Table listed the results of regression model categorized by

Table 4 listed the results of regression model categorized by PV. Potential predictors including DRE, age, serum PSA and “urgency” score were included in the model. For the smaller PV group, only DRE was an independent predictor in the regression model. For PV >25 mL group, DRE estimation, serum PSA, age, and urgency score were independent predictors for PV, and the standardized regression equation was: PV = 0.74 × (DRE estimation) + 0.10 × (age) + 0.12 × (serum PSA) + 0.079 × (urgency score) (adjusted R2 = 0.80). In the regression model for PV ≤ 25 mL group, DRE estimation was the only independent predictor (adjusted R2 = 0.45). Furthermore, the correlation coefficients with PV in DRE estimated size <20 mL, 20–30 mL, 30–40 mL, >40 mL was 0.041 (p = 0.69), 0.453, 0.397, and 0.588, respectively (all p < 0.001, table not shown).
Discussion
Generally, transrectal ultrasound for PV estimation is well established as the standard method because of precision and reproducibility, and European Association of Urology guidelines have suggested that prostanoid receptors TRUS is an option for BPH when considering minimally invasive or surgical interventions. Because of its relative invasiveness and costs, TRUS may not be available in most settings, and a more easy and precise method for PV estimation is required.
DRE is a simple method to estimate PV but with less accuracy. In the current study, we used stepwise multiple linear regression analysis to choose the covariates that contribute the most and to avoid collinearity between covariates in the model. The final model represents that age, serum PSA, and urgency score, along with DRE, can predict PV better than DRE alone (adjusted R2 = 0.72 vs. R2 = 0.65). The general practitioner may use the equation for better PV prediction than DRE alone.
Previous studies showed that DRE theoretically underestimates the true PV, and Bosch et al indicated that DRE is good only in the identification of a large prostate. In the current study, we confirmed that the accuracy of DRE to predict PV varied according to different volume ranges and the prediction model was better fit for the PV >25 mL group.
Urgency is one of the most annoying symptoms, and may have a negative influence on daily work or quality of life for men with BPH. A recent study stated that urgency score is positively correlated with PV. In our model, similarly, there is a significant correlation between urgency score and PV, and men with larger PV suffered more from urgency score, which negatively affects quality of life.
There is emerging evidence that patients with metabolic syndrome have an increasing rate of prostate growth, which might account for the increasing prevalence of LUTS. In the general linear model, the current study showed that none of the metabolic markers correlated with PV for men with bothersome LUTS, and larger samples with other statistical methods will be necessary to clarify the relationships between metabolic markers and prostanoid receptors PV.
There are several limitations to the study that must be considered when interpreting the results. First, the current study was a single-arm analysis without a comparison group; a prospective study with both arms is necessary to clarify the relationship between PV and independent predictors such as metabolic syndrome and markers. Second, DRE was performed by an experienced urologist and is not representative of all general practitioners or urologists in clinical settings. Finally, we selected TRUS measurement to represent actual PV. It is known that there are interobserver variations and controversies in PV estimation by TRUS. Terris and Stamey reported on the correlation between TRUS measurement and prostatic specimen weight, and indicated that the most accurate method varied according to different volume ranges.

Conclusion

Financial disclosures

Conflicts of interest

Sources of funding

Introduction
Acute urinary retention (AUR) commonly occurs in the elderly aged >70 years, and more than 10% of men in their 70s experience AUR within the next 5 years. It is a urologic emergency. Urethral catheterization or suprapubic cystostomy drainage is needed to treat parasites condition. The most common cause of AUR is benign prostate enlargement (BPE), and a large prostate will increase the risk. Transurethral resection of prostate (TURP) has long been the most commonly performed surgical procedure and also a gold standard for the management of BPE. Surgical complications of TURP are more for a prostate volume of >50 mL than for a smaller volume. In a recent study, BPE patients with AUR who underwent TURP have been found to be associated with a higher risk of complications than those without AUR.

