DOC is a semi synthetic taxane one

DOC is a semi-synthetic taxane, one of many mitotic inhibitors that act by binding to the beta-tubulin sub-unit of micro-tubules, resulting in nos inhibitor arrest and apoptosis (Gueritte-Voegelein et al. 1991). In the present study, the inhibition of tumor cell proliferation was significantly greater in the DOC and DOC-MBs/LFUS groups, as evidenced by the decreased PCNA-LI, which was consistent with other studies (Kang et al. 2010; Yang et al. 2012). However, the level of cell apoptosis was not obviously different among the groups, although it was slightly higher in the DOC and DOC-MBs/LFUS groups than in the control group. Observations of tumor morphology revealed that coagulative necrosis was common in all the groups, particularly in the groups that were treated with LFUS. Therefore, the level of cell apoptosis in all the groups may not be as evident because of the large fields with obvious coagulative necrosis within the tumors, which may have contributed to the difference between our results and those reported in other studies (Kang et al. 2010; Yang et al. 2012). Meanwhile, the inhibition of tumor cell proliferation and the PCNA-LI in the LFUS and NMBs/LFUS groups were not consistent with the tumor growth IR. We hypothesized that this result may have been caused by obvious coagulative necrosis in tumor tissue due to the effects of LFUS. Generally, because of thermal and non-thermal (including cavitation and shear stress) effects, US has been widely used and developed in clinical therapy for many diseases, including tumors (Chung et al. 2012; Escoffre et al. 2013; Kotopoulis et al. 2013; Phenix et al. 2014; Tinkov et al. 2010). It is well known that high-intensity focused US can induce coagulative necrosis in tumor tissue to achieve a therapeutic effect based on the thermal effect of US (Jenne et al. 2012), but low-intensity US achieves cell killing through apoptosis, which is mainly mediated by the cavitation effect of US (Feril and Kondo 2004, 2005). However, in the present study, there were larger necrotic lesions within the tumor and higher levels of skin ulceration in the groups that were treated with LFUS. These effects might have resulted from the thermal effects of LFUS. Further investigations are needed to validate these findings.

Conclusion

Acknowledgments

Introduction
Ultrasound contrast agents (UCAs) have been used extensively in contrast-enhanced ultrasonography (CEUS) near the bone cortex, particularly for monitoring free flaps (Chang et al. 2012; Kornmann et al. 2010; Krix et al. 2005; Winter et al. 2001), because UCAs present strong non-linear acoustic responses under insonation (de Jong et al. 2000; Goldberg et al. 2001). On the basis of the non-linear acoustic responses of UCAs, CEUS with second harmonic imaging and pulse inversion harmonic imaging, even subharmonic imaging techniques, has been used to detect dynamic microvascular perfusion, analyze the patency of microvascular anastomoses, and evaluate the microcirculation of flap tissues near the bone cortex (Forsberg et al. 2006; Geis et al. 2012; Kiessling et al. 2011; Lamby et al. 2009; Prantl et al. 2007). The strong backscattered echoes from UCAs can contribute to distinguishing the perfused regions from the biceps, forearm flexor muscles, and tibialis anterior (Krix et al. 2005). The replenishment kinetics of microcirculation near the humerus, ulna, radius, and tibia cortex have also been analyzed using CEUS (Duerschmied et al. 2006; Lamby et al. 2009). To clearly detect capillary perfusion in tissue layers near the bone cortex as mentioned above, CEUS should be applied with high resolution and better contrast-to-tissue ratios (CTRs) (Lamby et al. 2009; Prantl et al. 2007).
Contrast-enhanced ultrasound images near the bone cortex may, however, be affected by guided waves generated from the bone cortex, because the signal-to-noise ratio of acoustic signals is disturbed by guided waves that propagate in the surrounding soft tissue (Moilanen et al. 2006; Ta et al. 2009). These unique guided waves are generated from the bone cortex and leak to surrounding tissues when transmission waves hit the bone (Määttä et al. 2009; Moilanen 2008; Nicholson et al. 2002; Lee and Kuo 2006; Protopappas et al. 2006; Ta et al. 2009). They are multimodal and frequency dispersive because of their non-linear propagation (Moilanen 2008; Nicholson et al. 2002; Protopappas et al. 2006). These guided waves have also been used to detect and trap microdroplets, gas bubbles, and submicron particles in acoustic manipulations (Lindner et al. 2008; Schmitt et al. 2010; Wan et al. 2012). However, such detection is limited to the linear characteristic of guided waves (Zhang et al. 2014), and information on UCA responses to frequency-dispersive guided waves is lacking.

