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In the latter half of the twentieth century, particularly in developed countries, a growing awareness of the environmental impact of personal choices—encompassing climate, pollution, land degradation, and biodiversity loss—resulted in an upsurge of environmental labels on goods. Environmental labels play a crucial role in assisting consumers in selecting environmentally superior products, fostering market development towards eco-friendly production systems, and serving as a foundation for product differentiation and increased product value. Despite a growing public interest in environmental quality and climate change, surveys reveal a gap between consumers’ environmental attitudes and actual purchasing behaviour. In addition, concerns about the complexity and cost of certification systems have arisen, with fears of creating market barriers for small producers. This review aims to provide an overview of environmental labelling in the context of animal food products, emphasising social and regulatory aspects, exploring technical considerations of life cycle thinking approaches in certification schemes, and discussing the pros and cons of standardising procedures for the development of multi-dimensional environmental labelling in the animal food sector.

Abstract Background Mucinous adenocarcinoma of the prostate (MACP) is one of the rarest variants of prostatic neoplasm, with more aggressive behavior than non-mucinous prostatic cancer. Previous studies suggested that these tumors exhibit different imaging magnetic resonance imaging (MRI) features compared with those of non-mucinous adenocarcinoma of the prostate upon which the conventional PIRADS v2.1 is based. To the best of our knowledge, this case series is the first to describe the multiparametric magnetic resonance imaging features of the MACP. Results We presented two cases of biopsy proven mucinous adenocarcinoma of the prostate studied with multiparametric MRI. In both cases, diagnosis was late because of the different MRI features of MACP than those of the more common adenocarcinoma of the prostate. In both mpMRI, MACP appears to be hyperintense on T2WI, there was not a significant decrease in diffusivity in ADC maps and it exhibits early enhancement in DCE-MRI; the septa resulted in hypointense on T2WI compared to the PZ Conclusions According to our experience, the conventional PIRADS v2.1 score is not suitable for mucinous prostate adenocarcinoma. MACP appears to be hyperintense on T2WI, has a lower ADC value, and exhibits early enhancement in DCE-MRI; the septa are usually hypointense on T2WI compared to the PZ. It is imperative for radiologists and urologists to be cognizant of this rare variant of prostate cancer to promptly identify and diagnose it, thereby preventing any diagnostic delays.

The dairy industry’s contribution to global warming has been thoroughly examined. However, it is important to raise public awareness of emission hotspots and the possibility of mitigation in dairy supply chains. This study assessed the Carbon Footprint (CF) of five dairy products through a cradle-to-grave Life Cycle Assessment approach and evaluated the carbon sink potential of some practices. The functional units were 1 kg of fresh raw milk, yogurt, fresh cheese, mozzarella cheese, and aged cheese. The data collected were related to an extensive dairy farm, a cheese-factory, two markets, a delivery service, and a court of consumers. The CFs were 4.39, 5.10, 9.82, 8.40, and 15.34 kg CO2 eq. for fresh raw milk, yogurt, mozzarella cheese, fresh cheese, and aged cheese, respectively. The hotspots of the dairy supply chain considered herein refer to farm activities and energy consumption, whereas conservative agriculture practices and rotational grazing sequestered 1.60 ± 0.80 kg CO2 eq. per kg of dairy product consumed. The CF was reduced by 0.14 kg CO2 eq. for 1 kg of dairy product delivered at home compared to direct purchasing at a market. The carbon sink capacity of dairy farms appeared as a primary mean for mitigating climate change in the dairy supply chain.

