A matter of age? How age affects the adaptation of lactating dairy cows to virtual fencing.

Virtual Fencing (VF) can be a helpful technology in managing herds in pasture-based systems. In VF systems, animals wear a VF collar using global positioning, and physical boundaries are replaced by virtual ones. The Nofence (Nofence AS, Batnfjordsøra, Norway) collars used in this study emit an acoustic warning when an animal approaches the virtual boundaries, followed by an aversive electrical pulse if the animal does not return to the defined area. The stimuli sequence is repeated up to three times if the animal continues to walk forward. Although it has been demonstrated that animals successfully learn to adapt to the system, it is unknown if this adaptation changes with animal age and thus has consequences for VF training and animal welfare. This study compared the ability of younger and older dairy cows to adapt to a VF system and whether age affected activity behavior, milk yield, and animal long-term stress under VF management. The study was conducted on four comparable strip-grazing paddocks. Twenty lactating Holstein-Friesian cows, divided into four groups of five animals each, were equipped with VF collars and pedometers. Groups differed in age: two groups of older cows (>4 lactations) and two groups of younger ones (first lactation). After a 7-d training, paddock sizes were increased by successively moving the virtual fence during four consecutive grazing periods. Throughout the study, the pedometers recorded daily step count, time spent standing, and time spent lying. For the determination of long-term stress, hair samples were collected on the first and last day of the trial and the hair cortisol content was assessed. Data were analyzed by generalized mixed-effect models. Overall, age had no significant impact on animal responses to VF, but there were interaction effects of time: the number of acoustic warnings in the last period was higher in younger cows (P < 0.001), and the duration of acoustic warnings at training was shorter for older cows (P < 0.01). Moreover, younger cows walked more per day during the training (P < 0.01). Finally, no effects on milk yield or hair cortisol content were detected. In conclusion, all cows, regardless of age, adapted rapidly to the VF system without compromising their welfare according to the indicators measured.

For dairy farmers, pasture management is a difficult task, including feeding the herd on demand, improving pasture use efficiency, and dealing with high labor costs. Virtual Fencing (VF) is an innovative technology that can help farmers to solve these issues. In a VF system animals wear a tracking collar. Physical boundaries are replaced by virtual ones using a smartphone application. The collars emit an acoustic warning when the animal reaches the virtual boundaries, further accompanied by an aversive electrical pulse if the animal does not return to the predefined area. Previous studies have shown that cattle learned to adapt to the system easily, but it is still unclear if older animals can adapt just as quickly. Thus, this is the first study investigating the effect of dairy cow age on learning VF in a strip-grazing trial. The results showed that older and younger cows adapted to the system equally fast, with no differences in activity behavior or changes in daily milk yield. Moreover, hair cortisol levels did not indicate lasting stress in the cows associated with the VF management during the trial. These results demonstrate the potential of VF in the management of lactating grazing cows of all ages.

Stress indicators in dairy cows adapting to virtual fencing.

Virtual fencing (VF) enables livestock grazing without physical fences by conditioning animals to a virtual boundary delimited with an audio tone (AT) and an electric pulse (EP). The present study followed the adaptation process of lactating dairy cows to a VF system with changing virtual boundaries and investigated its impact on animal welfare. Twenty cows were divided into stratified groups (2× VF; 2× electric fencing, EF) of five individuals. Each group grazed half-days in a separate EF paddock of comparable size during 3 d of acclimation (P0), followed by 21, 14, 14, and 7 d of experimental treatment (P1 to P4). At the start of the trial, all cows were equipped with an IceQube pedometer (Peacock Technology Ltd, Stirling, UK) and a VF collar (Nofence AS, Batnfjordsøra, Norway). During P0, cows were accustomed to their first paddock with a deactivated virtual boundary and wearing the sensors. In P1 to P4, an active virtual boundary for the VF groups, and a second EF for the EF groups was set up parallel to an outer EF within their paddock. Throughout the trial, the sensors continuously tracked cow positions and activity behavior at 15-min intervals. From P1 onwards, the VF collars additionally recorded each AT and EP per cow with a georeferenced time stamp. During P0 to P4, daily feed intake, body weight, and milk yield were recorded in the barn. A total of 26 milk samples were collected per cow to determine milk cortisol levels. Behavioral observations were conducted for 2 h on day 23 to record agonistic behaviors, vocalizations, and excretions. The total number of stimuli per cow ranged from 37 to 225 ATs (mean ±â€…SD: 1.9 ±â€…3.3 per day) and 3 to 11 EPs (mean ±â€…SD: 0.1 ±â€…0.7 per day) throughout the trial. The maximum number of EPs per day was 8 for an individual cow and occurred once on D1. Mean EP/AT decreased by 55% during the first three half-days of grazing and with each paddock change from 0.2 EP/AT in week 1 to 0.03, 0.02, and 0 EP/AT in weeks 4, 6, and 8, respectively. Linear and generalized mixed effects models revealed that milk yield and cortisol, feed intake, body weight, and activity and lying behavior did not significantly differ between VF and EF groups. A higher number of agonistic behaviors were observed in the VF groups when the VF system was activated. However, due to the short observation periods only few contacts were observed in total. Overall, all cows adapted to the VF system without evidence of lasting adverse effects on animal welfare.

