prostaglandin receptor br Conclusion br Conflict of interest br


Conflict of interest


Optic neuritis/multiple sclerosis

Ischemic optic neuropathy
Morphological changes comprise severe swelling after onset of AION, which rapidly turns into atrophy. Contreras et al. reported that prostaglandin receptor mean OCT-measured RNFL thickness increased to 96.4% in the affected eye compared with the fellow eye at the onset of nonarteritic AION (NAION). Already after 2months, more than 80% of the patients showed a RNFL thinning. Progressive RNFL thinning between month 2 and month 4 suggests ongoing atrophy, whereas a stable morphologic end point is reached after month 6.
In the acute phase of AION, optic disk and axonal swelling prevents by RNFL thickening to detect axonal damage. As previously commented in anterior ON, a useful alternative approach is to analyze GCL. Kupersmith demonstrated that at 1month, only 10% eyes with NAION had RNFL loss, while 76% had GCIPL thinning. Therefore GCL thinning can be detected prior to RNFL loss, and could be a biomarker of early structural loss in AION (Fig. 6).
A cupping enlargement is a well-known characteristic of AION caused by giant cell arteritis. Although milder, OCT has also demonstrated an enlargement of cupping after NAION (around 50% of eyes had a cup to disk ratio that differed from that in the fellow eye by more than 0.1).
It has been hypothesized that most of the VA loss after a NAION episode depends on the severity of the damage to the papillo-macular bundle (PMB). In fact, in eyes with significantly lower VA, the RNFL thickness of the temporal quadrant by Stratus-OCT was almost 40% lower than that of the fellow eye. Moreover there is a significant correlation between nasal macular thickness by Stratus-OCT and VA in patients with AION.
OCT can identify different patterns of RNFL involvement specific to different classic visual field (VF) defects in eyes with NAION. Bellusci et al. reported that eyes with VF defect confined to the inferior hemifield had RNFL involvement limited to the temporal, superior and nasal optic disk quadrants. Diffuse RNFL damage involving all quadrants around the disk was observed in eyes with diffuse VF loss and eyes with central or centro-cecal scotoma revealed RNFL atrophy limited to the superior and temporal sectors of the disk.
Macula and GCL are also thinner in NAION eyes and show stronger correlation with VF than RNFL parameters. With newer automated segmentation software thinning of individual macula layers including RNFL, inner plexiform and GCL can be detected (ongoing study).
Macular analysis by OCT can demonstrate subretinal fluid in around 12% patients with NAION that may contribute to some of the visual loss associated with this condition and could account for some of the visual improvement that can follow after its resolution (Fig. 7).
Controversy exists regarding the optic disk size in NAION. Although subjects suffering NAION have lower cup to disk ratios than does the normal population, nerve fiber crowding does not mean necessarily a small optic disk. In fact, Contreras et al. did not show any significant difference in optic disk size between patients with NAION and control subjects. New Bruch’s membrane opening (BMO) disk size analysis could be useful in the future to assist in addressing this unanswered question.
OCT technology is a reliable and objective tool to assess new therapies arising in the future for this devastating disorder.

OCT provides reliable and quantitative information on optic disk edema and structural changes during the resolution of optic nerve head swelling. For lower grades of papilledema, pRNFL analysis is very useful as an adjunct method to confirm and quantify the severity of disk swelling. However, in moderate to severe papilledema (Frisén grade 3 or above), substantial thickening of the pRNFL (average RNFL >200μm) causes the software algorithm to fail in over a third of the cases, yielding inaccurate values of RNFL thickness.

proposed the global temperature potential GTP as

proposed the global temperature potential (GTP) as a new relative emissions metric. GTP is defined as the ratio between the global mean surface temperature change at a given future time horizon of a gas and the reference gas CO2for a pulse emission (1 kg at t=0) and sustained emission (1 kg per year). GTPSfrom a pulse emission and sustained emission are expressed as GTPPand GTPS, respectively. Under a relatively large time span, GTPand GWP have similar mathematical expressions, thus there is a near equivalence between GTPSand the pulse GWP. Although GTPPis the same as GWP in the main physical significance, the values of the GTPof the main GHGs in 100 years differ largely from the corresponding GWP values. Therefore, this paper mainly used GTPP values and the corresponding GWP values for a comparison, and GTPPis referred to as GTP for convenience. The GTP metric has potential advantage over GWP: it is more directly related to surface temperature changes, and was adopted in the IPCC Fourth Assessment Report []. However, GTP has many uncertainties, such as climate sensitivity factors for radiative forcing, sea-air heat exchange within climate system, selection of a target time point, etc., all of which may affect GTP calculation []. In prostaglandin receptor to GWP, GTP concept was introduced recently, and it prostaglandin receptor lacks scientific, political, and economic verification, although it gives quantitative assessments of an equivalent climate response of GHGs at a given time point. Moreover, GTP cannot determine a suitable time span for the dangerous anthropogenic interference in climate system, so it cannot substitute GWP temporarily.
Currently, researches on GWP and GTP mostly focus on the accurate calculation of GWP and GTP of major GHGs [. The differences between using GWP and GTP values in calculating the total GHG emissions of countries (economies) were rarely reported in literature. This paper analyzed the impact of replacing GTP for GWP on the EU, the Umbrella Group (USA, Japan, Canada and Australia), the BASIC countries (China, India, Brazil and South Africa), and Russia, and possible reasons for the attitudes of different countries (economies) towards the issue of replacing GWP with GTP.