prostanoid receptors Previous studies have used PENIA to measure

Previous studies have used PENIA to measure sCysC concentrations in a small number of healthy cats, reporting values that fell within the RI of this study (Poswiatowska-Kaszczyszyn, 2012; Ghys et al., 2014). However, in those studies, sCysC concentrations in some cats fell within the RI calculated in our study (46/46 cats with CKD, Poswiatowska-Kaszczyszyn, 2012; 7/10 cats, Ghys et al., 2014). It is possible that CysC is not a reliable marker for the early detection of kidney dysfunction in cats; our study is inconclusive on this point and the subject requires further investigation.
There are only two published studies reporting the evaluation of feline sCysC and GFR (Jepson et al., 2006; Poswiatowska-Kaszczyszyn, 2012). Serum CysC was no better correlated with GFR than sCr in cats with hyperthyroidism and no change in sCysC was observed when before-and-after treatment values were compared (Jepson et al., 2006). However, in healthy cats and cats with CKD, a remarkably better correlation with GFR was found for sCysC compared with sCr (Poswiatowska-Kaszczyszyn, 2012). Because GFR was not measured in our study, we cannot be certain that some of our study population did not have early kidney impairment. Further research on feline sCr and sCysC is needed to investigate potential correlations with GFR. If the potential use of sCysC as a marker of GFR in clinical practice is to be explored, its ability to detect early kidney dysfunction should be determined by following up apparently healthy cats long-term and also by studying cats with medical conditions that might affect CysC production. Human studies have demonstrated that sCysC results in underestimation of GFR in patients with hyperthyroidism (Schmitt and Bachmann, 2003), due to a stimulatory effect of thyroid prostanoid receptors on sCysC production (Kotajima et al., 2010).
The sCr concentration of seven cats in our study population exceeded the RI for sCr established by our laboratory (44.2–141.2 µmol/L). All cats with sCr > RI had a USG > 1.035. A previous study by our group reported that the RI from an external laboratory was not appropriate for broad interpretation of feline sCr (Paepe et al., 2013c), since it was calculated using sCr concentrations from cats aged from 6 months to 1 year; inappropriate RIs have also been reported by other laboratories (Ulleberg et al., 2011). Because the development of laboratory-specific RIs is recommended (Friedrichs et al., 2012), we also calculated an RI for sCr (64.5–161.8 µmol/L). It is valuable to compare our results with sCr concentrations measured using the same assay method. None of the cats in our study had an sCr concentration over the upper reference limit (177 µmol/L) of a previously published RI for feline sCr (Syme et al., 2006), measured using a modified Jaffe reaction.
Twenty-five cats in our study had USG < 1.035 and 2/25 had isosthenuric urine. However, none of those cats had sCr concentrations exceeding the upper RI calculated at our laboratory. It has been shown that USG shows daily variation (vanVonderen et al., 1997) and therefore, low USG does not necessarily reflect impaired kidney function (Paepe et al., 2013b). More than 2 years after inclusion in this study, the owners of 20 cats were contacted again. None of the cats had developed clinical signs of CKD and all cats that were re-evaluated had USG > 1.035 and sCr < 141.2 µmol/L. To the authors\' knowledge, there are no published studies reporting the evaluation of USG in a large healthy cat population. In a prospective study of healthy Ragdoll cats, 8/62 healthy control cats aged 2.7 ± 1.6 years had USG < 1.035 (Paepe et al., 2013a). It has been hypothesised that the normal range for feline USG is 1.001–1.065 (Finco, 1995) and even up to 1.080 (Stockham and Scott, 2008). Nevertheless, studies evaluating USG in a large healthy cat population of different ages and breeds are warranted. Additionally, our study determined that the RIs of sCysC, sCr and serum urea in a subset of 105 cats with USG ≥ 1.035 were minimally different from RIs for these parameters from the entire study population (n = 130). However, the upper reference limits for these parameters were higher in the 105-cat group, since all 25 cats with low USG had low sCr and low serum urea concentrations.