Virtual fences are commercially available but face restrictions in some countries due to animal welfare concerns. For virtual fencing (VF), animals are equipped with collars that emit audio tones (ATs) followed by electric pulses (EPs) when they cross a virtual boundary tracked by global navigation. Existing studies have so far not covered the aspect of longer-term learning, impacting possibly VF suitability. The present study followed therefore the learning process of dairy cows with changing virtual boundaries and examined behavior and stress indicators in dairy cows during an 8-wk adaptation to VF across four experimental periods. Four control and treatment groups of five cows each were investigated. EPs occurred most frequently on days 1 to 3 and remained low for the remaining experiment. In the latter two experimental periods, almost no EPs were recorded while ATs were still triggered, indicating that it took the animals two introductions to a new fence line to respond to the ATs only. Animal welfare was assessed by monitoring cow activity and lying behavior, milk yield, milk cortisol, feed intake, body weight, and frequencies of agonistic interactions, vocalizations, and excretions. All cows adapted to the VF system without compromising animal welfare during the study period.

Nitrogen translocation by Highland cattle grazing in Alnus viridis-encroached pastures.

During the last decades, Alnus viridis has expanded over former montane pastures and meadows, due to land use and abandonment. This nitrogen-fixing woody species has triggered negative agro-environmental impacts, such as nitrogen (N) leaching, soil acidification and a reduced biodiversity. The aim of this study was to estimate the N translocation from A. viridis-encroached areas to adjacent open pastures by Highland cattle. In 2019 and 2020, Highland cattle herds equipped with GPS collars were placed in four A. viridis-encroached paddocks across Italy and Switzerland. The N content was measured in A. viridis leaves, herbaceous vegetation, and cattle dung pats, which were collected throughout the grazing season. Using GPS locations and collar activity sensors, livestock activity phases were discriminated. The N ingested by cattle was estimated through the N content of herbaceous vegetation and A. viridis leaves of vegetation patches visited by cattle during 24 h before dung sampling (N24H). The N content of herbaceous vegetation significantly increased with increasing A. viridis cover. The average N content in dung pats (31.2 ± 3.4 g.kg-1 DM) was higher than average values from literature on grazing cattle. Moreover, it was positively related to the N24H. Most of this N (29.5 ± 10.3 kg ha-1 yr-1) was translocated towards resting areas, which generally occurred on flat open pastures. Our results highlight the potential of Highland cattle to effectively translocate part of the ingested N from A. viridis-encroached towards targeted open areas, thus bringing new perspective for forage yield and quality improvement in the long-term. Supplementary Information: The online version contains supplementary material available at 10.1007/s10705-023-10282-0.

How Interactive Visualizations Compare to Ethical Frameworks as Stand-Alone Ethics Learning Tools for Health Researchers and Professionals.

BACKGROUND: Despite the bourgeoning of digital tools for bioethics research, education, and engagement, little research has empirically investigated the impact of interactive visualizations as a way to translate ethical frameworks and guidelines. To date, most frameworks take the format of text-only documents that outline and offer ethical guidance on specific contexts. This study's goal was to determine whether an interactive-visual format supports frameworks in transferring ethical knowledge by improving learning, deliberation, and user experience. METHODS: An experimental comparative study was conducted with a pre-, mid-, and post-test design using the online survey platform Qualtrics. Participants were university based early-stage health researchers who were randomly assigned to either the control condition (text-only document) or the experimental condition (interactive-visual). The primary outcome variables were learning, (measured using a questionnaire), deliberation (using cases studies) and user experience (measured using the SED/UD Scale). Analysis was conducted using descriptive statistics and mixed-effects linear regression. RESULTS: Of the 80 participants, 44 (55%) used the text-only document and 36 (45%) used the interactive-visual. Results of the knowledge-test scores showed a statistically significant difference between participants' post-test scores, indicating that the interactive-visual format better supported understanding, acquisition, and application of the framework's knowledge. Findings from the case studies showed both formats supported ethical deliberation. Results further indicated the interactive-visual provided an overall better episodic and remembered user experience compared with the text-only document. CONCLUSIONS: Our findings show that ethical frameworks formatted with interactive and visual qualities provide a more pleasing user experience and are effective formats for ethics learning and deliberation. These findings have implications for practitioners developing and deploying ethical frameworks and guidelines (e.g., in educational or employee-onboarding settings), in that the knowledge generated can lead to more effective dissemination practices of normative guidelines and health data ethics concepts.