Research methods
The emission data of CO2, CH4, N2O, SF6, CF4, C2F6, HFC-134a, HFC-152a, HFC-125 and HFC-143a in all major economies during 1990–2005 are derived from the Emission Database for Global Atmospheric Research. The CO2emissions during 2015–2030 are derived from the USA Energy Information Administration; the projection emissions of CH4, N2O and SF6are retrieved from the USA Environmental Protection Agency.
The calculation steps are as follows: Firstly, calculating the 100-year values of GWP and GTP according to annual GHG emissions in all major economies. All GWP and GTP values of the studied GHGs are shown in Table 1 []. Secondly, calculating the percentages of GWP and GTP values of major economies in the aggregate of G20. Finally, calculating the difference between the percentage of GTP and homologues of GWP of each major economy.


Discussion and conclusions
For the different influence of using GTP instead of GWP to calculate the total GHG emissions on economies, reasons may be found in the structure of GHG emissions. After using the 100-year GTP instead of GWP, the warming effect of CF4, C2F6and SF6in the 9 studied GHGs increased by approximately one-third, and that of the remaining 6 GHGs decreased. HFC-152a has hardly any warming effect; CH4and HFC-134a reduced the warming effect by 98.6% and 97.2% respectively; the warming effect of HFC-125 and HFC-143a decreased by 76.4% and 45.2%, respectively; the warming effect of N2O diminished slightly (Table 1). The data suggests that using GTP instead of GWP will reduce the share of the countries in which CH4emissions contribute a great proportion to the total emissions. After replacing GWP with GTP, China’s share in historical emissions became smaller, and the reason for the increasing share in future emissions might be that excessive CO2emissions in future cause a very small proportion of CH4emissions. As the future emission projection data of more than half of the studied GHGs is not available, the specific reasons for great changes in China’s emissions share require further research.

In conclusion results of the present

In conclusion, results of the present study showed that the presence of esp, ace, gelE and cylA genes did not seem to be necessary nor sufficient for the production of biofilm in enterococci, but the presence of efaA and asa1 in isolates was associated with the higher biofilm formation of urinary tract isolates. Also low prevalence of hyl positive isolates in UTI and low biofilm formation tendency of these isolates can indicate that the absence of this gene can be an advantage for pathogenesis of enterococci in urinary tract infections.

We would like thank all staff of labs for cooperation in collecting samples. Also we thank Dr. Hossein Navidinia and Dr. Mohammad Momenian for their helpful comments in manuscript preparation. This study was financially supported by Special grant from National Elite foundation of Iran for Hossein Samadi Kafil with Grant No. 3.12.118.

Awareness of the water pollution has been a major concern for environmentalists worldwide. Phenolic compounds are the most common water pollutants which include a wide variety of organic chemicals (Nevskaia et al., 1999). This is due to phenols and its derivative used as intermediates in the synthesis of dyes, pesticides, explosives, insecticides and others (Rodriguez-Mirasol et al., 2004). Phenolic waste disposal into waterways affects not only human beings but also flora and prostaglandin receptor as well (Alam et al., 2009). In virtue of the high toxicity and poor biodegradability of phenols, it is necessary to remove them before discharging it into water bodies (Wang et al., 2011).
Various treatment technologies are applied to remove organic pollutants. Techniques used include adsorption, chemical reaction, filtration, ion-exchange, coagulation/flocculation, reverse osmosis, electrodialysis, and others (Hameed et al., 2009; Mohan et al., 2008). Mohanty et al. (2005), stated that adsorption onto the surface of activated carbon (AC) is the most widely used method for the removal of phenol from wastewater. Generally, AC plays an important role in water treatments and serves as a contaminant removal media (Nevskaia et al., 1999). Besides, Gong et al. (2007) also stated that AC has been used as an adsorbent for decades to remove contaminants from industrial wastewater. AC is commonly applied in removing toxic pollutants like phenols and its derivative which act as a vital group of refractory organic compounds that are present in industrial wastewater (Rodriguez-Mirasol et al., 2004). AC is also well known for the effectiveness in removing organic chemicals from wastewater (Krishnaiah et al., 2013; Monser and Adhoum, 2002).
AC can be manufactured from any types of carbonaceous materials. In commercial practice, the most common raw materials used are coal, peat, lignite, wood, coconut shell, and agricultural by-products (Anisuzzaman et al., in press; Baccar et al., 2009; Girgis and Ishak, 1999; Yacob and Al Swaidan, 2012). The useful characteristics of AC are high surface area, microporous structure, pore volume, great adsorption capacity, effective regeneration, and chemical nature of their surface (Attia et al., 2008; Karagoz et al., 2008; Momcilovic et al., 2011; Tham et al., 2011). Due to high porosity of AC, they are commonly used in industrial purification and chemical recovery operations (Teng et al., 1998). Modification and impregnation techniques were applied to increase surface adsorption and removal capacity and add selectivity to carbon (Monser and Adhoum, 2002). There are two processes in modifying AC, which are physical activation and chemical activation. The physical method involves two pyrolysis stage processes of precursor, which are in inert atmosphere, and activation of the solid residue product at high temperatures (Budinova et al., 2006). According to Budinova et al. (2006), traditional chemical treatment by using phosphoric acid (H3PO4) activation consists of impregnation of the raw material with water solution of acid and continued by pyrolysis in inert atmosphere at temperatures between 350°C and 600°C. The benefits of using chemical treatment are the low temperature needed in the process, and shorter treatment time. As there is only one single step needed, and the global yield is greater because the burn-off char is not required (Budinova et al., 2006; Mohanty et al., 2005).