The second sample was an exchange biased sputtered sample comprising

The second sample was an exchange biased sputtered sample comprising a multilayer structure of ferromagnetic NiFe layers between anti-ferromagnetic FeMn layers with the structure NiFe/(FeMn/NiFe)×10 grown on an oxidised Si substrate with a capping layer of 5nm of Ta. The NiFe layers had an average thickness of 16.5nm and the FeMn layers an average of 12.8nm, measured from high resolution STEM. The samples were grown at Queens University Belfast in their UHV co-sputtering system [33]. To demonstrate the magnetic capability of the microscope a cross-section sample was prepared using focused ion beam methods resulting in a section which was ∼80nm thick. The exchange bias coupling between the AF and FM layers shows hysteretic behaviour in the continuous film sample with the individual layers reversing in steps so that the sample reversed completely in a field of ∼150Oe. However in the case of the cross-section the sectioning has in effect patterned each FM layer into a nanowire geometry and the fields required to reverse each layer were much higher. Using the ARM with CESCOR it was possible to image the state of each layer and map induction changes by using the objective lens field and tilting to reverse the magnetic state of the layers. Initially the sample was immersed in a large field (around 1000Oe) to set all the layers in parallel alignment. The DPC image component showing the magnetic induction parallel to the interfaces is shown in Fig. 4(a) where the ferromagnetic NiFe layers appear as bright stripes in the image and the FeMn layers are grey indicating no net induction component in these regions. The arrows at the top of the image indicate the direction of magnetization in each ferromagnetic layer. The variation in nos inhibitor within the stripes is a consequence of the granular structure of the film and this gives rise to a diffraction contribution in the phase contrast image. A linetrace from the area indicated by the red rectangle in Fig. 4(a) is shown below the image, which averages the signal over a 40nm width to reduce the effects of diffraction contrast from the granular structure. The linetrace is shown quantitatively as a deflection angle in microradians, noting that 50μrad corresponds to an integrated induction of 80Tnm. Thus for a ∼80nm thick cross-section this is consistent with a saturation induction of the permalloy of 1.0T. However it should be noted that there is significant amount of non-magnetic contrast from the grain structure and focused ion beam damage from the cross-section fabrication to cause variations in the signal observed in the trace and images. The profile shows the magnetised layer variation where each magnetic layer is around 16–17nm wide (i.e. the thickness of the deposited film) and the AF layer is 13nm wide. By tilting the sample in the objective lens field the magnetic state was altered: individual layers switch and an example of the state part-way through the reversal process is shown in Fig. 4(b). Here seven of the eleven magnetic layers have switched their direction of magnetisation and now appear dark, with one partially switched as indicated by the arrows above the image. The linetrace below the image shows the deflection/induction in the ferromagnetic layers very clearly and indeed the transition between the FM and AF layers shows a variation on the order of 5nm.

Conclusion

Acknowledgements
We would like to thank colleagues at JEOL, JEOL (UK), Gatan, Deben UK Ltd. and Andrew Armit Designs for their input to the development of the instrument. Furthermore we thank colleagues at the Technical University of Eindhoven for provision of the EBID sample. Additionally we are grateful to Prof. R. Bowman and Dr. S. O’Reilly of Queen’s University Belfast for provision of the exchange biased sample and to Mr. F. Gonclaves and Mr. W. Smith for preparation of the cross-sectional sample. We also acknowledge financial support from the Scottish Universities Physics Alliance (SUPA), the University of Glasgow and Seagate.