Digital bioethics: introducing new methods for the study of bioethical issues.

The online space has become a digital public square, where individuals interact and share ideas on the most trivial to the most serious of matters, including discussions of controversial ethical issues in science, technology and medicine. In the last decade, new disciplines like computational social science and social data science have created methods to collect and analyse such data that have considerably expanded the scope of social science research. Empirical bioethics can benefit from the integration of such digital methods to investigate novel digital phenomena and trace how bioethical issues take shape online.Here, using concrete examples, we demonstrate how novel methods based on digital approaches in the social sciences can be used effectively in the domain of bioethics. We show that a digital turn in bioethics research aligns with the established aims of empirical bioethics, integrating with normative analysis and expanding the scope of the discipline, thus offering ways to reinforce the capacity of bioethics to tackle the increasing complexity of present-day ethical issues in science and technology. We propose to call this domain of research in bioethics digital bioethics.

Links across ecological scales: Plant biomass responses to elevated CO2.

The degree to which elevated CO2 concentrations (e[CO2 ]) increase the amount of carbon (C) assimilated by vegetation plays a key role in climate change. However, due to the short-term nature of CO2 enrichment experiments and the lack of reconciliation between different ecological scales, the effect of e[CO2 ] on plant biomass stocks remains a major uncertainty in future climate projections. Here, we review the effect of e[CO2 ] on plant biomass across multiple levels of ecological organization, scaling from physiological responses to changes in population-, community-, ecosystem-, and global-scale dynamics. We find that evidence for a sustained biomass response to e[CO2 ] varies across ecological scales, leading to diverging conclusions about the responses of individuals, populations, communities, and ecosystems. While the distinct focus of every scale reveals new mechanisms driving biomass accumulation under e[CO2 ], none of them provides a full picture of all relevant processes. For example, while physiological evidence suggests a possible long-term basis for increased biomass accumulation under e[CO2 ] through sustained photosynthetic stimulation, population-scale evidence indicates that a possible e[CO2 ]-induced increase in mortality rates might potentially outweigh the effect of increases in plant growth rates on biomass levels. Evidence at the global scale may indicate that e[CO2 ] has contributed to increased biomass cover over recent decades, but due to the difficulty to disentangle the effect of e[CO2 ] from a variety of climatic and land-use-related drivers of plant biomass stocks, it remains unclear whether nutrient limitations or other ecological mechanisms operating at finer scales will dampen the e[CO2 ] effect over time. By exploring these discrepancies, we identify key research gaps in our understanding of the effect of e[CO2 ] on plant biomass and highlight the need to integrate knowledge across scales of ecological organization so that large-scale modeling can represent the finer-scale mechanisms needed to constrain our understanding of future terrestrial C storage.

Movement assessment of breast and organ-at-risks using free-breathing, self-gating 4D magnetic resonance imaging workflow for breast cancer radiation therapy.

Motion management is essential in treatment planning of radiotherapy for breast cancer. This study assessed the movement of organs-at-risk and the breast using 4D magnetic resonance imaging (MRI). A self-gating respiration-resolved radial 3D gradient echo sequence was used. Five healthy volunteers were imaged at 1.5 T during free-breathing in supine position making use of a breast board. Median distances between heart and chest wall in axial views were 2.4 cm (range: 1.5 cm) and 3.0 cm (range: 1.7 cm) for end-of-exhale and end-of-inhale. 4D-MRI allowed organ delineation and might be a promising addition to novel RT planning for breast cancer patients.

A Platform to Develop and Apply Digital Methods for Empirical Bioethics Research: Mixed Methods Design and Development Study.