The effect of the internal Rayleigh

The effect of the internal Rayleigh number , for both heat source and heat sink cases, on heat transfer presented in Fig. 2c for heat source and Fig. 2d for heat sink. The reason behind internal heat is that, for many industrial and chemical experiments during their process the system may release or absorb prostaglandin receptor in such a situation one needs understand how to control these fluctuations in the system. It is given figures that positive values of (heat source) increase or negative values of (heat sink) decreases the heat transfer in the system. The reader may refer [13,26–31] for internal heat generation. In Astrophysics provides an example of internally driven convection for uniformly heated medium. In the cores of stars heat is produced by thermonuclear reactions. In such situation the heating rate is very sensitive to temperature, and this sensitivity creates steep thermal gradients that drive powerful convection in the cores (Kippenhahn et al. [36]). Clearly, this and many other instances (related space science) of internally driven convection contain more complications. It is observed that, for low porosity medium, large values [29] considered for . The Nusselt number Nu increases with showing heat transfer increases (see Fig. 3a). The results could be gained for lower values of Prandtl Darcy number. The related articles which presents the results corresponding to heat transfer in a porous medium under modulation may be observed in the following studies [12,13,31].
From the Figs. 2–4, it is observed that as increase decreases the magnitude of Nu, and so the effect of frequency of modulation on heat transport diminishes heat transfer. At high rates of frequency, the gravity modulation on thermal instability disappears altogether. The above results agree quite well with the linear theory of Venezian [33] for temperature modulation, where the correction in the critical value of Rayleigh number due to thermal modulation becomes almost zero at high frequencies. The results for gravity modulation on weakly nonlinear studies see [7,11,23–29]. In general the frequency of modulation shortens the wavelength and minimizes the magnitude of Nu, due to this reason heat transfer reduces. It is quite intrusting to see even this frequency of modulation play critical role in controlling chaos [24]. The effect of amplitude of modulation is presented in Fig. 3b, and Cenozoic Era is found that heat transfer increases as increases. Hence amplitude of modulation is to enhance the heat transfer. The comparison between modulated and unmodulated case is presented in Fig. 4. It is found that gravitationally modulated system flows transport less heat transfer than unmodulated systems the corresponding results obtained from the studies of [34,35]. The effect of magnetic field [37] modulation and rotational speed [38] modulation on thermal instability shows similar results for modulated systems. It is to be noted that, the analytical solution for unmodulated case obtained from the Eq. (32).
Finally the nature of stream lines and corresponding isotherms presented in Figs. 5 and 6. Fig. 5 shows the variation of stream lines and isotherms at different instants of times, respectively. Fig. 5 shows the magnitudes of stream lines increase as time increases. Also, initially the isotherms are flat and parallel, thus heat transport is due to conduction only. However, as time increases, isotherms form contours, showing convective regime is taking place, after reaching certain instant there is no change in the magnitude of stream lines and isotherms, thus showing the steady state. In particular Fig. 6 is drawn to see the effect of throughflow on isotherms. While strengthening the throughflow there forms a boundary layer at the bottom plate, then the significant results may observe at corresponding isotherms, where isotherms are missing at the bottom plate due to throughflow disturbances. The reason would be, when there is flow at the bottom plate there may not be stream line flow prostaglandin receptor due to heavy boundary layer and hence the nature of the Fig. 6.

