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In recent years the association between sexual dysfunction (SD) and obesity in the general population has drawn major attention. Although sexual dysfunction is common in psychosis, its relationship with weight gain and obesity remains unclear.
To investigate the association between sexual dysfunction and obesity in a cohort of patients with first episode psychosis.
Sexual function was assessed in a cohort of patients with first episode psychosis using the Sexual Function Questionnaire (SFQ). Anthropometric measures, including weight, BMI, waist, waist–hip ratio were investigated. Additionally, leptin and testosterone were investigated in male patients.
A total of 116 patients (61 males and 55 females) were included. Of these 59% of males and 67.3% of females showed sexual dysfunction (SD) according to the SFQ. In males, higher SFQ scores were significantly correlated with higher BMI (Std. β = 0.36, P = 0.01), higher leptin levels (Std. β = 0.34, P = 0.02), higher waist–hip ratio (Std. β = 0.32, P = 0.04) and lower testosterone levels (Std. β = −0.44, P = 0.002). In contrast, in females, SFQ scores were not associated with any of these factors.
While sexual dysfunction is present in both female and male patients with their first episode of psychosis, only in males is sexual dysfunction associated with increased BMI and waist–hip ratio. The association between SD, BMI, low levels of testosterone and high levels of leptin suggest that policies that lead to healthier diets and more active lifestyles can be beneficial at least, to male patients.
Recent years have seen great interest in the suggestion that between-group aggression and within-group altruism have coevolved. However, these efforts have neglected the possibility that warfare – via its impact on demography – might influence human social behaviours more widely, not just those directly connected to success in war. Moreover, the potential for sex differences in the demography of warfare to translate into sex differences in social behaviour more generally has remained unexplored. Here, we develop a kin-selection model of altruism performed by men and women for the benefit of their groupmates in a population experiencing intergroup conflict. We find that warfare can promote altruistic, helping behaviours as the additional reproductive opportunities winners obtain in defeated groups decrease harmful competition between kin. Furthermore, we find that sex can be a crucial modulator of altruism, with there being a tendency for the sex that competes more intensely with relatives to behave more altruistically and for the sex that competes more intensely with non-relatives in defeated groups to receive more altruism. In addition, there is also a tendency for the less-dispersing sex to both give and receive more altruism. We discuss implications for our understanding of observed sex differences in cooperation in human societies.
Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic disease transmitted from dromedary camels to people, which can result in outbreaks with human-to-human transmission. Because it is a subclinical infection in camels, epidemiological measures other than prevalence are challenging to assess. This study estimated the force of infection (FOI) of MERS-CoV in camel populations from age-stratified serological data. A cross-sectional study of MERS-CoV was conducted in Kenya from July 2016 to July 2017. Seroprevalence was stratified into four age groups: <1, 1–2, 2–3 and >3 years old. Age-independent and age-dependent linear and quadratic generalised linear models were used to estimate FOI in pastoral and ranching camel herds. Models were compared based on computed AIC values. Among pastoral herds, the age-dependent quadratic FOI was the best fit model, while the age-independent FOI was the best fit for the ranching herd data. FOI provides an indirect estimate of infection risk, which is especially valuable where direct estimates of incidence and other measures of infection are challenging to obtain. The FOIs estimated in this study provide important insight about MERS-CoV dynamics in the reservoir species, and contribute to our understanding of the zoonotic risks of this important public health threat.