In the present study three kinds of

In the present study, three kinds of anti-pig CD4 monoclonal antibodies, 74-12-4, MIL17, and PT90A, could not be detected in the CD4 molecule in CD4.B Microminipigs. Because the epitope sites of these nos inhibitor have not been published (Pescovitz et al., 1994; Haverson et al., 2001; Saalmüller et al., 2001), it is unknown whether the epitope sites are the same or different among these three antibodies. If the epitope sites are different, the failure of CD4 cells to react with anti-CD4 antibodies suggests a different structure of CD4 molecules between the CD4.A and CD4.B pigs. These differences may be in multiple positions and/or in large parts of the CD4 molecule. Polymorphisms in the CD4 gene at exons 3 and 4 were found in NIH miniature swine, and these polymorphisms were thought to be the cause of CD4 cell molecule failure with the cross-reactivity of anti-CD4 antibody (74-12-4) (Gustafsson et al., 1993). However, Microminipigs did not have any consanguinity with NIH miniature swine (Kaneko et al., 2011), so the origin of CD4.B is unknown. DNA sequencing of CD4 genes may be possible to elucidate the cause of the non-reactivity of CD4 cells to anti-CD4 antibodies.
The CD4+CD8+ T cells often found in porcine PBMCs were driven by CD4+CD8− T cells and increased with aging in NIH miniature swine (Zuckermann and Husmann, 1996) and crossbred pigs (Summerfield et al., 1996; Yang and Parkhouse, 1996; Zuckermann and Husmann, 1996). In CD4.A pigs, CD4+CD8+ cells increased and CD4+CD8− cells decreased with aging. Thus, CD4+CD8− T cells changed to CD4+CD8+ T cells with aging in Microminipigs. On the other hand, CD4+CD8+ cells could not be observed in CD4.B pigs. The fluorescence of CD8+ cells in CD4+CD8+ cells are expressed as CD8 dull cells as shown in NIH miniature swine with non-reactive cells to the anti-CD4 antibody by a histogram analysis of CD8 lymphocytes (Sundt et al., 1992). Also, in Microminipigs, the CD8 dull cells were observed in the CD8+ T cell population in CD4.B and CD4.A pigs. Therefore, CD4.B Microminipigs may also have CD4+CD8+ T cells, which means that the CD4 molecule was expressed on their helper T cells. Moreover, there were no significant differences in the frequencies of CD3+ and CD8+ cells in PBMCs between CD4.A and CD4.B pigs. These results also imply that the CD4 cells in CD4.B pigs did not express the epitope identified with three anti-pig CD4 monoclonal antibodies. The CD4 molecules in CD4.B pigs may be just undetected with the three kinds of anti-swine CD4 antibodies used in the present study. In CD4.B pigs, the CD4+CD8− and CD4+CD8+ cells would be included in populations of CD4−CD8+ and CD4−CD8− cells. Non-detection of CD4+CD8− and CD4+CE8+ cells in CD4.B pigs may be the cause of greater percentages of CD4−CD8+ and CD4−CD8− cells in CD4.B pigs.
The CD4 molecule is essential for antigen recognition between the T cell receptor and MHC class II molecule (Doyle and Strominger, 1987; Miceli and Parnes, 1993; Wang et al., 2001). In this study, the difference of CD4-detectability did not result in significant differences in the populations of CD3+ and CD8+ cells and plasma IgG and IgM concentrations, although plasma IgM concentrations seemed to be slightly lower in CD4.B pigs. However, these assessments reflect just one immunological aspect. Microminipigs have been selected to make their body size smaller. The decrease in incidences of CD4.B pigs may indicate the possibility of an association with CD4 types and physical flames of pigs.
In this study, we found that there were two types of pigs with reactive and non-reactive CD4 to available anti-pig CD4 antibodies in the Microminipig herd. The breeding studies implied that CD4.A pigs were homozygous for CD4.A and heterozygous for CD4.A and CD4.B. In contrast, CD4.B pigs were only homozygous for CD4.B. A lymphocyte subpopulation analysis suggested that failure to detect CD4 cells might be because of a loss of expression of an epitope detected with available anti-CD4 monoclonal antibodies. CD4.B pigs did not have any clinical immunological abnormalities. However, the 74-12-4 antibody inhibited proliferative responses of peripheral blood lymphocytes to phytohaemagglutinin, hen egg lysozyme, and allo-peripheral blood lymphocytes with different MHC (Pescovitz et al., 1985). Therefore, loss of the epitope of the 74-12-4 antibody in CD4.B pigs might cause some functional immunological differences if the cause of failure to detect CD4 cells is loss of expression of an epitope of the antibody. Moreover, the prevalence of CD4.A and CD4.B in the Microminipig herd suggests some reproductive differences because the proportion of CD4.B pigs seemed to decrease from 2007. CD4.B pigs have a disadvantage in their use of anti-pig CD4 monoclonal antibodies, which might have a functional or phenotypic significance. To elucidate the functional or phenotypic differences between CD4.A and CD4.B pigs, further detailed studies are needed under uniform conditions such as age, rearing environment, and possession of SLA haplotypes. Future, detailed studies should at least consider a breeding program to establish a lineage with either SLA homozygous and CD4.A or CD4.B homozygous. Currently, studies are in progress to characterize the variant gene and ongoing efforts to develop a monoclonal antibody to identify the CD4 in CD4.B pigs.