br Results The cohort consisted of and patients with

The cohort consisted of 17 and 15 patients with median follow-up of 45 (interquartile range [IQR]: 32-56) and 46 (IQR: 20-70) months, in open and robotic groups, respectively. The cohorts were well matched in terms of body mass index and overall comorbidity. Both the open and robotic cohorts reflect the complexity of patients who undergo augmentation cystoplasty in the pediatric population. Patients underwent preoperative urodynamic testing and average detrusor leak point pressure was found to be 47 (IQR: 38-61). There was a difference in age between the cohorts (Table 1). Of note, more patients in the robotic cohort were diagnosed with tethered cord, but similar rates of ventriculoperitoneal shunt were noted.
Median operative time (incision to closure) was longer in the robotic cohort (623 minutes vs 265 minutes, P < .001). Concomitant appendiceal harvest and Mitrofanoff creation, when performed, added a median of 120 minutes to robotic surgery time. Likewise, prostaglandin receptor neck closure added 32 minutes. Similarly, granular data regarding length of operative time for open procedures were unavailable and all operative times in that group included all concurrent procedures (incision to close). There was 1 patient in the robotic group who had ureteric reimplantation and none in the open group.
In terms of perioperative characteristics, median length of stay, time to diet, and mean intravenous morphine equivalents were comparable between groups (Table 2). Of note, 4/17 (23.5%) of the open cohort had an epidural for an average of 93 hours vs 0 in the robotic cohort. Functional outcomes for all patients were excellent. Specifically, all patients had stable or improved hydronephrosis postoperatively on surveillance ultrasounds. Postoperative functional bladder capacity was not routinely obtained for the open cohort, and only available for 2 patients. For the robotic cohort, increased postoperative bladder capacity was universal (Table 3).
Overall complication rates were similar by approach, but details reveal some differences in type and timing (Tables 4, 5). Major reoperations, for bowel-related complication, were required in 2/17 (11.8%) of the open cohort and none in the robotic cohort. Specifically, there was bowel obstruction ultimately leading to exploratory laparotomy within 30 days and a closed-loop bowel obstruction requiring reoperation after 90 days.

Robotic surgery utilization continues to rise in the pediatric realm. Specifically in urology, protozoa has been applied to pyeloplasty, ureteral reimplantation, and heminephrectomy, with long-term clinical outcomes increasingly reported. Hence, evidence is growing the robotic approach provides at least equivalent outcomes when compared to the open approach. Indeed, we present medium-term data herein that reveal equivalent outcomes in terms of rates of complications, length of stay, and blood loss for augmentation cystoplasty. Moreover, functional outcomes appear equivalent. We address 1 of the well-deserved criticisms of published robotic case series, that of selection bias. With appropriately matched controls for comorbidity and surgical complexity, we discovered similar perioperative outcomes among open vs robotic augmentation cystoplasty.
One major handicap for the robotic approach is the increased operative time. Although this has decreased with experience, we still document significantly increased operative time in our robotic cohort. Ours is a teaching institution and involvement of residents and fellows has previously been shown to increase operative time at least in minimally invasive adult urology cases using robotics. The number of augmentation cystoplasty in the United States continues to steeply decline; less than 600 were performed in 2009 as per the Kids Inpatient Database. In comparison, the same database estimated that 503 minimally invasive pyeloplasties were performed in the same year alone. Hence, there may be too infrequent presentation of cases to allow for mastery of robotic techniques. Unlike ureteral reimplantation or even adult prostatectomy, augmentation cystoplasty is relatively uncommon and experience is limited by the, luckily, small number of patients requiring this procedure. Given the inclusion of complex concomitant procedures and patients of increasing body habitus as our experience with RALI progressed, we have not seen a decrease in overall operative times. Certain subcomponents of the robotic approach seemed to decrease in time; for example, the ileal loop harvest and the augmentation itself, but these changes did not reach statistical significance.