BACKGROUND: The rise of digital methods and computational tools has opened up the possibility of collecting and analyzing data from novel sources, such as discussions on social media. At the same time, these methods and tools introduce a dependence on technology, often resulting in a need for technical skills and expertise. Researchers from various disciplines engage in empirical bioethics research, and software development and similar skills are not usually part of their background. Therefore, researchers often depend on technical experts to develop and apply digital methods, which can create a bottleneck and hinder the broad use of digital methods in empirical bioethics research. OBJECTIVE: This study aimed to develop a research platform that would offer researchers the means to better leverage implemented digital methods, and that would simplify the process of developing new methods. METHODS: This study used a mixed methods approach to design and develop a research platform prototype. I combined established methods from user-centered design, rapid prototyping, and agile software development to iteratively develop the platform prototype. In collaboration with two other researchers, I tested and extended the platform prototype in situ by carrying out a study using the prototype. RESULTS: The resulting research platform prototype provides three digital methods, which are composed of functional components. This modular concept allows researchers to use existing methods for their own experiments and combine implemented components into new methods. CONCLUSIONS: The platform prototype illustrates the potential of the modular concept and empowers researchers without advanced technical skills to carry out experiments using digital methods and develop new methods. However, more work is needed to bring the prototype to a production-ready state.

Patient specific distortion detection and mitigation in MR images used for stereotactic radiosurgery.

Objective.In MRI-based radiation therapy planning, mitigating patient-specific distortion with standard high bandwidth scans can result in unnecessary sacrifices of signal to noise ratio. This study investigates a technique for distortion detection and mitigation on a patient specific basis.Approach.Fast B0 mapping was performed using a previously developed technique for high-resolution, large dynamic range field mapping without the need for phase unwrapping algorithms. A phantom study was performed to validate the method. Distortion mitigation was validated by reducing geometric distortion with increased acquisition bandwidth and confirmed by both the B0 mapping technique and manual measurements. Images and contours from 25 brain stereotactic radiosurgery patients and 95 targets were analyzed to estimate the range of geometric distortions expected in the brain and to estimate bandwidth required to keep all treatment targets within the ±0.5 mm iso-distortion contour.Main Results.The phantom study showed, at 3 T, the technique can measure distortions with a mean absolute error of 0.12 mm (0.18 ppm), and a maximum error of 0.37 mm (0.6 ppm). For image acquisition at 3 T and 1.0 mm resolution, mean absolute distortion under 0.5 mm in patients required bandwidths from 109 to 200 Hz px-1for patients with the least and most distortion, respectively. Maximum absolute distortion under 0.5 mm required bandwidths from 120 to 390 Hz px-1.Significance.The method for B0 mapping was shown to be valid and may be applied to assess distortion clinically. Future work will adapt the readout bandwidth to prospectively mitigate distortion with the goal to improve radiosurgery treatment outcomes by reducing healthy tissue exposure.

Qualitative analysis of visual risk communication on twitter during the Covid-19 pandemic.

BACKGROUND: The Covid-19 pandemic is characterized by uncertainty and constant change, forcing governments and health authorities to ramp up risk communication efforts. Consequently, visuality and social media platforms like Twitter have come to play a vital role in disseminating prevention messages widely. Yet to date, only little is known about what characterizes visual risk communication during the Covid-19 pandemic. To address this gap in the literature, this study's objective was to determine how visual risk communication was used on Twitter to promote the World Health Organisations (WHO) recommended preventative behaviours and how this communication changed over time. METHODS: We sourced Twitter's 500 most retweeted Covid-19 messages for each month from January-October 2020 using Crowdbreaks. For inclusion, tweets had to have visuals, be in English, come from verified accounts, and contain one of the keywords 'covid19', 'coronavirus', 'corona', or 'covid'. Following a retrospective approach, we then performed a qualitative content analysis of the 616 tweets meeting inclusion criteria. RESULTS: Our results show communication dynamics changed over the course of the pandemic. At the start, most retweeted preventative messages came from the media and health and government institutions, but overall, personal accounts with many followers (51.3%) predominated, and their tweets had the highest spread (10.0%, i.e., retweet count divided by followers). Messages used mostly photographs and images were found to be rich with information. 78.1% of Tweets contained 1-2 preventative messages, whereby 'stay home' and 'wear a mask' frequented most. Although more tweets used health loss framing, health gain messages spread more. CONCLUSION: Our findings can inform the didactics of future crisis communication. The results underscore the value of engaging individuals, particularly influencers, as advocates to spread health risk messages and promote solidarity. Further, our findings on the visual characteristic of the most retweeted tweets highlight factors that health and government organisations should consider when creating visual health messages for Twitter. However, that more tweets used the emotive medium of photographs often combined with health loss framing raises concerns about persuasive tactics. More research is needed to understand the implications of framing and its impact on public perceptions and behaviours.

