of the analysis was performed using the statistical program R , includiet al. ,32. In aet al. , MAS 5.0et al. , Perfectet al. ,21 and Set al.  executab for use ,28.n datasets and Cij, Sij are the logged signals for a given probe set in the jth C and S chips, respectively, in dataset i. The mean signal (for this probe set) for the C chips in dataset i is:Say we have  is the number of C chips in dataset i; similarly, the mean signal for the S chips in dataset i is:where The mean fold change over all datasets is:i is based on the CyberT estimate:The modified standard deviation for the C chips in dataset const is the weight for the contribution of the average standard deviation  for probe sets with the same average signal intensity as Cij. The modified standard deviation for the S chips in dataset i (sd.Si) is defined analogously. The pooled variance over all 10 datasets is defined as:where The variance between the 10 datasets is defined as:Then the combined statistic was chosen to be:2 fold change) vs A  plot for the comparison of two biological samples. Additional data file Additional data is available with the online version of this article. Additional data file contains a figure and explanatory legend showing the degree of overlap between two lists of differentially expressed genes. Additional data file A figure and explanatory legend showing the degree of overlap between two lists of differentially expressed genesClick here for additional data fileAll analysis option combinations used to generate the expression summary datasets in this studyClick here for additional data fileA plot of observed vs actual spiked-in fold changes at the probe levelClick here for additional data file2 fold change) vs A  plot for the comparison of two biological samplesAn example of asymmetric M , Affymetrix *.CEL files for the C chips in this datasetClick here for additional data fileA Zip archive containing plain text files (in Affymetrix CEL format), Affymetrix *.CEL files for the S chips in this datasetClick here for additional data fileDetailed information for the individual DGC clones used in this studyClick here for additional data file


Factor analysis is one of the most used statistical techniques to analyze the inter-relationships among symptoms reported by Gulf War veterans. The objective of this study was to apply factor analyses to binary symptom data from the UK study of Gulf War illness and the US Air Force study of Gulf War veterans, and to compare the symptom domains derived from the distinct samples.UK veterans of the 1991 Gulf War , individuals deployed to Bosnia on U.N. peacekeeping operations  and Gulf War-era servicemen  who were not deployed to the Gulf were surveyed in 1997–1998, and US 1991 Gulf War veterans from four Air Force units  were surveyed in 1995 to collect health characteristics including symptoms. Each sample was randomly split in half for exploratory and confirmatory dichotomous factor analyses with promax oblique rotation.Four correlated factors were identified in each of the samples. Three factors  overlapped considerably across the UK cohorts. The Gastrointestinal/Urogenital factor in the UK Gulf cohort was noticeably different from the Gastrointestinal factor identified from the Bosnia and Era cohorts. Symptoms from Gulf War UK and U.S cohorts yielded similar Gastrointestinal, Respiratory and Mood-Cognition factors, despite differences in symptom inventories between the two surveys. A Musculoskeletal factor was only elicited from the US Gulf sample.Findings of this report are consistent with those from other factor analysis studies that identified similar symptom dimensions between Gulf and non-Gulf War veterans, except that the Gastrointestinal factor in Gulf veterans included other symptom types. Correlations among factors raise the question as to whether there is a general illness, even if not unique to Gulf veterans, representing the common pathway underlying the identified factors. Hierarchical factor analysis models may be useful to address this issue. Reports that veterans of the 1991 Gulf War were suffering from unexplained signs and symptoms started to appear as early as one year after the conflict . Factor Several studies have applied factor analysis  to examine and compare the inter-relationships among symptoms reported by veterans -13. In gWhen symptoms are measured on a continuous scale normally distributed, linear factor analysis  can be The objective of this report was to apply dichotomous factor analyses to binary symptom data from two studies, i.e., the UK study of Gulf War illness ,17-19 anThe data used in this report came from two sources: the UK Study of Gulf War illness ,17-19 thDuring the past month, have you suffered from any of the following symptoms?") [current health problems [In the UK study, we considered the analysis of 50 symptoms that occurred in the preceding month ("ptoms?") ,17,18 . Exploratory dichotomous factor analyses  were perThe confirmatory dichotomous model  specifieOf the 3,454 veterans of the Gulf War, 93.3% were men, 75% were married or living with a partner, 92.5% had regular military status when they were deployed to the Gulf. Their average age was 34.4 years (standard deviation = 6.8). The Bosnia cohort had 1,979 veterans with average age of 29.3 years (standard deviation = 6.7) including 89.4% men, 57.5% married or living with a partner, and 91.1% with regular military status when deployed to Bosnia. The Era cohort included 2,577 veterans  and 48.8% regular military status).The US Gulf sample included 1,163 veterans who were 94.0% men, 74.9% married or living with a partner, with an average age of 37.9 years (standard deviation = 8.4).The most common symptoms across all UK groups were feeling unrefreshed after sleep, irritability, headaches, fatigue, sleeping difficulties, forgetfulness, loss of concentration, joint stiffness and flatulence/burping Table . The preThe exploratory sample consisted of 1,783 persons. The scree plot suggested 1 major factor, but it was not clear how many additional factors should be investigated (data available from authors). We removed the first eigenvalue from the