The Meat Standards Australia (MSA) grading scheme has the ability to predict beef eating quality for each ‘cut×cooking method combination’ from animal and carcass traits such as sex, age, breed, marbling, hot carcass weight and fatness, ageing time, etc. Following MSA testing protocols, a total of 22 different muscles, cooked by four different cooking methods and to three different degrees of doneness, were tasted by over 19 000 consumers from Northern Ireland, Poland, Ireland, France and Australia. Consumers scored the sensory characteristics (tenderness, flavor liking, juiciness and overall liking) and then allocated samples to one of four quality grades: unsatisfactory, good-every-day, better-than-every-day and premium. We observed that 26% of the beef was unsatisfactory. As previously reported, 68% of samples were allocated to the correct quality grades using the MSA grading scheme. Furthermore, only 7% of the beef unsatisfactory to consumers was misclassified as acceptable. Overall, we concluded that an MSA-like grading scheme could be used to predict beef eating quality and hence underpin commercial brands or labels in a number of European countries, and possibly the whole of Europe. In addition, such an eating quality guarantee system may allow the implementation of an MSA genetic index to improve eating quality through genetics as well as through management. Finally, such an eating quality guarantee system is likely to generate economic benefits to be shared along the beef supply chain from farmers to retailors, as consumers are willing to pay more for a better quality product.
Accurately quantifying a consumer’s willingness to pay (WTP) for beef of different eating qualities is intrinsically linked to the development of eating-quality-based meat grading systems, and therefore the delivery of consistent, quality beef to the consumer. Following Australian MSA (Meat Standards Australia) testing protocols, over 19 000 consumers from Northern Ireland, Poland, Ireland, France and Australia were asked to detail their willingness to pay for beef from one of four categories that best described the sample; unsatisfactory, good-every-day, better-than-every-day or premium quality. These figures were subsequently converted to a proportion relative to the good-every-day category (P-WTP) to allow comparison between different currencies and time periods. Consumers also answered a short demographic questionnaire. Consumer P-WTP was found to be remarkably consistent between different demographic groups. After quality grade, by far the greatest influence on P-WTP was country of origin. This difference was unable to be explained by the other demographic factors examined in this study, such as occupation, gender, frequency of consumption and the importance of beef in the diet. Therefore, we can conclude that the P-WTP for beef is highly transferrable between different consumer groups, but not countries.
This study examined the response of forage crops to composted dairy waste (compost) applied at low rates and investigated effects on soil health. The evenness of spreading compost by commercial machinery was also assessed. An experiment was established on a commercial dairy farm with target rates of compost up to 5 t ha−1 applied to a field containing millet [Echinochloa esculenta (A. Braun) H. Scholz] and Pasja leafy turnip (Brassica hybrid). A pot experiment was also conducted to monitor the response of a legume forage crop (vetch; Vicia sativa L.) on three soils with equivalent rates of compost up to 20 t ha−1 with and without ‘additive blends’ comprising gypsum, lime or other soil treatments. Few significant increases in forage biomass were observed with the application of low rates of compost in either the field or pot experiment. In the field experiment, compost had little impact on crop herbage mineral composition, soil chemical attributes or soil fungal and bacterial biomass. However, small but significant increases were observed in gravimetric water content resulting in up to 22.4 mm of additional plant available water calculated in the surface 0.45 m of soil, 2 years after compost was applied in the field at 6 t ha−1 dried (7.2 t ha−1 undried), compared with the nil control. In the pot experiment, where the soil was homogenized and compost incorporated into the soil prior to sowing, there were significant differences in mineral composition in herbage and in soil. A response in biomass yield to compost was only observed on the sandier and lower fertility soil type, and yields only exceeded that of the conventional fertilizer treatment where rates equivalent to 20 t ha−1 were applied. With few yield responses observed, the justification for applying low rates of compost to forage crops and pastures seems uncertain. Our collective experience from the field and the glasshouse suggests that farmers might increase the response to compost by: (i) increasing compost application rates; (ii) applying it prior to sowing a crop; (iii) incorporating the compost into the soil; (iv) applying only to responsive soil types; (v) growing only responsive crops; and (vi) reducing weed burdens in crops following application. Commercial machinery incorporating a centrifugal twin disc mechanism was shown to deliver double the quantity of compost in the area immediately behind the spreader compared with the edges of the spreading swathe. Spatial variability in the delivery of compost could be reduced but not eliminated by increased overlapping, but this might represent a potential 20% increase in spreading costs.