BackgroundPatients with central core myopathy (CCM) can be at risk of exercise-induced rhabdomyolysis and myalgia. Despite its possible positive effects, physical training has been long avoided in these patients as no population-specific exercise adaption strategies have been developed. Here we present the case of a 17-year-old male CCM patient who underwent a 3-month training program tailored to a preliminary test aimed at assessing his physical exertion tolerance measured via changes in serum creatine kinase (CK).MethodsThe preliminary tolerance test consisted of three 25-minute sessions (one session per week) of physical exercise (aerobic, resistance and mixed) at an intensity quantified as level 6 of the Borg Category Ratio (CR) 0–10 scale. A blood sample to assess CK was conducted 36 h following eachsession. The intervention consisted of a training program (three sessions per week) including both resistance and aerobic exercises concomitant with a personalized nutritional plan. Before and after intervention, a battery of metabolic (indirect calorimetry, bioimpedance) and cardiopulmonary (CPET) tests were performed.ResultsAfter training, improvements of the anaerobic threshold (+6.9%), normalized VO2 max (+15%) and body composition (muscle mass, +1.1 kg; fat mass, −1.1 kg were observed without pain, rhabdomyolysis, and blood CK augmentation compared to pretraining values.ConclusionOur results highlight that a mixed aerobic/resistance training, properly tailored and supported by a specific nutritional plan, may safely improve the physical fitness and body composition in a CCM patient. Dosing exercise-induced CK serum change following Borg CR-10 intensity assessment, may be useful to correctly tailor physical exercise in these patients.

This study presents a comprehensive assessment of the Water Footprint (WF) for buffalo mozzarella production and consumption relative to an area in central Italy with a high concentration of buffalo farms. Using the Water Footprint Network (WFN) methodology, the consumption of green, blue, and grey water fractions (Wfc) throughout the supply chain has been examined.The study encompassed nine buffalo dairy farms, two cheese factories, four retail outlets, and a cohort of 243 consumers, providing a comprehensive overview of the entire process from raw milk production and mozzarella cheese making to the final stage of home consumption. The results of the study were expressed as litres of water per kg of consumed buffalo mozzarella cheese. The total WF was 6820 ± 1490 L per kg of mozzarella, with green, blue, and grey Wfc contributing for 59%, 12%, and 29%, respectively. The green Wfc was predominantly influenced (88%) by off-farm feed. The blue Wfc was also primarily affected by off-farm feed (61%), followed by on-farm crop irrigation, buffalos’ drinking water and cheese factory operations. Home consumption had a negligible impact on the overall WF. The grey Wfc brought to light environmental concerns, primarily due to nitrate leaching. Although off-farm crops had a remarkable effect on the grey Wfc, the cultivation of on-farm crops was responsible for 69% of this fraction. In particular, a significant part of the grey Wfc originated from on-farm areas left fallow for parts of the year, leading to no uptake of residual nitrogen by crops.Adhering to WFN guidelines, this research not only expands knowledge on the WF of buffalo mozzarella, but also highlights critical water hotspots. It underscores the necessity for dairy farmers to refine irrigation and soil management, incorporating precise irrigation and crop rotation strategies, to mitigate the impacts on Wfc efficiently.

Heat stress impacts ruminant livestock production on varied levels in this alarming climate breakdown scenario. The drastic effects of the global climate change-associated heat stress in ruminant livestock demands constructive evaluation of animal performance bordering on effective monitoring systems. In this climate-smart digital age, adoption of advanced and developing Artificial Intelligence (AI) technologies is gaining traction for efficient heat stress management. AI has widely penetrated the climate sensitive ruminant livestock sector due to its promising and plausible scope in assessing production risks and the climate resilience of ruminant livestock. Significant improvement has been achieved alongside the adoption of novel AI algorithms to evaluate the performance of ruminant livestock. These AI-powered tools have the robustness and competence to expand the evaluation of animal performance and help in minimising the production losses associated with heat stress in ruminant livestock. Advanced heat stress management through automated monitoring of heat stress in ruminant livestock based on behaviour, physiology and animal health responses have been widely accepted due to the evolution of technologies like machine learning (ML), neural networks and deep learning (DL). The AI-enabled tools involving automated data collection, pre-processing, data wrangling, development of appropriate algorithms, and deployment of models assist the livestock producers in decision-making based on real-time monitoring and act as early-stage warning systems to forecast disease dynamics based on prediction models. Due to the convincing performance, precision, and accuracy of AI models, the climate-smart livestock production imbibes AI technologies for scaled use in the successful reducing of heat stress in ruminant livestock, thereby ensuring sustainable livestock production and safeguarding the global economy.