plot, to better determine how much each additional factor contributed to the variance, and decided to examine 2 to 5-factor solutions. Although all solutions indicated a good fit between data and model (RMSEA ≤ 0.06), the 2-, and 3- factor models yielded non-interpretable factors, and the 5-factor solution could not be confirmed. Thus, we tested the 4-factor exploratory solution in the confirmatory sample that included 1,671 subjects. We specified the number of factors to be 4, the factor variances to be 1 and the leading symptoms of the first (pain on passing urine), second (loss of concentration), third (unable to breathe deeply enough), and fourth (tingling in fingers and arms) factors. Table The Bosnia Cohort exploratory sample included 1,008 subjects and the confirmatory included 971. A 4-factor solution with 32 symptoms was confirmed . Results for all 1,979 subjects are displayed in Table Although the constructs identified from symptoms reported by Bosnia veterans were similar to those confirmed in the Gulf War veteran sample, we were unable to confirm the Gulf War confirmatory 4-factor solution in the Bosnia sample. Some symptoms from the Gulf cohort Gastrointestinal/Urogenital factor loaded in several Bosnia cohort factors, yielding a structure that was difficult to interpret.There were 1,325 observations in the exploratory and 1,252 in the confirmatory samples. A confirmatory 4-factor model with 26 symptoms and all 2,577 subjects is displayed in Table The overlap of symptom composition across samples was remarkable for the Respiratory, Peripheral Nervous and Mood-Cognition factors Table . The facThe exploratory sample consisted of 590 subjects and the confirmatory included 573. A 4-factor solution with 26 symptoms was confirmed and results for all 1,163 subjects are displayed in Table We could not directly compare the factor structures because the symptom inventories were so different. For example, 3 peripheral nervous symptoms were asked from the UK veterans  while the US study included only 1 (numbness or tingling in fingers or toes). Thus, a separate factor could not be derived from the US study. Nevertheless, both UK and US data yielded similar constructs, namely a mixed gastrointestinal factor, a mood-cognition factor, and a respiratory-related factor. The main difference was that the musculoskeletal construct could not be confirmed in the UK Gulf cohort, and it represented a separate factor in the US sample Tables  and 5.The objective of this report was to identify and compare syndromes among 4 samples collected from UK ,17-19 anWe identified and confirmed at most 4 correlated factors in each of the samples. Three of the four constructs  overlapped considerably across the UK cohorts. These factors were identical to those derived in a linear factor analysis of these data . HoweverIn addition, despite differences in study designs, methods of data collection, military populations and symptom inventories between the UK and US studies of Gulf War veterans, Gastrointestinal, Respiratory and Mood-cognition factors were identified in both UK and US studies. Of note, although joint pain and joint stiffness were measured in both UK and US samples of Gulf War veterans, a Musculoskeletal factor was only elicited as a separate factor from the US data.In general, findings of this report were consistent with those from other studies that used factor analysis of symptoms to compare symptom patterns between Gulf and non-Gulf War veterans ,9-11. HoIn this report, we encountered difficulties confirming the dichotomous factor structures, or reproducing a factor structure in another sample, because many symptoms were rare, which created numerical problems. On the other hand, failure to reproduce factor structures across samples may also be due to different symptom distributions in the samples being considered, as was the case of the UK Gulf and Bosnia cohorts. We also acknowledge the difficulties in analyzing self-report symptom data. However, since the UK and US studies were independent of the military and confidential, we do not believe there was a reason form service personnel to exaggerate symptoms in order to gain compensation or eligibility for veterans.Finally, it must be noted that, in each of the UK or US cohorts, factors were moderately or highly correlated. Correlated factors are complex to interpret because it is difficult to separate their independent effects . This fiIn conclusion, considerable progress has been made in defining medically unexplained illness associated with deployment to the 1991 Gulf War. Our results from independent studies conducted in the UK and US confirmed occurrence of an illness comprised of 4 correlated groups of symptoms (factors) in deployed military personnel from both countries. Similar illness occurred in troops who did not participate in the Gulf War , so we believe that this pattern of symptoms is not unique to Gulf War service nor does it represent a unique illness or "Gulf War syndrome." In fact, similar illnesses to those affecting Gulf War veterans have been noted among veterans of US Civil War  and BritNone declared.RN conceived of this analysis was responsible for its execution and had primary responsibility for the manuscript; KI was instrumental in the conception and design of the UK veterans' study and had primary responsibility for its analysis; collaborated in analysis and interpretation of the present data and writing the manuscript; SW was Principal Investigator for the UK veterans' study, Collaborated in the concept of the present study and collaborated in analysis, interpretation and the manuscript; CU collaborated in the UK veteran's study and collaborated in analysis and interpretation of data and drafting the manuscript for this study; LH collaborated in the UK veteran's study and collaborated in analysis and interpretation of data and drafting the manuscript for this study; WCR was Principal Investigator of the US Gulf War study, conceived the idea for the present study, served as Principal Investigator for the present study and collaborated in all aspects of data interpretation and writing the manuscript.