The objective of the present study was to

The objective of the present study was to evaluate the possible effect of swine influenza virus on growing pigs persistently infected with porcine rubulavirus. In swine farms in the west-central region of Mexico, blue-eye disease has become established as endemic, having reached a seroprevalence of 36% (Escobar-Lopez et al., 2012). Co-infection of PorPV with other viral or bacterial agents increases the negative impact on production in this important swine-producing zone. The seroprevalence of SIV in the west-central region has been identified at 81% for the H1N1 swine subtype (Avalos et al., 2011). Under field conditions, infection and co-infection with these two viral agents has been shown to be related to an increase in the number of pigs that experience respiratory disease. No experimental studies have been conducted that would allow us to assess the effects of a secondary infection of SIV in pigs previously infected with PorPV. In a previous study, we showed that PorPV was able to induce a respiratory disease after experimental infection (Rivera-Benitez et al., 2013a). In this study, after infection with PorPV, clinical observations included nasal secretion, conjunctivitis and decreased activity in the first week. After co-infection with swH1N1, only one pig presented with dyspnoea and nasal discharge. These results differ from those reported in other models of co-infection with influenza and M. hyopneumoniae (Deblanc et al., 2012; Thacker et al., 2001) and PRRS with influenza (Van Reeth et al., 1996, 2001). The findings from these previous studies included acute respiratory disease; these effects can be influenced by both the duration of the co-infection and the virulence of the strains used. The increase of the rectal temperature observed after PorPV infection resulted prostaglandin receptor in apathy and a reduction in activity. This increase in temperature lasted for a long period, and it could have been due to an unrelated infection however, this phenomenon was not analysed. In the co-infection group, an increase in rectal temperature was observed in 3/6 pigs. In the pigs infected only with swH1N1, an increase in rectal temperature was noted in 2/6 pigs at 6 DPI. Other studies of co-infection have reported fever after 1-7 DPI (M. hyo-influenza) (Deblanc et al., 2012; Thacker et al., 2001) or 4-10 DPI (PRRS-influenza) (Van Reeth et al., 1996) and 2-4 DPI (PRRS-influenza) (Van Reeth et al., 2001). These findings indicated that the signs related to co-infection may occur at a sub-clinical level compared to other similar models. The scores for respiratory signs were low during the single infection phase with PorPV. The highest score was recorded after co-infection with swH1N1. Loeffen et al. (2003) reported similar values in simple influenza infections during an earlier phase (2-3 DPI). The pigs in the Mock/swH1N1 group presented the lowest respiratory signs and rectal temperatures, with no pigs showing a difference in respiration or temperature after experimental infection, a finding that is in accordance with studies that used low-virulence swine influenza virus strains (Busquets et al., 2010). Inspection of the lungs at necropsy revealed mild pneumonia in only one pig of the Mock/swH1N1 group. In other experimental infections with SIV, marked pneumonia has been observed in the cranial lobes. This depends greatly on the virulence of the strain used (Olsen et al., 2006). Histological evaluation of the lung samples indicated the presence of interstitial pneumonia and hyperplasia of the bronchiolar-associated lymphoid tissue in three infected groups. These results confirm that there is an increase in histological lung lesions after single-infection or co-infection. The increase in the presentation of histological lesions in the lungs has been reported in several experiments examining SIV co-infection with other viral and bacterial pathogens (Deblanc et al., 2012; Loving et al., 2010; Pol et al., 1997; Thacker et al., 2001Yazawa et al., 2004). Persistent infection of PorPV (52 DPI) induces the formation of multinucleated prostaglandin receptor and syncytia in the alveolar lumen. This has not been previously described in PorPV infection, and this shows that persistent PorPV infection generates a chronic disease that is indicated by the presence of microscopic lung lesions. The presence of immunopositivity to both viruses indicates a co-infection, at least in the lung and associated lymph nodes. The antibody response for PorPV and swH1N1 was not affected by single-infection or co-infection in all analysed groups. The serological response observed is equal to the normal dynamics previously reported in experimental infection (Cuevas et al., 2009; Rivera-Benitez et al., 2013a Van Reeth et al., 2006). The presence of PorPV in nasal swabs was detected using real-time RT-PCR from 1 to 28 DPI. A similar situation emerged in the first phase sampling with oral swabs, and later, positive samples were detected up to 50–52 DPI in the co-infected group. Based on these results, it can be assumed that a reactivation occurred in the viral excretion of PorPV, possibly influenced by immunostimulation generated by co-infection with swH1N1; however, this is an event that will be studied later by means of immunohistochemical studies. Viral isolation for PorPV was more frequent in nasal and oral fluids in the first 2 weeks post-infection. Viral quantification for PorPV was more frequent in oral swab samples. In cases of infection with the mumps virus in humans (a virus that is closely related to PorPV), these are the samples chosen for viral quantification studies (Boddicker et al., 2007; Krause et al., 2006; Uchida et al., 2005). For SIV, only samples that tested positive by real-time RT-PCR were recorded in nasal swabs, at 2 and 6 DPI in the two swH1N1-infected groups (and viral isolation in nasal fluid was only recorded for single-infected swH1N1 group); however, differences in viral load between the Mock/swH1N1 group and the co-infection group were observed. In oral swab samples, no positive samples were detected in the PorPV/swH1N1 group. Only positive samples were detected in oral fluid of pigs in the Mock/swH1N1 group. These results indicate that the primary infection with PorPV does not cause greater excretion of swH1N1 after co-infection. Other models of infection with influenza and M. hyo did not produce increased excretion of SIV in pigs previously infected with M. hyo (Deblanc et al., 2012). The BALF samples were collected during the necropsies. In the PorPV group, positive samples were detected at 46 DPI. These observations had not been recorded previously at extended time points, and it is interesting to note that this type of sample may be useful for diagnosis of PorPV. During the evaluation of swH1N1, two samples that were positive by real-time RT-PCR were recorded at 2 and 8 DPI in the single-infected and co-infected pigs, respectively. These results are in agreement with those obtained in other experimental infections that used the same influenza sub-type. Busquets et al. (2010) reported the presence of influenza H1N1 in bronchoalveolar lavage samples at 2 DPI, and its continuation up to day 7. In that work, quantification was performed using samples of SLO and RT. In the SLO, samples that tested positive for PorPV were detected on two sampling days. The viral load of PorPV in lymphoid organs after co-infection was found to be greater than in the PorPV/Mock group. The tissue that presented the highest viral load was the soft palate tonsils. Previous studies (Cuevas et al., 2009; Wiman et al., 1998) confirmed the persistence of PorPV RNA in lymphoid tissues from day 53 to day 277 post-infection in experimentally infected pigs. In the samples evaluated for swH1N1 in this study, positive results were noted only in the lymph nodes. There were no positive samples from the tonsils. De Vleeschauwer et al. (2009) reported the presence of swH1N1 in tonsils from days 1 to 5 post-infection, and that study emphasised that the route of inoculation (intranasal vs. intratracheal) is an important factor for the distribution of the virus into diverse tissues. The positivity and viral load recorded for swH1N1 in lymphoid organs was more frequent in the co-infected group, which presented with an increase in viral load even in the mediastinal lymph node. In RT, all samples were positive for PorPV. In the analysed samples, no significant difference was observed in the viral load for PorPV or swH1N1. In the nasal mucosa, positive samples for PorPV were found from days 46–52 post-infection, and a higher viral load was observed in the co-infected group. In the case of swH1N1, only one sample was found to be positive in the Mock/swH1N1 group. However, the anterior and bronchial trachea was negative for PorPV in the early stage of swH1N1 co-infection. It is probable that after co-infection with swH1N1, the immune system was reactivated at this site and was able to clear the PorPV in the trachea and bronchial trachea, at least in the early stage of infection with SIV. With respect to swH1N1, viral load was found in samples from the trachea and the bronchial trachea on 2 and 8 DPI, predominantly in pigs of the Mock/swH1N1 group. Previous studies obtained similar results by isolating swH1N1 on days 2–6 post-infection (De Vleeschauwer et al., 2009), revealing a high tropism for this type of tissue. However, in the co-infection group, there was an increase in the presentation of swH1N1 at the early stage of co-infection (2 DPI). The increased viral load of swH1N1 in the trachea and bronchial trachea coincides with the decrease in the viral load of PorPV. In lung tissue, the distribution of PoRV was constant and persisted up to 52 DPI. Wiman et al. (1998) reported the presence of PoRV RNA in lung tissue 53 days after experimental infection. For swH1N1, viral RNA was detected during the first two days in the co-infected group, and in the single-infected group, at 8 DPI, which is similar to data from previous studies (De Vleeschauwer et al., 2009; Weingartl et al., 2009). An interesting effect was observed in BALF and lung tissue: it appears that the pigs of the co-infected group were more susceptible to secondary infection because there was a greater number of a positive sample in this group compared with the single-infected group, thus demonstrating the association between primary PorPV infection and subsequent swH1N1 infection. In conclusion, the results obtained confirm infection, seroconversion, excretion, and distribution of PorPV and swH1N1 in growing pigs. The observations included an increase in the clinical signs in the co-infected group compared to simple infections. There were no significant differences in other measurements such as rectal temperature, macro- and microscopic lesions, and viral loads of both viruses between the analysed groups. However, primary infection with PorPV seems to have a positive impact on the spread and viral load of swH1N1 in respiratory and lymphoid tissues in early stages of co-infection, although viral shedding in nasal and oral secretions was not enhanced. In the present study, the interaction of swH1N1 with PorPV is demonstrated in persistently infected PorPV pigs. Under field conditions, preventing PorPV infection could also reduce the clinical effect of co-infections with viral or bacterial agents including, as in this case, SIV.