The shortage of organs for transplantations is increasing in Europe as well as globally. Many initiatives to the organ shortage, such as opt-out systems for deceased donation and expanding living donation, have been insufficient to meet the rising demand for organs. In recurrent discussions on how to reduce organ shortage, financial incentives and removal of disincentives, have been proposed to stimulate living organ donation and increase the pool of available donor organs. It is important to understand not only the ethical acceptability of (dis)incentives for organ donation, but also its societal acceptance. In this review, we propose a research agenda to help guide future empirical studies on public preferences in Europe towards the removal of disincentives and introduction of incentives for organ donation. We first present a systematic literature review on public opinions concerning (financial) (dis)incentives for organ donation in European countries. Next, we describe the results of a randomized survey experiment conducted in the United States. This experiment is crucial because it suggests that societal support for incentivizing organ donation depends on the specific features and institutional design of the proposed incentive scheme. We conclude by proposing this experiment’s framework as a blueprint for European research on this topic.

Research shows that women are less likely to enter competitions than men. This disparity may translate into a gender imbalance in holding leadership positions or ascending in organizations. We provide both laboratory and field experimental evidence that this difference can be attenuated with a default nudge-changing the choice to enter a competitive task from a default in which applicants must actively choose to compete to a default in which applicants are automatically enrolled in competition but can choose to opt out. Changing the default affects the perception of prevailing social norms about gender and competition as well as perceptions of the performance or ability threshold at which to apply. We do not find associated negative effects for performance or wellbeing. These results suggest that organizations could make use of opt-out promotion schemes to reduce the gender gap in competition and support the ascension of women to leadership positions.

Public opinion about environmental aspects is generating a widespread concern, which contributes to lead consumers to choose sustainable products. Livestock systems are responsible for the emissions of different pollutants and, as a consequence, this is reflected in the environmental sustainability of animal-based products.This study was aimed at evaluating the environmental impacts of buffalo mozzarella cheese with a cradle-to-grave life cycle assessment approach from the primary production of milk to the end-of-life of buffalo mozzarella cheese. The functional units were 1 kg of buffalo Fat and Protein Corrected Milk (FPCM) evaluated at farm gate and 1 kg of consumed buffalo mozzarella cheese evaluated at consumers’ home.The study enrolled 9 buffalo dairy farms, 2 dairy plants and 4 markets where 243 customers were surveyed. Processes of raw milk production, mozzarella cheese making, transports, retail and home consumption were considered. The accounted environmental impacts were: climate change (CC), terrestrial acidification (TA), freshwater eutrophication (FE), marine eutrophication (ME), ozone depletion (OD), ecotoxicity (EC), human toxicity (HT), land use (LU) and fossil depletion (FD). Buffalo farming was the primary hotspot accounting for more than 50% throughout all impact categories and having a major role in CC, TA, FE, ME, OD and LU. The energy consumption of cheese making had a contribution of 29% in HT, whereas the use of high-emitting vehicles by consumers accounted for 23% and 17% in EC and FD, respectively. To reduce several sources of pollution and mitigate the environmental impacts of buffalo mozzarella cheese, the LCA hotspots identification can lead to the development of specific mitigating strategies to improve sustainability along the supply chain. The development of farm-based models may better assess environmental impacts, the mitigation achieved by the implemented best practices and the “pollution swapping” effect to evaluate the effectiveness of the mitigation strategy.