ACTN4 cause an autosomal dominant form of human FSGS. We characterized the biological effect of these mutations by biochemical assays, cell-based studies, and the development of a new mouse model. We found that a fraction of the mutant protein forms large aggregates with a high sedimentation coefficient. Localization of mutant α-actinin-4 in transfected and injected cells, as well as in situ glomeruli, showed aggregates of the mutant protein. Video microscopy showed the mutant α-actinin-4 to be markedly less dynamic than the wild-type protein. We developed a “knockin” mouse model by replacing Actn4 with a copy of the gene bearing an FSGS-associated point mutation. We used cells from these mice to show increased degradation of mutant α-actinin-4, mediated, at least in part, by the ubiquitin–proteasome pathway. We correlate these findings with studies of α-actinin-4 expression in human samples. “Knockin” mice with a disease-associated Actn4 mutation develop a phenotype similar to that observed in humans. Comparison of the phenotype in wild-type, heterozygous, and homozygous Actn4 “knockin” and “knockout” mice, together with our in vitro data, suggests that the phenotypes in mice and humans involve both gain-of-function and loss-of-function mechanisms.Focal segmental glomerulosclerosis (FSGS) is a common pattern of renal injury, seen as both a primary disorder and as a consequence of underlying insults such as diabetes, HIV infection, and hypertension. Point mutations in theα-actinin-4 gene  Transgenic experiments in mice suggest that the human kidney disorder, focal segmental glomerulosclerosis (FSGS), is a result of both gain- and loss-of-function mechanisms ACTN4 mutations cause a form of focal segmental glomerulosclerosis (FSGS)  . This les (FSGS) .The four α-actinin genes encode highly homologous proteins that normally form approximately 100 kDa head-to-tail homodimers. While the best-defined function of α-actinin-4 is to cross-link and bundle actin filaments, α-actinins have been found to interact with a large and diverse set of other proteins . α-ActinACTN4-associated FSGS is inherited in an autosomal dominant pattern. By contrast, mice homozoygous for Actn4 null alleles have glomerular disease, while heterozygous Actn4 null mice have no readily apparent phenotype .We performed both transfection and nuclear injection studies in a conditionally immortalized podocyte cell line to look at the effect of disease-associated mutations on α-actinin-4 localization. Irrespective of the method used to express the mutant α-actinins in cells, we found altered localization of the mutants. Consistent with the altered sedimentation observed in vitro, mutant α-actinin-4 formed localized aggregates when expressed in cells. We used video microscopy to view the fate of the green fluorescent protein (GFP)–α-actinin-4 after nuclear injection of the cDNA. Similar results were observed in three independent sets of experiments. In each experiment, 15–35 cells were microinjected in the nucleus with plasmid DNA; of these, five to ten cells showed signal at 4–6 h after injection. Consistently, the mutants behaved abnormally, were unevenly distributed in the cell cytoplasm, and were much less dynamic compared with the wild-type proteins . These fActn4+/+, Actn4K228E/+, and Actn4K228E/K228E mice with either wild-type GFP–α-actinin-4 or K228E mutant GFP–α-actinin-4  to generate litters with wild-type, heterozygous, and Actn4K228E/K228E mice. We genotyped mice by testing for the presence or absence of an engineered silent EarI site as described previously  following incubation in methionine-deficient medium. In order to trace the newly synthesized 35S-labeled α-actinins, we used an α-actinin-4-specific antibody to immunoprecipitate α-actinin-4 from the cell lysates. (We detected no α-actinin-4 in the cell pellets.) As shown in 35S]methionine for 3 hours (pulse), following incubation in methionine-deficient media, and then incubated the cells in media containing excess cold methionine (chase) for different timepoints to follow the degradation of the newly synthesized α-actinin-4. As shown in We observed decreased mutant α-actinin expression in an immortalized knockin mouse fibroblast homozygous for the broblast D. To helActn4K228/K228E mice, as well as Actn4K228/+ and wild-type littermates. In Actn4K228/K228E mice as old as 13 mo, we saw no abnormalities by light microscopy with periodic acid–Schiff (PAS) and hematoxylin-and-eosin (H & E) staining. All of