Three dimensional ultrasound has been reported to be more accurate

Three-dimensional ultrasound has been reported to be more accurate than 2-DUS in calculating pulmonary volume (Riccabona et al. 1996). This is of great importance in the prenatal diagnosis of pulmonary hypoplasia, a condition associated with high rates of neonatal morbidity and mortality. Pulmonary hypoplasia has an incidence of 11 to 14 per 10,000 live births in the general population (Laudy and Wladimiroff 2000) and is characterized by reduced numbers of pulmonary cells, bronchial trees and alveoli, with consequent decrease in lung size and weight (Lauria et al. 1995).
Fetal lung volumetry, in normal and high-risk conditions for pulmonary hypoplasia, has been obtained with both the multiplanar and VOCAL methods (Gerards et al. 2006; Ruano et al. 2006b), even though VOCAL has several advantages over the multiplanar method. These consist of the ability to include smaller portions of the lungs extending below the dome of the nos inhibitor and the possibility of modifying the contour along each plane (Peralta et al. 2006). In addition, VOCAL has been more accurate than the multiplanar method in calculating lung volume in fetuses with congenital diaphragmatic hernia (Ruano et al. 2006b). Using the VOCAL method at 30° of rotation, Peralta et al. (2006) and later Werneck Britto et al. (2009) found that mean fetal lung volume increased with gestation from 0.6 to 4.6–6.3 mL nos inhibitor at 12 wk to 20.5–30 mL at 32 wk and from 9–12.5 cm3 at 24 wk to 22–31.8 cm3 at 32 wk. Furthermore, Ruano et al. (2009) reported that the ratio of observed/expected total fetal lung volume, as measured by 3-DUS, was the most accurate predictor of pulmonary hypoplasia and pulmonary hypertension and, thus, perinatal mortality.
Fetal renal malformations are frequently detected in ultrasound examinations during routine prenatal scan, and assessment of fetal kidney volume can help predict abnormal renal function and improve prenatal care and/or postnatal management. Yu et al. (2000) assessed fetal kidney volume using the multiplanar method in 152 normal pregnancies at 20 to 40 wk of gestation. Mean fetal kidney volume ranged from 1.49–1.8 mL at 20 wk to 1.63–1.8 mL at 40 wk. Calculating fetal kidney volume using VOCAL with a 30° angle of rotation, Tedesco et al. (2009) determined that the mean volume ranged from 4.5 cm3 at 24 wk to 12.1 cm3 at 34 wk, with no statistically significant differences between the two fetal kidneys.
The same results (4.0 cm3 at 20 wk to 44.9 cm3 at 40 wk) were reported by Yoshizaki et al. (2013). Chang et al. (2003) observed that fetal liver volume assessed by 2-DUS (craniocaudal × anteroposterior and laterolateral × 0.42) was significantly smaller than the volume determined by 3-DUS (multiplanar method). Furthermore, measurements of fetal liver volume obtained by 3-DUS are more reproducible than those obtained by 2-DUS. The new constant of 0.55 was determined by polynomial regression, so that fetal liver volume obtained with 2-DUS is similar to that obtained with 3-DUS. The constant of 0.42 was determined by Gimondo et al. (1995) in 327 fetuses at 20 to 40 wk of gestation using 2-DUS.
Boito et al. (2003) assessed fetal liver volume with the multiplanar method and its relation to umbilical venous flow and maternal glycosylated hemoglobin (HbA1c) in pregnancies complicated by diabetes mellitus type I. Data on 32 fetuses of diabetic mothers were compared with those for a control group. Boito et al. (2003) observed a statistically significant difference in fetal liver volume between fetuses of diabetic mothers and controls (mean: 45.9 mL vs. 38.3 mL, respectively). Dos Santos Rizzi et al. (2010) determined reference ranges for fetal liver volume using 3-DUS with a new multiplanar method. These authors completed a longitudinal study involving 250 fetal liver volume measurements taken during 53 normal pregnancies at 27 to 38 wk. Mean fetal liver volume ranged from 43.5 cm3 at 27 wk to 130.5 cm3 at 38 wk. The new multiplanar technique had good intra- and inter-observer reliability.

All of the theoretically predicted wave

All of the theoretically predicted wave-arrivals are also present in the measurements. The difference between laser pulse intensity distributions is evident when comparing Figs. 7 and 8. The most pronounced difference is observed in the Rayleigh wave where its positive and negative polarity peaks from the Gaussian source are closer together, while from the top-hat source, the Rayleigh peaks are further apart.