Abstract Background Pneumococcal disease is a leading cause of communicable disease morbidity and mortality globally. We aimed to estimate invasive pneumococcal disease (IPD), pneumococcal pneumonia (PP) and all-cause pneumonia (ACP) incidence rates (IRs) in children aged 0–17 years in England from 2003 to 2019. Methods A retrospective study in children ≤17 years old from 2003 to 2019 using the Clinical Practice Research Datalink (CPRD) Gold and Hospital Episodes Statistics Admitted Patient Care (HES APC) databases. IPD episodes were identified in hospital records (HES APC). PP (caused by Streptococcus pneumoniae only) and ACP episodes (caused by any pathogen) were identified in primary care (CPRD) and in hospital records (HES APC). Annual IRs by age-group were calculated as the number of episodes/person-years (PY) at risk, with 95% confidence intervals (95% CI). Interrupted time series analyses were conducted to assess changes in IRs across the post-PCV7 (2007–2009), early post-PCV13 (2011–2014) and late post-PCV13 (2015–2019) periods compared to the pre-PCV7 period (2003–2005) using generalized linear models. Results 170 IPD episodes, 769 PP episodes and 12,142 ACP episodes were identified in 1,500,686 children in 2003–2019. The overall IPD, PP and ACP IRs (per 100,000 PY) were 2.29 (95% CI 1.96–2.66), 10.34 (95% CI 9.62–11.10) and 163.37 (95% CI 160.47–166.30), respectively. The highest IPD, PP and ACP IRs were observed in children aged

Abstract The COVID-19 pandemic and its social restrictions have affected mental health globally. This systematic review aims to analyze the psychological responses of the general population and its related sociodemographic risk factors, excluding the most vulnerable groups (e.g., healthcare workers, COVID-19 patients and survivors, pregnant women, people with chronic diseases or preexisting psychiatric disorders). A reproducible search from June 2020 to February 2021 was conducted on PubMed and Google Scholar, following the PRISMA guidelines. Papers that (1) considered the most at-risk populations, (2) did not report sociodemographic data, and (3) did not use validated scales were excluded from our analysis. Non-English papers and review articles were also excluded. Of 1116 papers identified, 25 were included for this review (n = 162,465). The main risk factors associated with the emergence of depression, anxiety, sleep disorders, post-traumatic stress disorder, and obsessive compulsive disorder were: female gender, younger and later age, high level of education, Latino origin, free marital status, living quarantine in a house with no outdoor, negative coping strategies, close proximity to positive cases, high concern about contracting COVID-19 and living in a most affected area. High income, physical activity, resilience, family support, and a high level of knowledge about COVID-19, seems to be protective factors against the onset of psychological symptoms. In a general population, COVID-19 restrictions are linked to risk factors for psychological disorders caused by gender and sociodemographic conditions. In this regard governments should pay more attention to the public’s mental health and its risk and protective factors.

AA amyloidosis may complicate several chronic inflammatory conditions. From a clinical point of view, causality between inflammatory pathology and AA amyloidosis can be assumed because of the data described in the literature; some of the best known include rheumatoid arthritis, ankylosing spondylitis, inflammatory bowel disease, and chronic infections. Singles cases of inflammatory diseases have been found at AA amyloidosis. Causality becomes more plausible if at least two different cases with AA amyloidosis are both found to have the same rare inflammatory disease. We describe the case of a patient with primary sclerosing cholangitis (PSC) with development of AA amyloidosis conditioning a nephrotic syndrome, likely secondary to failure to control the chronic inflammatory process. Only two cases in the literature describe the association of this rare disease and the appearance of AA amyloidosis. The treatment of AA amyloidosis consists in treating the underlying inflammatory disorder; to date, few effective treatments are available for PSC. Therefore, and in view of the limited data in the literature, we believe it is important to describe its association.