the 11 Actn4K228/K228E kidneys examined by electron microscopy had abnormalities in podocyte structure. Typically, these consisted of focal areas of foot process effacement . Only 10% (23 of 231) of the offspring of crosses between heterozygous mice were homozygous for the K228E change, suggesting increased peri- or neonatal lethality in the homozygous mice, similar to what we have observed in Actn4 null mice , heterozyogtes for either a null or K228E allele (Actn4+/– and Actn4K228E/+), and homozoygotes for either a null or K228E allele (Actn4–/– and Actn4K228E/K228E). Results were quite variable within each genotypic group of mice (likely reflecting differences in age and genetic background). However, the overall pattern of protein excretion was similar in the Actn4+/+, Actn4+/–, and Actn4K228E/+ mice, while both groups of homozygous mutant mice (Actn4–/– and Actn4K228E/K228E) had significantly greater—and similar—degrees of proteinuria  renal failure in adulthood.Human α-actinin-4-associated FSGS is characterized by a dominant pattern of inheritance. Affected individuals typically develop disease in adulthood. Some individuals develop progressive renal failure, others develop moderate proteinuria, while a few show no evidence of kidney dysfunction well into adulthood. This contrasts with other recently elucidated inherited disorders of the podocyte caused by mutations in the slit-diaphragm proteins nephrin and podocin, where disease typically presents in the neonatal period or in childhood and follows a recessive pattern of inheritance . Mice laThese phenotypic differences themselves suggest a different mechanism of disease from what is observed with slit-diaphragm protein defects. Our earlier experiments suggested that mutant α-actinin-4 binds actin filaments more strongly than wild-type α-actinin-4 in vitro. However, this may reflect a propensity toward oligomerization rather than increased F-actin binding per se. The finding that the mutant α-actinin-4 forms aggregates with greatly decreased half-life suggests two possible models to explain the human (and mouse) disease. One model would explain the development of podocyte damage as a direct effect of protein aggregation and the toxic effects of such aggregation, as is observed in several degenerative neurologic conditions such as Alzheimer and Parkinson diseases . The secWe do not regard these models as mutually exclusive. In fact, we believe it likely that the development of disease may involve both of these mechanisms. It is interesting to note that α-actinin-4-mediated kidney disease bears some similarities to the adult-onset neurodegenerative condition Huntington disease. In Huntington disease, dominant mutations that lead to expanded polyglutamine tracts cause neurodegeneration. The mutant huntingtin protein is misfolded and forms aggregates that are thought to have dominant, toxic effects on neuron function . These pACTN4 mutations become increasingly susceptible to minor insults. We note also that mice, unlike humans, express α-actinin-1 in podocytes .We note that, as shown in utations . AlthougActn4 knockin mice have no clear phenotype either by histologic analysis at the light and electron microscopic levels or by analysis of urine protein and serum creatinine. Even at more advanced ages, the Actn4K228E/+ mice appear normal. By contrast, we observe clear glomerular phenotypes in both Actn4–/– and Actn4K228E/K228E mice. Our genetic observations are consistent with our biochemical observations. Specifically, we believe that α-actinin-4 mutations lead to a reduction in normal α-actinin-4 activity and to protein aggregation and that glomerular phenotypes reflect both loss of normal α-actinin-4 function and toxic effects of aggregated α-actinin-4. While the disease observed in homozygous Actn4K228E/K228E mice may primarily reflect loss of function resulting from rapid α-actinin-4 degradation, heterozygous humans may show slow development of podocyte damage from the effects of α-actinin-4 aggregation.As indicated in Is alteration of α-actinin-4 expression or conformation a cause or a mediator of secondary forms of kidney disease? These seem plausible hypotheses given the data presented here, together with results from other investigators showing alterations in α-actinin-4 levels in association with proteinuria in certain animal models . This su2. Differentiated podocytes were cultured in the medium containing no γ-IFN at 37°C. Additional conditionally immortalized podocytes