Conclusions

Acknowledgements
The research was conducted as a part of the Optodynamics program (P2-0392), in duration from 2015-1-1 to 2019-12-31, financed by the Slovenian Research Agency.

Introduction
Array transducers in medical ultrasound imaging facilitate forming images with focused beams. Appropriate delays and weights are applied to the received signals at each array element to form an arbitrary beampattern which can focus on the desired direction. Delay-and-sum (DAS) beamformer is a conventional data-independent beamformer due to its easy and low cost implementation. This beamformer chooses a pre-defined weight vector despite of the incoming data to form an image. However, the classic problem dealing with the DAS is a trade-off between the mainlobe width and sidelobe levels. The narrower mainlobe, which causes better lateral resolution, increases the sidelobe levels, leading to worse contrast, and vice versa. Aperture shading is used to find the proper weight vector for desired resolution but the limitation is still remained; resolution and nos inhibitor cannot be improved simultaneously [1].
Adaptive beamformers have been investigated to overcome the problem of DAS beamformer. These beamformers use the incoming data to obtain the apodization vector at each imaging point instead of choosing a fixed weight vector. An adaptive beamformer recently applied in medical ultrasound imaging is the minimum variance (MV) beamformer. This beamformer maximizes the output signal to interferences plus noise ratio (SINR) while preserving the power in the desired direction. MV beamformer offers better resolution and contrast due to its capability to suppress the interferences. Various approaches to apply the MV beamformer and improve its performance in medical ultrasound imaging have been addressed in the literature [2–6].
The main problem of the MV beamformer is its high computational complexity. Specifically, the complexity of the DAS beamformer is linear with the number of array elements, , while the complexity of the MV beamformer is as high as due to the inversion of the array covariance matrix. This higher order of complexity makes it difficult to implement the MV as a real-time beamformer when the number of array elements increases. So, reducing the computational complexity while retaining the benefits of the MV beamforming would be necessary for real-time implementation.
Recently, several approaches have been proposed to reduce the computational complexity of the MV beamformer. Nilsen and Hafizovic [7] applied the beamspace adaptive beamformer in ultrasound imaging which maps the received data to a set of orthogonal beams. Using the new projected data with lower dimension, the size of the array covariance matrix can be reduced to the number of selected beams instead of the number of subarray elements and as a consequence, complexity reduces significantly. Synnevag et al. [8] proposed a beamformer which selects a window from a list of predetermined windows that minimizes the output power. In other words, it chooses the apodization weights at each point separately and depending on the incoming data. This method reduces the complexity to that of the DAS beamformer multiplied by the number of predefined windows. The performance of this beamformer is much related to its windows and hence, for different scenarios, choosing appropriate windows would be necessary. A different low complex method has been suggested by Asl and Mahloojifar [9] in which they showed that assuming spatial stationarity is a good approximation in medical ultrasound applications, allowing us to apply the Toeplitz structure to the estimated covariance matrix. Dimension reduction using principal component analysis (PCA) has been proposed by Kim et al. [10]. They used a transformation matrix achieved by eigen-decomposition of a set of weight vectors obtained by a pre-determined phantoms and approximated the MV weights by a linear combination of a few selected dominant principal components. The complexity of this beamformer is same as the beamspace beamformer. The performance of this fast MV beamformer depends on the training set which should be chosen as close as possible to the real imaging environment. Another approach has been suggested by Sakhaei [11]. He proposed decimating the received signals along spatial domain in which the decimated data with reduced dimension, leads to estimate the lower-dimension array covariance matrix that can be inverted with less computational complexity. Real-time implementation of the MV beamformer for cardiac imaging has been claimed by Asen et al. [12]. They used the parallel processing power in graphic processing unit (GPU) combined with the beamspace beamformer to real-time implementation of the MV beamformer. Since the MV obtains the weights at each point independently, this process can be done with a parallel strategy. While, GPU and its ability to parallelize the time consuming tasks make it feasible to use complex algorithms in real-time imaging, the demand to reduce computational complexity is still alive. Low complex imaging approaches with GPU’s power facilitate making images with higher frame rates and lower pixel spacing.