The beef industry must become more responsive to the changing market place and consumer demands. An essential part of this is quantifying a consumer’s perception of the eating quality of beef and their willingness to pay for that quality, across a broad range of demographics. Over 19 000 consumers from Northern Ireland, Poland, Ireland and France each tasted seven beef samples and scored them for tenderness, juiciness, flavour liking and overall liking. These scores were weighted and combined to create a fifth score, termed the Meat Quality 4 score (MQ4) (0.3×tenderness, 0.1×juiciness, 0.3×flavour liking and 0.3×overall liking). They also allocated the beef samples into one of four quality grades that best described the sample; unsatisfactory, good-every-day, better-than-every-day or premium. After the completion of the tasting panel, consumers were then asked to detail, in their own currency, their willingness to pay for these four categories which was subsequently converted to a proportion relative to the good-every-day category (P-WTP). Consumers also answered a short demographic questionnaire. The four sensory scores, the MQ4 score and the P-WTP were analysed separately, as dependant variables in linear mixed effects models. The answers from the demographic questionnaire were included in the model as fixed effects. Overall, there were only small differences in consumer scores and P-WTP between demographic groups. Consumers who preferred their beef cooked medium or well-done scored beef higher, except in Poland, where the opposite trend was found. This may be because Polish consumers were more likely to prefer their beef cooked well-done, but samples were cooked medium for this group. There was a small positive relationship with the importance of beef in the diet, increasing sensory scores by about 4% in Poland and Northern Ireland. Men also scored beef about 2% higher than women for most sensory scores in most countries. In most countries, consumers were willing to pay between 150 and 200% more for premium beef, and there was a 50% penalty in value for unsatisfactory beef. After quality grade, by far the greatest influence on P-WTP was country of origin. Consumer age also had a small negative relationship with P-WTP. The results indicate that a single quality score could reliably describe the eating quality experienced by all consumers. In addition, if reliable quality information is delivered to consumers they will pay more for better quality beef, which would add value to the beef industry and encourage improvements in quality.
Quantifying consumer responses to beef across a broad range of demographics, nationalities and cooking methods is vitally important for any system evaluating beef eating quality. On the basis of previous work, it was expected that consumer scores would be highly accurate in determining quality grades for beef, thereby providing evidence that such a technique could be used to form the basis of and eating quality grading system for beef. Following the Australian MSA (Meat Standards Australia) testing protocols, over 19 000 consumers from Northern Ireland, Poland, Ireland, France and Australia tasted cooked beef samples, then allocated them to a quality grade; unsatisfactory, good-every-day, better-than-every-day and premium. The consumers also scored beef samples for tenderness, juiciness, flavour-liking and overall-liking. The beef was sourced from all countries involved in the study and cooked by four different cooking methods and to three different degrees of doneness, with each experimental group in the study consisting of a single cooking doneness within a cooking method for each country. For each experimental group, and for the data set as a whole, a linear discriminant function was calculated, using the four sensory scores which were used to predict the quality grade. This process was repeated using two conglomerate scores which are derived from weighting and combining the consumer sensory scores for tenderness, juiciness, flavour-liking and overall-liking, the original meat quality 4 score (oMQ4) (0.4, 0.1, 0.2, 0.3) and current meat quality 4 score (cMQ4) (0.3, 0.1, 0.3, 0.3). From the results of these analyses, the optimal weightings of the sensory scores to generate an ‘ideal meat quality 4 score (MQ4)’ for each country were calculated, and the MQ4 values that reflected the boundaries between the four quality grades were determined. The oMQ4 weightings were far more accurate in categorising European meat samples than the cMQ4 weightings, highlighting that tenderness is more important than flavour to the consumer when determining quality. The accuracy of the discriminant analysis to predict the consumer scored quality grades was similar across all consumer groups, 68%, and similar to previously reported values. These results demonstrate that this technique, as used in the MSA system, could be used to predict consumer assessment of beef eating quality and therefore to underpin a commercial eating quality guarantee for all European consumers.