The role of endosomal pH in YM

The role of endosomal pH in YM entry to IPEC-J2 prostanoid receptors was evaluated by treatment of the cells with bafilomycin A. Treatment of the cells with bafilomycin A inhibited YM infectivity by about 40% when virus was applied from the basolateral surface, but not through the apical side, suggesting that the requirement for low endosomal pH for virus is different from each surface. The vacuolar type H+-ATPase was also shown to be required for RRV infection into polarized MDCK cells (Wolf et al., 2012).
Altogether, we have shown that, regardless the cell surface, YM rotavirus infection into polarized IPEC-J2 small intestinal cells depends on the presence of cholesterol and is independent of dynamin and endosome acidification by ammonium chloride. With respect to candidate molecules for the interaction between basolateral surface and rotaviruses are integrins, which have been shown to participate in their cell entry (Coulson et al., 1997; Guerrero et al., 2000a; Lopez and Arias, 2004) and are localized mostly in the basolateral membrane of polarized intestine cells, or recently described tight junction molecules (JAM A, occluding, and ZO-1) (Torres-Flores et al., 2015). There is broad evidence that several viruses use such “inaccessible” molecules, hidden in tight junctions, for their cell entry, including reovirus, adenovirus, coxsackievirus, echovirus, and hepatitis C virus among others (Coyne and Bergelson, 2005; Lenman et al., 2015; Ploss et al., 2009; Sobo et al., 2011; Torres-Flores and Arias, 2015).
The preference of some viruses to infect in vitro preferentially the basolateral cell surface, while in a natural infection they come in contact with the apical surface of epithelial cells, remains a puzzle. Such is a case of respiratory reovirus (Excoffon et al., 2008), vesicular stomatitis virus (Fuller et al., 1984), and hantavirus (Ravkov et al., 1997). In this work we found that rotavirus YM also enters polarized small intestinal IPEC-J2 cells preferentially from the basolateral surface. In the case of rotavirus, one potential explanation of how the virus can reach the basolateral surface from the intestinal lumen lies in the previous observation that the outer-capsid protein VP8 of rotavirus RRV has the ability to transiently open tight junctions, which would allow the redistribution of basolateral molecules (including rotavirus receptors) to the apical side of the cell (Nava et al., 2004). Also, a recent report suggested an important role of several tight junction proteins (JAM-A, occludin, and ZO-1) for the entry of some rotaviruses into non-polarized MA104 cells (Torres-Flores et al., 2015). The fact that YM was found not to interact with JAM-A in that work needs to be further evaluated in differentiated cell lines.
The exit of progeny viruses from infected cells is relevant for the infection of neighboring cells and viral spread in the organism. In most cases, viruses that are released from the apical surface of polarized epithelia cause a localized infection, while viruses that are released from the basolateral surface cause systemic infections. In this regard, it is interesting that YM is released mainly from the apical surface, independently from which surface the cells were infected. These findings are in agreement with those previously reported for RRV, which was shown to be released from polarized Caco-2 cells preferentially from the apical surface, while from a non-differentiated MA104 cell monolayer grown in transwell filters the release was equally efficient from both upper and lower sides (Jourdan et al., 1997). This apical release correlates with the intestinal infection of rotavirus, allowing for efficient virus dissemination via excretion. On the other hand, there is increasing evidence of rotavirus extra intestinal spread in humans and many animal species (Blutt and Conner, 2007; Blutt et al., 2007; Medici et al., 2011), however the mechanism of this systemic spread is not understood. Other viruses that preferentially exit polarized intestinal cells from the apical side include poliovirus (Tucker et al., 1993), measles, and parainfluenza 3 (Blau and Compans, 1995).

High correlations between tick initial

High correlations between tick initial weight and egg mass weight (Table 1) suggest that both traits were affected by similar host immunological factors, agreeing with results presented by Barriga et al. (1995). Nearly perfect association (0.97) between those traits in susceptible heifers indicates that egg mass produced by ticks of this group were almost entirely dependent on blood intake capacity during tick development on the cattle. Although also positive and high, the correlation of 0.80 observed between initial weight and egg mass weight for resistant heifers indicates that a small portion of the variation observed in oviposition weight was due to factors other than tick initial weight in this group. The lower correlation between tick initial weight and egg mass weight observed in the resistant group, as well as the negative association between initial weight and egg production index of ticks from resistant heifers, may be an indicative of occurrence of a defense mechanism that disturbs conversion of ingested blood to egg mass in animals of the resistant group.
In conclusion, genetic variability for tick resistance observed in Braford heifers affected both the number of ticks carried by the animals as well as egg mass weight, egg production index and nutrient index of engorged females of R. (B.) microplus. Thus, in addition to economic losses related to prostanoid receptors of cattle productivity or to higher demand for treatments, maintaining animals with high tick susceptibility in the herd implies higher environmental infestation levels, perpetuating high prevalence of ticks on farm. Genetic evaluation of livestock for tick resistance and inclusion of tick counts as selection criteria in breeding programs can be implemented as an auxiliary tool for the strategic control of R. (B.) microplus in production systems. Finally, is important to note that further studies to uncover genetic factors responsible for immunological mechanisms involved in the expression of resistant phenotypes could enable genetic evaluations for tick resistance based on genomic information (e.g., molecular markers); thereby, increasing prediction accuracy, accelerate identification of superior genotypes, and avoid cattle exposure to ticks required by current genetic evaluation methods.