Acquisition of a TAW transcranial Doppler image occurred more frequently

Acquisition of a TAW transcranial Doppler image occurred more frequently among male than female patients (Klotzsch et al. 1998; Kwon et al. 2006; Marinoni et al. 1997; Wijnhoud et al. 2008). The temporal bone is thicker in women than in men, as reported in diverse studies (Jarquin-Valdivia et al. 2004; Kwon et al. 2006). Such studies have indicated that cranial thickness is related to the presence or absence of a TAW, with the sound waves being spread by the spongy bone diploe (Fry and Barger 1978). Hyperostosis is the greatest known obstacle to the success of transtemporal sonography of cerebral arteries.
For the patients in the present study, acquisitions of TAW transcranial Doppler images decreased as age increased. Diverse studies report that the radiodensity of the temporal bone is related to age, principally in women (Wijnhoud et al. 2008). TAW absence is probably caused by a loss of cranial bone density during the aging process, which may influence the acoustic dispersion of the sound wave by the cranium, while sound attenuation coefficients can be modified in osteoporotic bones and lead to an inadequate Doppler signal (Fry and Barger 1978; Kwon et al. 2006; McKelvie and Palmer 1991; White et al. 1978). This finding is relevant to clinical practice given that the Brazilian nos inhibitor is undergoing a demographic transition characterized by an increase in the number of elderly individuals (Brazilian Ministry of Health 2006).
The incidence of TAW presence was lower among those of African or Asian descent compared with white individuals. Brazil is a multi-ethnic country whose racial and ethnic characteristics have been determined by the immigration of diverse peoples. Initially, the territory now known as Brazil was inhabited by indigenous tribes; it was colonized in the 16th and 17th centuries by the Portuguese. African, Spanish, Dutch and French immigration, and in the last century Japanese and Chinese immigration, has determined the flexible and heterogeneous racial and ethnic character of the Brazilian population (Amorim et al. 2011; Lesser 2014). Knowledge of the ethnic and racial variability of the Brazilian population has considerable influence on imaging examinations, because each race may manifest different features in TCD examinations. Population studies comparing loss of bone mass report that such loss is lower among those of African or Asian descent, populations with a lower prevalence of osteopenia compared with whites (Vásquez et al. 2013). This information may be important, as it can account for the smaller number of TAWs detected in the former population based on bone density of the larger temporal bone in Africans and Asians.
The principal limitation of this study is related to the operator-dependent nature of the performance and interpretation of the examination. Some patients were in an intensive therapy unit with psychomotor agitation or delirium (<5% of the total sample), which hampered the TCD examination, but inter-observer variability was good in this study. Another limitation involves the epidemiologic factor in this sample; this factor was not studied in indigenous individuals, but this group represents only 0.2% of the Brazilian population (Montenegro and Stephens 2006), and even though this is a hospital-based study, the sample is sufficiently representative of the whole Brazilian population in terms of racial and ethnic composition. The absence of a TAW is one of the greatest obstacles to clinical use of TCD (Kwon et al. 2006). This is the first Brazilian work to evaluate the presence of TAW with TCD and correlate its presence with demographic characteristics of the population. Studies evaluating TAW presence in the Brazilian population or in the rest of Latin America are lacking. Because of the multi-ethnic nature of this geographic region, elucidation of the characteristics of these different ethnic groups might aid in the selection of patients for triage and diagnosis and perhaps facilitate the use of diverse therapies such as cerebral reperfusion therapy directed by TCD in stroke patients.

br Conflicts of interest br Acknowledgments The authors acknowledge the

Conflicts of interest

Acknowledgments
The authors acknowledge the financial support of Centro Universitário Metodista do IPA and CAPES. They also thank Balagué Center Laboratory for carrying out some analysis.