European conformation and fat grades are a major factor determining carcass value throughout Europe. The relationships between these scores and sensory scores were investigated. A total of 3786 French, Polish and Irish consumers evaluated steaks, grilled to a medium doneness, according to protocols of the ‘Meat Standards Australia’ system, from 18 muscles representing 455 local, commercial cattle from commercial abattoirs. A mixed linear effects model was used for the analysis. There was a negative relationship between juiciness and European conformation score. For the other sensory scores, a maximum of three muscles out of a possible 18 demonstrated negative effects of conformation score on sensory scores. There was a positive effect of European fat score on three individual muscles. However, this was accounted for by marbling score. Thus, while the European carcass classification system may indicate yield, it has no consistent relationship with sensory scores at a carcass level that is suitable for use in a commercial system. The industry should consider using an additional system related to eating quality to aid in the determination of the monetary value of carcasses, rewarding eating quality in addition to yield.
Delivering beef of consistent quality to the consumer is vital for consumer satisfaction and will help to ensure demand and therefore profitability within the beef industry. In Australia, this is being tackled with Meat Standards Australia (MSA), which uses carcass traits and processing factors to deliver an individual eating quality guarantee to the consumer for 135 different ‘cut by cooking methods’ from each carcass. The carcass traits used in the MSA model, such as ossification score, carcass weight and marbling explain the majority of the differences between breeds and sexes. Therefore, it was expected that the model would predict with eating quality of bulls and dairy breeds with good accuracy. In total, 8128 muscle samples from 482 carcasses from France, Poland, Ireland and Northern Ireland were MSA graded at slaughter then evaluated for tenderness, juiciness, flavour liking and overall liking by untrained consumers, according to MSA protocols. The scores were weighted (0.3, 0.1, 0.3, 0.3) and combined to form a global eating quality (meat quality (MQ4)) score. The carcasses were grouped into one of the three breed categories: beef breeds, dairy breeds and crosses. The difference between the actual and the MSA-predicted MQ4 scores were analysed using a linear mixed effects model including fixed effects for carcass hang method, cook type, muscle type, sex, country, breed category and postmortem ageing period, and random terms for animal identification, consumer country and kill group. Bulls had lower MQ4 scores than steers and females and were predicted less accurately by the MSA model. Beef breeds had lower eating quality scores than dairy breeds and crosses for five out of the 16 muscles tested. Beef breeds were also over predicted in comparison with the cross and dairy breeds for six out of the 16 muscles tested. Therefore, even after accounting for differences in carcass traits, bulls still differ in eating quality when compared with females and steers. Breed also influenced eating quality beyond differences in carcass traits. However, in this case, it was only for certain muscles. This should be taken into account when estimating the eating quality of meat. In addition, the coefficients used by the Australian MSA model for some muscles, marbling score and ultimate pH do not exactly reflect the influence of these factors on eating quality in this data set, and if this system was to be applied to Europe then the coefficients for these muscles and covariates would need further investigation.
Ossification score and animal age are both used as proxies for maturity-related collagen crosslinking and consequently decreases in beef tenderness. Ossification score is strongly influenced by the hormonal status of the animal and may therefore better reflect physiological maturity and consequently eating quality. As part of a broader cross-European study, local consumers scored 18 different muscle types cooked in three ways from 482 carcasses with ages ranging from 590 to 6135 days and ossification scores ranging from 110 to 590. The data were studied across three different maturity ranges; the complete range of maturities, a lesser range and a more mature range. The lesser maturity group consisted of carcasses having either an ossification score of 200 or less or an age of 987 days or less with the remainder in the greater maturity group. The three different maturity ranges were analysed separately with a linear mixed effects model. Across all the data, and for the greater maturity group, animal age had a greater magnitude of effect on eating quality than ossification score. This is likely due to a loss of sensitivity in mature carcasses where ossification approached and even reached the maximum value. In contrast, age had no relationship with eating quality for the lesser maturity group, leaving ossification score as the more appropriate measure. Therefore ossification score is more appropriate for most commercial beef carcasses, however it is inadequate for carcasses with greater maturity such as cull cows. Both measures may therefore be required in models to predict eating quality over populations with a wide range in maturity.