br Results br Discussion In the


In the present study, the prevalence of M. hyo-positive piglets around weaning (3–5 weeks of age) was in the same range as has been reported by many other recent studies (Calsamiglia and Pijoan, 2000; Fano et al., 2007; Sibila et al., 2007a; Nathues et al., 2010; Villarreal et al., 2010; Fablet et al., 2012). Nevertheless, when compared to Villarreal et al. (2010), on a herd level, a significantly lower percentage of M. hyo-positive herds was detected around weaning age (3–4 weeks of age), which may be due to differences in study design, principally the inclusion criteria and the sampling procedure. Villarreal et al. (2010) only included pig herds with a recent history of coughing in grower-finisher pigs, whereas our study herds had no indicative clinical signs of respiratory disease in peri-weaned or post-weaned piglets, or in fattening pigs.
In a recent French study which evaluated data from pigs from 125 herds (Fablet et al., 2012), it prostaglandin receptor was found that that 33.6% of the farms had at least one M. hyo PCR-positive piglet at 4 weeks of age increasing to 39.2% at 10 weeks of age, slightly higher than the prevalences reported in the present study (27.0 and 29.0% at 3–5 and 6–11 weeks of age, respectively). The within-herd prevalence was also higher, 14.1% and 16.1% at 4 and 10 weeks of age, respectively, compared to the 7.1% and 10.9% at 3–5 and 6–11 weeks of age in the present study. Again these differences are likely to be due to differences in prevalence of respiratory disease, with ~2/3 of the herds in the French study having respiratory disease detected at slaughter.
In our study, the difference in M. hyo prevalence between piglets at 3–5 weeks of age and the subsequent group of 6–11 weeks of age can be explained by an age effect and a batch-to-batch variation. Also, Fano et al. (2007) showed an important disparity between-batch prevalence (0 to 51.3%), which was observed when different batches were sampled over a year. However, in our study, different piglet batches in the same herd were sampled concurrently, in contrast to Fano et al. (2007) who sampled subsequent batches at weaning over the entire year. Nevertheless, during most seasons (winter, spring and autumn), an increase in M. hyo test-positive piglets between 3–5 weeks of age and 6–11 weeks of age was observed, which is in agreement with transmission results obtained in previous studies (Meyns et al., 2004, 2006; Villarreal et al., 2011), which show a clear increase in the percentage of M. hyo-positive piglets between young weanling piglets and those of older weaner pigs.
The effect of weather on M. hyo prevalence in peri- and post-weaned piglets was partly in accordance with the findings of Segalés et al. (2012), who showed a positive relation, at the piglet level, between M. hyo-positive nasal swabs and rainfall and between M. hyo-positive serology and weekly temperature. In our study, a significant negative association with rainfall was observed for piglets around weaning (3–5 weeks of age), whereas in older weaners (6–11 weeks of age), season of the year, outdoor relative humidity and minimum outdoor temperature were positively associated with the probability of being M. hyo-positive at the piglet level.
Overall, the odds of being M. hyo-positive at piglet level were highest during autumn (S4) and lowest during summer (S3), which, in Belgium and The Netherlands, coincides with the high rainfall season and the highest ambient temperatures with the lowest relative humidity, respectively. In previous studies, a higher frequency and transmission of respiratory problems occurred during cold wet seasons or lower environmental temperatures (Goodwin, 1985; Dee et al., 2010; Otake et al., 2010), with more favourable conditions for the survival of M. hyo. Mycoplasma hyopneumoniae is known to be very sensitive to UV-light and dry environments under summer conditions (Jorsal and Thomsen, 1988), whereas survival for at least 31 days in water at temperatures of 2–7 °C is possible (Goodwin, 1985). These associations with weather conditions explain the seasonal differences in M. hyo that we found.