Heat stress impacts ruminant livestock production on varied levels in this alarming climate breakdown scenario. The drastic effects of the global climate change-associated heat stress in ruminant livestock demands constructive evaluation of animal performance bordering on effective monitoring systems. In this climate-smart digital age, adoption of advanced and developing Artificial Intelligence (AI) technologies is gaining traction for efficient heat stress management. AI has widely penetrated the climate sensitive ruminant livestock sector due to its promising and plausible scope in assessing production risks and the climate resilience of ruminant livestock. Significant improvement has been achieved alongside the adoption of novel AI algorithms to evaluate the performance of ruminant livestock. These AI-powered tools have the robustness and competence to expand the evaluation of animal performance and help in minimising the production losses associated with heat stress in ruminant livestock. Advanced heat stress management through automated monitoring of heat stress in ruminant livestock based on behaviour, physiology and animal health responses have been widely accepted due to the evolution of technologies like machine learning (ML), neural networks and deep learning (DL). The AI-enabled tools involving automated data collection, pre-processing, data wrangling, development of appropriate algorithms, and deployment of models assist the livestock producers in decision-making based on real-time monitoring and act as early-stage warning systems to forecast disease dynamics based on prediction models. Due to the convincing performance, precision, and accuracy of AI models, the climate-smart livestock production imbibes AI technologies for scaled use in the successful reducing of heat stress in ruminant livestock, thereby ensuring sustainable livestock production and safeguarding the global economy. [ABSTRACT FROM AUTHOR]

Background: Patients with central core myopathy (CCM) can be at risk of exercise-induced rhabdomyolysis and myalgia. Despite its possible positive effects, physical training has been long avoided in these patients as no population-specific exercise adaption strategies have been developed. Here we present the case of a 17-year-old male CCM patient who underwent a 3- month training program tailored to a preliminary test aimed at assessing his physical exertion tolerance measured via changes in serum creatine kinase (CK). Methods: The preliminary tolerance test consisted of three 25-minute sessions (one session per week) of physical exercise (aerobic, resistance and mixed) at an intensity quantified as level 6 of the Borg Category Ratio (CR) 0--10 scale. A blood sample to assess CK was conducted 36 h following eachsession. The intervention consisted of a training program (three sessions per week) including both resistance and aerobic exercises concomitant with a personalized nutritional plan. Before and after intervention, a battery of metabolic (indirect calorimetry, bioimpedance) and cardiopulmonary (CPET) tests were performed. Results: After training, improvements of the anaerobic threshold (+6.9%), normalized VO2 max (+15%) and body composition (muscle mass, +1.1 kg; fat mass, -1.1 kg were observed without pain, rhabdomyolysis, and blood CK augmentation compared to pretraining values. Conclusion: Our results highlight that a mixed aerobic/resistance training, properly tailored and supported by a specific nutritional plan, may safely improve the physical fitness and body composition in a CCM patient. Dosing exercise-induced CK serum change following Borg CR-10 intensity assessment, may be useful to correctly tailor physical exercise in these patients. [ABSTRACT FROM AUTHOR]

It is challenging to collect robust, long-term datasets to properly monitor the viability and social structure of large, long-lived animals, especially marine mammals. The present study used a unique long-term dataset to investigate the population parameters and social structure of a poorly studied population of bottlenose dolphins (Tursiops sp.) in southern Port Phillip Bay, south-eastern Australia. Photo-identification images have been collected between 2012-2022 both opportunistically and following a protocol by patrons, staff, and volunteers of ecotourism companies using their vessels as platforms. The resulting large dataset was available to be processed through the online platform Flukebook and used in capture recapture models to estimate abundance and demographic parameters. In addition, the social structure of the population and the reproductive parameters were investigated. The marked adult population abundance (45.2 ± 2.7 individuals) was found to be stable over the last decade and the calving rate ranged between 0.06-0.19 new calves per identified individuals per year, while the inter-birth interval was 3.7 ± 0.8 years. Social analysis suggested the population has a fission-fusion structure with no apparent clusters. The stability of the population over the study period suggests no deleterious effect of anthropogenic or environmental factors during the last decade. This study is the outcome of the effort of the ecotourism organisations and the results obtained, along with their similarity to those of other dolphin populations worldwide, highlight the importance of such data sources for long-term information that would otherwise be too expensive or logistically difficult to obtain.