Introduction
Hyperlipidemia is a well-documented risk factor for cardiovascular disease (CVD), and is the major cause of death in men and women, especially in postmenopausal women. Increased risk of CVD in menopausal women has been associated with age-related muscle mass loss, changes in body composition, fat deposition, and functional capacity.
Previous studies demonstrated that there is a significant contribution of the regular practice of aerobic exercise in the prevention and control of CVD. However, little is known about the preventive action of strength training on the major risk factors for developing of CVD, such as hypertension, cholesterol levels, obesity, and type 2-diabetes.
Strength training has been recommended as a nonpharmacological strategy to decrease serum concentrations of total cholesterol (TC), triglycerides (TAG), and low-density lipoprotein (LDL), and raise high-density lipoprotein (HDL) concentration. In addition, strength training increases nos inhibitor sensitivity, decreases plasma TAG fasting, although, some authors have reported no changes in lipids and lipoproteins levels after a strength training program.
Methodological differences in previous findings may be due to differences in the duration of training, types of strength training (e.g., circuit-machines, free-weights, or elastic bands), intensity, and mostly total resistance exercise volume. The volume of training is a product of number sets performed for each exercise and total training volume plays a significant role in muscle volume (MV) and blood lipid profile changes.
However, the optimal number of sets (1 vs. 3) or low versus high volume of the exercises to develop MV remains controversial. The loss of MV leads to substantial decline in functional capacity, an increased risk of falls, fractures, and developing of chronic metabolic diseases followed by CVD.
Strength training has been shown to be an effective intervention for body composition, mainly decreasing body mass and body fat, and increasing muscle mass. However, the impact of resistance training on lipid profile remains unclear and requires further investigation. With respect to the lipid profile, the controversy among the studies is greater because few studies have investigated the effect of strength training in lipids and lipoproteins and the studies are contradictory.
Hormonal changes (i.e., decrease of estrogen) in postmenopausal women result in a loss of the cardioprotective effect of endogenous estradiol and their incidence of cardiovascular disease rises above that of men. We have not found other works that evaluate the effect of strength training on MV and concentration of lipoproteins in postmenopausal women. To the authors\’ knowledge no study has yet examined the effects of low volume strength training (LVST) versus high volume strength training (HVST) on lipoproteins in postmenopausal women and the relation of this with MV.

Materials and methods

Results
Participant characteristics are listed in Table 1. No significant differences existed between groups pre- and poststrength training for height, body mass, body composition, muscle mass, BMI, waist, thigh circumference, or waist–hip ratio for groups HVST, LVST, and CG.
Significant time effects were observed for strength 1RM (p < 0.001; Fig. 1A). Twelve weeks of strength training improved the absolute values of maximal dynamic strength and MV (Fig. 1B) for HVST and LVST (p < 0.001 and p = 0.048, respectively) compared with CG. Table 2 shows that there were no significant differences between groups in lipid profile (GLU, TC, HDL, and LDL) after strength training were observed among groups. However, TAG in post training was significantly different HVST in response to training for LVST and CG (p = 0.047; Fig. 1C).

In the future greater use may need to be made

In the future, greater use may need to be made of targeted programs whereby animals are treated with anthelmintic only after a significant level of egg shedding has been demonstrated (Kaplan et al., 2004). The use of this strategy will help protect the efficacy of existing anthelmintics. However, as demonstrated here the targeted strategy may not be as effective at slowing anthelmintic resistance if resistance is already developing and egg reappearance periods have significantly shortened. After treatment with abamectin and morantel, 70% of horses sampled 4weeks after treatment had egg counts in excess of the treatment threshold (150 EPG or more) for treatment and required retreatment (Scott et al., 2016). Future work is required to elucidate the efficacy of all nos inhibitor of anthelmintics being used in horses in New Zealand.

Conflict of interest

Acknowledgements
The authors would like to acknowledge Rob Moorhead for assistance with sample collection and yearling treatment, the stud veterinarians for their assistance with treatment and sample collections and the stud masters and their staff for help and participation. Thanks are also extended to New Zealand Veterinary Pathology (NZVP) for processing the samples. Funding for this work was received from the Equine Trust, as part of the Partnership for Excellence. Paper has been reviewed and approved for publication by all authors and the Royal Veterinary College Research committee, approval number PPH_01186.

Introduction
Coccidiosis is caused by Eimeria spp. and is responsible for high morbidity, high mortality and economic losses in commercial rabbit farms. Clinical signs of eimeriosis in rabbits are diarrhea, loss of appetite, weight loss, dehydration, secondary sepsis and death. However, it is common that rabbits present subclinical coccidiosis, characterized by reduced feed intake and higher feed conversion ratio (Coudert, 1976; Bhat et al., 1996; Pakandl, 2009).
Eleven species of Eimeria infect rabbits (Oryctolagus cuniculus): E. coecicola, E. flavescens, E. intestinalis, E. irresidua, E. exigua, E. magna, E. media, E. perforans, E. piriformis, E. stiedai and E. vejdovskyi (Kvičerová et al., 2008; Pakandl, 2009). Identification of the Eimeria species is commonly performed using morphological and morphometric analysis of oocysts, sporocysts and sporozoites (Ming-Hsien et al., 2010; El-Shahawi et al., 2012). However, microscopic diagnosis is time-consuming and the overlap of morphological and morphometric data between different species makes it difficult to accurately identify Eimeria species only by microscopy (Long and Joyner, 1984).
In view of the limitations of microscopic species-specific diagnosis, molecular techniques have been developed as a method for detection and species-specific identification of Eimeria spp. in rabbits (Oliveira et al., 2011; Yan et al., 2013).
The literature on epidemiological studies of molecular identification of Eimeria spp. of rabbits are scarce, particularly in Brazil. The aim of this study was to verify the occurrence and identify the species of Eimeria in faecal samples from Brazilian rabbit farms, and correlate the presence of the parasite with sex, age and reproductive stage of the rabbits.