Natural estrogens in surface waters of a catchment with intensive livestock farming in Switzerland.

Natural estrogens such as 17α-estradiol (E2α), 17ß-estradiol (E2ß), estrone (E1), and estriol (E3), released to surface waters from both urban and agricultural sources, are endocrine disrupting for fish. Here, we assess the prevalence of livestock farming derived natural estrogens in tributaries and ponds in the agriculturally dominated catchment of Lake Baldegg, Switzerland. Passive samplers were deployed in the main tributary and daily time-proportional water samples were collected in five tributaries for 30 days at the beginning of the vegetation period. Furthermore, we took grab samples of 12 ponds in the catchment. Aqueous samples were liquid-liquid extracted, derivatized, and analysed with LC-MS/MS and stream water samples additionally with ERα-CALUX, a bioassay for assessing total estrogenic activity. Natural estrogens were regularly detected, with mean concentrations ranging from below the limit of detection to 0.55 ng L-1 for E2ß and E1, respectively, and passive sampling and bioassay results largely confirmed these findings. Monte Carlo simulated mean natural estrogen concentrations underestimated measured ones by a factor of three to 11. An agricultural area's hydrological contribution and connectivity to surface waters seemed to be more important for the development of estrogen concentrations in streams than livestock densities in a catchment or the actual loads of slurry applied. Pond water occasionally contained natural estrogens in concentrations up to 8.6 ng L-1 for E2α. The environmental quality standards of the European Union (0.4 ng L-1 for E2ß and 3.6 ng L-1 for E1) were never exceeded for longer than a day in tributaries, but E1 reached critical concentrations for aquatic organisms in ponds.

Assessing Public Opinion on CRISPR-Cas9: Combining Crowdsourcing and Deep Learning.

BACKGROUND: The discovery of the CRISPR-Cas9-based gene editing method has opened unprecedented new potential for biological and medical engineering, sparking a growing public debate on both the potential and dangers of CRISPR applications. Given the speed of technology development and the almost instantaneous global spread of news, it is important to follow evolving debates without much delay and in sufficient detail, as certain events may have a major long-term impact on public opinion and later influence policy decisions. OBJECTIVE: Social media networks such as Twitter have shown to be major drivers of news dissemination and public discourse. They provide a vast amount of semistructured data in almost real-time and give direct access to the content of the conversations. We can now mine and analyze such data quickly because of recent developments in machine learning and natural language processing. METHODS: Here, we used Bidirectional Encoder Representations from Transformers (BERT), an attention-based transformer model, in combination with statistical methods to analyze the entirety of all tweets ever published on CRISPR since the publication of the first gene editing application in 2013. RESULTS: We show that the mean sentiment of tweets was initially very positive, but began to decrease over time, and that this decline was driven by rare peaks of strong negative sentiments. Due to the high temporal resolution of the data, we were able to associate these peaks with specific events and to observe how trending topics changed over time. CONCLUSIONS: Overall, this type of analysis can provide valuable and complementary insights into ongoing public debates, extending the traditional empirical bioethics toolset.

Grazing Allometry: Anatomy, Movement, and Foraging Behavior of Three Cattle Breeds of Different Productivity.