The aims of the study were to determine the prevalence of cardiometabolic risk factors and establish the proportion of people with psychosis meeting criteria for the metabolic syndrome (MetS). The study also aimed to identify the key lifestyle behaviours associated with increased risk of the MetS and to investigate whether the MetS is associated with illness severity and degree of functional impairment.
Baseline data were collected as part of a large randomized controlled trial (IMPaCT RCT). The study took place within community mental health teams in five Mental Health NHS Trusts in urban and rural locations across England. A total of 450 randomly selected out-patients, aged 18–65 years, with an established psychotic illness were recruited. We ascertained the prevalence rates of cardiometabolic risk factors, illness severity and functional impairment and calculated rates of the MetS, using International Diabetes Federation (IDF) and National Cholesterol Education Program Third Adult Treatment Panel criteria.
High rates of cardiometabolic risk factors were found. Nearly all women and most men had waist circumference exceeding the IDF threshold for central obesity. Half the sample was obese (body mass index ≥ 30 kg/m2) and a fifth met the criteria for type 2 diabetes mellitus. Females were more likely to be obese than males (61% v. 42%, p < 0.001). Of the 308 patients with complete laboratory measures, 57% (n = 175) met the IDF criteria for the MetS.
In the UK, the prevalence of cardiometabolic risk factors in individuals with psychotic illnesses is much higher than that observed in national general population studies as well as in most international studies of patients with psychosis.
The ability of the biochemical measurements, haem iron, intramuscular fat (IMF%), moisture content, and total, soluble and insoluble collagen contents, to predict untrained consumer sensory scores both across different muscles and within the same muscle from different carcasses were investigated. Sensory scores from 540 untrained French consumers (tenderness, flavour liking, juiciness and overall liking) were obtained for six muscles; outside (m. biceps femoris), topside (m. semimembranosus), striploin (m. longissimus thoracis), rump (m. gluteus medius), oyster blade (m. infraspinatus) and tenderloin (m. psoas major) from each of 18 French and 18 Australian cattle. The four sensory scores were weighted and combined into a single score termed MQ4, which was also analysed. All sensory scores were highly correlated with each other and with MQ4. This in part reflects the fact that MQ4 is derived from the consumer scores for tenderness, juiciness, flavour and overall liking and also reflects an interrelationship between the sensory scores themselves and in turn validates the use of the MQ4 term to reflect the scope of the consumer eating experience. When evaluated across the six different muscles, all biochemical measurements, except soluble collagen, had a significant effect on all of the sensory scores and MQ4. The average magnitude of impact of IMF%, haem iron, moisture content, total and insoluble collagen contents across the four different sensory scores are 34.9, 5.1, 7.2, 36.3 and 41.3, respectively. When evaluated within the same muscle, only IMF% and moisture content had a significant effect on overall liking (5.9 and 6.2, respectively) and flavour liking (6.1 and 6.4, respectively). These results indicate that in a commercial eating quality prediction model including muscle type, only IMF% or moisture content has the capacity to add any precision. However, all tested biochemical measurements, particularly IMF% and insoluble collagen contents, are strong predictors of eating quality when muscle type is not known. This demonstrates their potential usefulness in extrapolating the sensory data derived from these six muscles to other muscles with no sensory data, but with similar biochemical parameters, and therefore reducing the amount of future sensory testing required.
Exploring potential links between the internal physical processes of galaxies with respect to their external morphologies can reveal connections between past and present populations. One primary physical driver of galaxy evolution is star formation, which is directly detected from UV emission. Here, we summarize a study investigating the optical and UV morphologies of rest-frame UV-detected star-forming galaxies at intermediate redshifts (0.1<z<1.2) observed with the Hubble Space Telescope (HST) Solar Blind Channel (far-UV) and Wide Field PlanetaryCamera 2 (WFPC2; U-band) in the Great Observatories Origins Deep Survey fields.