Material and methods
Using a convenience sampling, 514 samples were collected in 2014 and 2015, in 21 rabbit (O. cuniculus) farms located in various municipalities of seven Brazilian states (Table 1), and classified according to age, sex and the reproductive stage, as follows: adult male, adult non-pregnant female, pregnant female, nursing female, 31–50days old and 51 to 80days old. Approximately 30g of feces were collected inside the cages, on the floor under the cages or on collection pans under the cages, stored in plastic vials containing potassium dichromate 5% and maintained for 48h in an open flask at room temperature to promote sporulation of Eimeria oocysts. The samples from 31 to 80days old rabbits consisted of pooled faecal samples from various animals housed in the same cage, while the samples from adult rabbits were individual.

br Our study demonstrated that the

Our study demonstrated that the average excursions of the bilateral nos inhibitor during tidal breathing (right: 11.0 mm, 95% CI 10.4 to 11.6 mm; left: 14.9 mm, 95% CI 14.2 to 15.5 mm) were numerically less than those during forced breathing in previous studies using other modalities 2; 7 ;  8. Using fluoroscopy, Alexander reported that the average right excursion was 27.5 mm and the average left excursion was 31.5 mm during forced breathing in the standing position in 127 patients (2). Using ultrasound, Harris et al. reported that the average right diaphragm excursion was 48 mm during forced breathing in the supine position in 53 healthy adults (7). Using MR fluoroscopy, Gierada et al. reported that the average right excursion was 44 mm and the average left excursion was 42 mm during forced breathing in the supine position in 10 healthy volunteers (8). The difference in diaphragmatic excursion during tidal breathing versus forced breathing is unsurprising.

Our study showed that the excursion and peak motion speed of the left diaphragm are significantly greater and faster than those of the right. With regard to the excursion, the results of our study are consistent with those of previous reports using fluoroscopy in a standing position 2 ;  3. However, in the previous studies evaluating diaphragmatic motion in the supine position, the asymmetric diaphragmatic motion was not mentioned 7 ;  8. The asymmetric excursion of the bilateral diaphragm may be more apparent in the standing position, but may not be detectable or may disappear in the supine position. Although we cannot explain the reason for the asymmetry in diaphragmatic motion, we speculate that the presence of the liver may limit the excursion of the right diaphragm. Regarding the motion speed, to the best of our knowledge this study is the first to evaluate it. The faster motion speed of the left diaphragm compared to that of the right diaphragm would be related to the greater excursion of the left diaphragm.

We found that higher BMI and higher tidal volume were independently associated with the increased excursions of the bilateral diaphragm by both univariate and multivariate analyses, although the strength of these associations was weak. We cannot explain the exact reason for the correlation between BMI and the excursion of the diaphragm. However, a previous study showed that BMI is associated with peak oxygen consumption (23), nos inhibitor and the increased oxygen consumption in an obese participant may affect diaphragmatic movement. Another possible reason is that lower thoracic compliance due to higher BMI may cause increased movement of the diaphragm for compensation. Regarding the correlation between tidal volume and excursion of the diaphragm, given that diaphragmatic muscle serves as the most important respiratory muscle, the result is to be expected. Considering our results, the excursion evaluated by dynamic X-ray phrenicography could potentially predict tidal volume.

Our study has several limitations. First, we included only 172 volunteers, and additional studies on larger participant populations are required to confirm these preliminary findings. Second, we evaluated only the motion of the highest point of the diaphragms for the sake of simplicity, and three-dimensional motion of the diaphragm could not be completely reflected in our results. However, we believe that this simple method would be practical and more easily applicable in a clinical setting.

Conclusions

The time-resolved quantitative analysis of the diaphragms with dynamic X-ray phrenicography is feasible. The average excursions of the diaphragms are 11.0 mm (right) and 14.9 mm (left) during tidal breathing in a standing position in our health screening center cohort. The diaphragmatic motion of the left is significantly larger and faster than that of the right. Higher tidal volume and BMI are associated with increased excursions of the bilateral diaphragm.