from “knockin” litters were generated exactly as described previously  and cultured as described previously . In brieeviously . FibroblFibroblasts were allowed to grow to confluence, then scraped off the tissue culture plate in the presence of cold phosphate-buffered saline (PBS) and spun at 3,000 rpm at 4°C for 10 min. Lymphocytes were isolated from whole blood with Histopaque-1077 solution  following the manufacturer's instructions. The pellets were resuspended in ice-cold lysis buffer . We collected the supernatant and estimated the protein concentration using either the Bradford method or equalizing the protein concentration in different lysates by Western blot using β-actin as a standard.We mutated a wild-type pBluescript-GFP-ACTN4 clone using a QuickChange kit  to create clones harboring each of three disease-associated mutations  . These mSucrose gradients of 5%–20% and 10%–40% were made using a buffer containing 0.02 M Tris–HCl (pH 7.5), 0.15M NaCl, 0.1 mM EDTA, and 0.2 mM of DTT and were internally calibrated with BSA, carbonic anhydrase, and catalase. In vitro translated and radiolabeled wild-type and mutant α-actinin-4  were loaded onto the gradient, centrifuged at 40,000 rpm for 15 h at 4°C, and eluted into 0.2 ml fractions. Eluates were analyzed by SDS-PAGE and autoradiography.35S]Methionine was added to a final concentration of 0.1 mCi to pulse the cells. Cells were pulse labeled for 0, 15, 30, 60, 120, 180, and 240 min. To study the degradation of α-actinin-4, cells were pulsed for 3 h and then chased for 0, 3, 6, 12, 20, 24, and 30 h with excess cold methionine. We used anti-α-actinin-4 antibody recognizing the N-terminus to precipitate α-actinin-4 from the cell lysates. Protein A–sepharose beads  were preincubated with the anti-α-actinin-4 antibody for 2 h at 4°C and then incubated with the lysates overnight at 4°C. The beads were washed with lysis buffer and resuspended in SDS-PAGE loading buffer. Samples were resolved on a 10% polyacrylamide gel and visualized by exposure to radiographic film. For lactacystin treatment, cells were first pulsed for 3 h as above, followed by addition of 2.5 μM lactacystin dissolved in DMSO  or 0.125% DMSO alone with cold methionine.Immortalized mouse fibroblasts were incubated in methionine-free MEM medium containing 10% FCS  and 25 mM HEPES for 20 min at 37°C. [For injection and imaging, cells were cultured on MatTek Corporation  35 mm coverslip dishes in F12 media  without phenol red and supplemented with 10 mM HEPES and antibiotics. Plasmid DNA at 0.5–2.0 ng/nl was injected in cell nuclei using a Narishige  IM-200 picoliter pressure injection system. OD microcapillary glass pipettes (1.0 mm) were pulled to a fine tip using a Narishige PB-7 needle puller. Cells were maintained at 37°C using a modified Harvard Apparatus  microscope incubator mounted on a Nikon  Diaphot 300 inverted microscope. Images were collected using a Princeton Instruments MicroMax 1300Y cooled CCD camera . Excitation and emission wavelengths were controlled using dichroic and bandbass filters from Omega Optical  and a Sutter Instrument  Lambda 10–2 filter wheel image acquisition. Device control and postacquisition processing were done with Isee Imaging Software .To display the changes in GFP–actinin distribution over time, images collected at 1 min intervals were used sequentially as red, green, and blue channels of a RGB composite image. Areas of signal that did not change have equal representation in each of the channels and generate a white signal in the final image. Areas of signal that did change on a minute-to-minute basis are indicated by either a red, green, or blue hue. For example, a region rich in red would indicate an signal present in the first image, but absent in the two sequential images, indicative of a withdraw or loss of signal in that region.Actn4 expression 58Og; Jackson Laboratory, Bar Harbor, Maine, United States). We verified excision of the neomycin resistance cassette by PCR. Heterozygous mice were crossed to obtain mice homozygous for the K228E substitution. Mice were genotyped for the K228E as described previously .Click here for additional data file.Video S2(11.8 MB MOV).Click here for additional data file.Video S3(10.9 MB MOV).Click here for additional data file.ACTN4; also LocusLink ID 81) and NM_021895 and NP_068695 . OMIM numbers are 603278 (FSGS-1) and 604638 (ACTN4).GenBank accession numbers for genes and proteins discussed in this paper are NM_004924 and NP_004915 (human