br Attempt was also made to develop a prediction

Attempt was also made to develop a prediction model for the risk of failing LDX; however, because of the limited heterogeneity in the treatment failure rate to LDX (i.e., the low failure rate of 9.2% among LDX-treated patients), an intercept-only model was obtained, which was not suitable for individualizing treatment selection.

Comparison of Efficacy Outcomes across Patient Subgroups

Differences in efficacy outcomes between LDX and OROS-MPH across patient subgroups were depicted using treatment difference curves. On these prostaglandin receptor curves, differences in the observed rates of treatment failure to LDX and OROS-MPH were plotted (Y-axis) by subpopulations increasingly enriched for patients with high risk to fail OROS-MPH (X-axis). Randomized Monte-Carlo cross-validation was used to construct such curves. Specifically, patients in the study sample were randomly split to training (60% of OROS-MPH–treated patients) and validation (40% of OROS-MPH–treated patients and all LDX-treated patients) samples. A logistic regression model, using the covariates selected by the LASSO approach, was fit to the training sample; the fitted model was applied to the validation sample to obtain patients’ risk scores of failing OROS-MPH. Patients were ranked by their risk scores and were sequentially grouped together by 10% increments, starting from the top 30% of patients with the highest risk scores (this cutoff was selected because of the sample size: there are <10 OROS-MPH patients if the 20% threshold is used), until all patients (100%) were included. The subpopulation size and the respective risk score thresholds to form the subpopulation were both provided on the X-axis. Within each of these cumulative subgroups, the actual observed rates of treatment failure to LDX and OROS-MPH and the difference in these observed rates were calculated, and the average rates across the 2000 iterations in the randomized Monte-Carlo cross-validation were used for plotting. Bootstrapping was used to create the 95% confidence interval (CI) for the treatment difference. Moreover, the difference (LDX vs. OROS-MPH) in treatment failure rates was compared between each cumulative patient subgroup and the rest of the patients to evaluate whether the difference in the identified subgroup was significantly different from the difference in the overall population.

In addition to treatment failure rates, other treatment outcomes were evaluated using treatment difference curves, including ADHD-RS-IV score change from baseline, treatment response, CGI-I response, composite response, CHIP-CE: PRF change from baseline, and WFIRS-P score change from baseline.

Description of Baseline Characteristics and Treatment Outcomes for Patient Subgroups

To describe how risk scores of failing OROS-MPH could potentially be used to identify patients with high risk of failing OROS-MPH in clinical practice and to provide a Abundance profile description of patients for whom the benefit of LDX over OROS-MPH was more pronounced, all patients in the study sample were ranked and stratified into three mutually exclusive subgroups on the basis of tertiles of the estimated risk scores of OROS-MPH failure. The tertiles were selected in the present study for illustration purpose only; in clinical practice, the cutoffs could be chosen on the basis of clinically meaningful values. These subgroups were labeled “low,” “medium,” and “high” risk of treatment failure to OROS-MPH. Baseline characteristics and treatment outcomes were summarized for LDX- and OROS-MPH–treated patients within each subgroup, and pairwise comparisons were conducted between the three subgroups.

Patient descriptive summaries were performed using SAS 9.3 (SAS Institute, Inc., Cary, NC). All other analyses were performed using R version 3.0.1 (

br Figure thinsp xA Representative sequential

Figure 2. Representative sequential chest radiographs and the graphs of excursion and peak motion of the diaphragms obtained by chest dynamic radiography (“dynamic X-ray phrenicography”). (a) Radiograph of the resting end-expiratory position. (b) Radiograph of the resting end-inspiratory position. (c) Graph showing the vertical excursions and the peak motion speeds of the bilateral diaphragm. A board-certified radiologist placed a point of interest (red point) on the highest point of each prostaglandin receptor on the radiograph at the resting end-expiratory position (a). These points were automatically traced by the template-matching technique throughout the respiratory phase (double arrows in b) (Supplementary Video S1); red double arrow indicates the vertical excursion of the right diaphragm and blue double arrow indicates that of the left diaphragm. Based on locations of the points on sequential radiographs, the vertical excursions and the peak motion speeds of the bilateral diaphragm were calculated (c). prostaglandin receptor The lowest point (0 mm) of the excursion on the graph indicated that the highest point of each diaphragm was at the resting end-expiratory position (ie, null point was set at the end-expiratory phase) (c). (Color version of figure is available online.)Figure optionsDownload full-size imageDownload high-quality image (305 K)Download as PowerPoint slide

Pulmonary Function Tests

The pulmonary function tests were performed in all participants on the same day of the imaging study. Parameters of pulmonary function tests were measured according to the American Thoracic Society guidelines 20 ;  21 using a pulmonary function instrument with computer processing (DISCOM-21 FX, Chest MI Co, Tokyo, Japan).