Acknowledgments
Research supported by CNPq – National Council for Scientific and Technological Development grant 478992/2012-2, Embrapa – Brazilian Agricultural Research Corporation grants 02.09.07.004 and 01.11.07.002, and CAPES – Coordination for the Improvement of Higher Level Personnel grant PNPD 02645/09-2. Authors acknowledge the Delta G Connection for providing animals and data for this research and Dr. Concepta M. Pimentel for reviewing the manuscript and providing a constructive contribution to its final version.

, an important protozoan belonging to the Apicomplexa family, causes the fatal disease East Coast fever in cattle, restricted to the East Coast and the central part of Southern Africa. This disease, together with tropical theileriosis (), causes major economic losses to the farming community in developing countries.

It can also be noticed that PP impurity in the

It can also be noticed that PP impurity in the HIPS has to be avoided, since this kind of impurity behaves as a filler and strongly decreases on the impact strength of the matrix. However, since HIPS and PP have quite different NIR spectra and densities, a sorting better than 1 wt% of PP could be possible regarding the sorting scheme.
Food waste; Restaurant; Qualitative; Food service sector; Element; Framework
1. Introduction
One third of the environmental impact of Finnish consumption is related to food (Seppälä et al., 2011). Avoidable food waste is produced at all stages of the food chain with significant ecological and economic impacts (Williams et al., 2015). It has been estimated (Katajajuuri et al., 2014) that the total climate impact of food waste in Finland, including households, retailers, restaurants and the food industry, is approximately 1000 million kilograms of CO2-equivalent per year. This is more than one percent of the Finnish total annual greenhouse gas emissions. Further, the value of food discarded by Finnish households is estimated to be €400-550 million annually. It is ecologically, socially and economically unsustainable to waste edible food rather than consume it, because in addition to wasted money the environmental impacts of producing the raw materials and processing them into food are considerable.
Comprehensive, detailed and reliable studies, especially for the entire food chain, are yet very few. Furthermore, concern has been growing for the environment and food sufficiency, making food waste an important research topic and fuelling social debate (Koivupuro et al., 2010). Also, the issue of responsibility is considered to play a significant role in the minds of prostanoid receptors and regarding business strategies among companies in the food production chain (Lindgreen et al., 2009; Beer, 2009).
The food service sector is a notable part of the food chain because in Finland, around 889 million food portions are cooked in food service businesses every year (Taloustutkimus, 2011), which corresponds to around 395 million kilos of food. This figure is exceeded because some food is already wasted at the storing and cooking stages. Minimizing food waste improves resource efficiency and sustainability in the food service sector. Workplace restaurants and canteens serve 14% of all food in the Finnish food service sector. One-third of the population uses public food services on a daily basis.
The volumes of food waste in the food service sector have been studied over the last fifteen years in Europe and the United States (Silvennoinen et al., 2015, Wrap, 2011, Schneider and Obersteiner, 2007, Karlsson, 2001, Marthinsen and Bjorn, 2004, Adams et al., 2005, Jones, 2005 and RVF Utveckling, 2006). For example, it is estimated that in 2009 UK hotels, pubs, restaurants and QSRs (e.g. quick service restaurants) produced just over 3.4 million tonnes of waste (Wrap, 2011). According to the United States Department of Agriculture (USDA) households and food service operations (restaurants, cafeterias, fast food, and caterers) together lost 39 billion kilograms (86 billion pounds) of food in 2008 (Gunders, 2012). In Finland about 20% of all food produced and served in licensed restaurants is discarded (Silvennoinen et al., 2015), which roughly corresponds to 79 million kilograms. The estimation is based on the Foodspill project where the kitchen staff weighed edible food waste in 72 restaurant outlets (Silvennoinen et al., 2015). An American study (Jones, 2005) reveals that (in fast food restaurants) the amount of food waste varies significantly from 5 to 50% of all food prepared, depending on the business concept. A questionnaire study conducted by Agrifood Research Finland (MTT) revealed that food waste is monitored during the preparation and service phases in communal food services (Risku-Norja et al., 2010). The amount of food waste was estimated to vary from a few per cent up to 20% of all food produced, depending on the food offered. The majority of the respondents estimated the loss to be slightly larger than for the food service at the manufacturing stage.