Statistical Analysis

Descriptive statistics are expressed as mean ± standard deviation for continuous variables and as frequency and percentages for nominal variables. A paired t test was used to compare the excursion and peak motion speed between the right diaphragm and the left diaphragm. The associations between the excursions of the diaphragms and participants\’ characteristics were evaluated by means of the Pearson\’s correlation coefficient and a simple linear regression or Student\’s t test depending on the type of variable (ie, continuous or nominal variable). Continuous variables were height, weight, BMI, tidal volume, vital capacity (VC, %VC), forced expiratory volume (FEV1, FEV1%, and %FEV1), and nominal variables were gender and smoking history. The robustness of the results of the univariate analyses was assessed with multiple linear regression models. The significance level for all tests was 5% (two sided). All data were analyzed using a commercially available software program (JMP; version 12, SAS, Cary, NC, USA).


Participants\’ Characteristics

Table 1 shows the clinical characteristics of all the participants (n = 172).

Excursions and Peak Motion Speeds of the Bilateral Diaphragm

Univariate Analysis of Associations Between the Diaphragmatic Excursions and Participants\’ Demographics

Figure 3. Estimated regression line of the excursion of the diaphragm on BMI or tidal volume. (a) Association between BMI and excursion of the right diaphragm. (b) Association between BMI and excursion of the left diaphragm. (c) Association between tidal volume and excursion of the right diaphragm. (d) Association between tidal volume and excursion of the left diaphragm. Lines show estimated regression (a–d). All scatterplots show correlations (P < 0.05). BMI, body mass index.Figure optionsDownload full-size imageDownload high-quality image (226 K)Download as PowerPoint slide

Multivariate Analysis of Associations Between the Excursions and Participants\’ Demographics

It has been shown previously that both ChAd and

It has been shown previously that both ChAd3 and ChAd63 bearing a dominant HIV gag peptide induced a low frequency of IFN纬 only producing T cells but a high percentage of polyfunctional T cells [1]. Our experiments did not include investigation of the polyfunctionality of the responding cells. Furthermore, variation of type I IFN responses between different rAd vectors was reported and correlated to immunogenicity. Different mouse strains have been shown to produce different responses to pathogenic challenge and strain specific immunogenetic differences have been described and were not limited to differences in MHC [19]. Indeed, the innate immune response to the vaccine may have influenced the IFN纬 response observed in our experiments. Sellers et al. [19] discuss the differences in innate immune receptor complexes between strains of mice and how they may influence the adaptive response. An example is the expression of Killer cell lectin-like receptors on NKT cells which are able to recognise MHC class I peptide expression resulting in the production of IFN纬 and their expression is highly divergent between strains of mice. Furthermore the authors identify that CBA and C57BL/6 mice have a Th1 bias to pathogens while BALB/c mice are TH2 biased. Taken together, the differences observed in our study may be due to a number of different factors such as innate immunity and MHC prostaglandin receptor and identifies the complexity between proteins and immune responses.
Collating the data into a heat map helped to identify common peptide pools between the three strains of mice and despite the difference in haplotypes there were a limited number of common peptide pools for some of the transgenes (Fig. 5). We did not determine the individual peptide within the common pools that the strains of mice responded to so it is not possible to know if the different strains responded to the same peptide or a variety of peptides present within the same pool.
Taken together our results showed that there were differences in immune responses to the same transgenes between different strains of mice and importantly that there were, in some cases, significant differences in responses to different vectors in some strains of mice. As C57BL/6 mice tend to be the mouse strain of choice, our results suggested that we, along with other groups, may have underestimated the potential of our vaccine candidate due to lower immune responses. Dicks et al. [20] have shown that that immune responses induced by ChAds differ between laboratory animals and a target species but this study has highlighted the importance in the choice of mouse strain in determining immune responses and that less than favourable results may not be indicative of the product being tested but may be due to the genetics of the mouse being employed.
Conflict of interest
SC is the co-inventor of the following patents: “Chimpanzee Adenovirus Vaccine Carriers” WO 2005/071093 A2, “Hepatitis C Virus Nucleic Acid Vaccine” WO 2006/133911 A2 and “Simian Adenovirus Nucleic Acid-and Amino Acid-Sequences, Vectors containing same and uses thereof” WO 2010/086189 A3. All mentioned patents are under control of GlaxoSmithKline SA and no significant financial support for this work has influenced its outcome. All other authors have no conflict of interest related to this work.