Modern breeding has formed a multitude of cattle breeds ranging from undemanding, low-productive breeds to high-productive, specialized dairy, or beef cattle. The choice of breed has important implications for farm management, but its impact on pasture vegetation is underestimated. We hypothesized (i) that anatomy, movement, and foraging behavior of cattle are allometrically related on the individual level, (ii) that differences among cattle are not explained by individual variation alone but also by breed, and (iii) that anatomy, movement, and foraging behavior of a cattle breed is related to its productivity. In order to test these hypotheses, we conducted a controlled grazing experiment in which three cattle breeds simultaneously grazed three types of heterogenous, alpine pastures: low-productive Highland cattle (average weight: 358 kg); local, dual-purpose Original Braunvieh (582 kg); and high-productive Angus × Holstein crossbreed (679 kg). We measured body weight and claw base of nine cows per breed after 10 weeks of grazing alpine pastures. Over a period of 9 days, we recorded the step frequency and lying time by pedometer and space use by GPS. Moreover, we visually observed foraging behavior on three occasions per cow. Forage selectivity and quality were calculated for every cow's diet. Allometric relationships were analyzed on the individual level by fitting standardized major axes. For most parameters measured, we detected strong allometric relationships and clear differences among breeds that depended on the level of productivity. The claws of Highland cattle were relatively large compared to their body weight and thus they exerted less static pressure than other breeds. Moreover, the more productive a breed was, the higher its selectivity and step frequency were. For example, Highland cattle foraged shrubs and thistles more frequently than high-productive Angus × Holstein. The latter walked longer distances to select higher-quality forage, while Highland cattle used the space more evenly, visited steeper slopes, and moved further away from water points. Irrespective of breed, vegetation composition influenced cattle behavior: On pastures of low forage quality, animals walked more, foraged more selectively, and used space less evenly. In conclusion, the observed breed-specific differences can be used to improve pasture management and grassland conservation.

Free-breathing fat and R2 * quantification in the liver using a stack-of-stars multi-echo acquisition with respiratory-resolved model-based reconstruction.

PURPOSE: To develop a free-breathing hepatic fat and R2∗ quantification method by extending a previously described stack-of-stars model-based fat-water separation technique with additional modeling of the transverse relaxation rate R2∗ . METHODS: The proposed technique combines motion-robust radial sampling using a stack-of-stars bipolar multi-echo 3D GRE acquisition with iterative model-based fat-water separation. Parallel-Imaging and Compressed-Sensing principles are incorporated through modeling of the coil-sensitivity profiles and enforcement of total-variation (TV) sparsity on estimated water, fat, and R2∗ parameter maps. Water and fat signals are used to estimate the confounder-corrected proton-density fat fraction (PDFF). Two strategies for handling respiratory motion are described: motion-averaged and motion-resolved reconstruction. Both techniques were evaluated in patients (n = 14) undergoing a hepatobiliary research protocol at 3T. PDFF and R2∗ parameter maps were compared to a breath-holding Cartesian reference approach. RESULTS: Linear regression analyses demonstrated strong (r > 0.96) and significant (P ≪ .01) correlations between radial and Cartesian PDFF measurements for both the motion-averaged reconstruction (slope: 0.90; intercept: 0.07%) and the motion-resolved reconstruction (slope: 0.90; intercept: 0.11%). The motion-averaged technique overestimated hepatic R2∗ values (slope: 0.35; intercept: 30.2 1/s) compared to the Cartesian reference. However, performing a respiratory-resolved reconstruction led to better R2∗ value consistency (slope: 0.77; intercept: 7.5 1/s). CONCLUSIONS: The proposed techniques are promising alternatives to conventional Cartesian imaging for fat and R2∗ quantification in patients with limited breath-holding capabilities. For accurate R2∗ estimation, respiratory-resolved reconstruction should be used.

Visualizing an Ethics Framework: A Method to Create Interactive Knowledge Visualizations From Health Policy Documents.

BACKGROUND: Data have become an essential factor in driving health research and are key to the development of personalized and precision medicine. Primary and secondary use of personal data holds significant potential for research; however, it also introduces a new set of challenges around consent processes, privacy, and data sharing. Research institutions have issued ethical guidelines to address challenges and ensure responsible data processing and data sharing. However, ethical guidelines directed at researchers and medical professionals are often complex; require readers who are familiar with specific terminology; and can be hard to understand for people without sufficient background knowledge in legislation, research, and data processing practices. OBJECTIVE: This study aimed to visually represent an ethics framework to make its content more accessible to its stakeholders. More generally, we wanted to explore the potential of visualizing policy documents to combat and prevent research misconduct by improving the capacity of actors in health research to handle data responsibly. METHODS: We used a mixed methods approach based on knowledge visualization with 3 sequential steps: qualitative content analysis (open and axial coding, among others); visualizing the knowledge structure, which resulted from the previous step; and adding interactive functionality to access information using rapid prototyping. RESULTS: Through our iterative methodology, we developed a tool that allows users to explore an ethics framework for data sharing through an interactive visualization. Our results represent an approach that can make policy documents easier to understand and, therefore, more applicable in practice. CONCLUSIONS: Meaningful communication and understanding each other remain a challenge in various areas of health care and medicine. We contribute to advancing communication practices through the introduction of knowledge visualization to bioethics to offer a novel way to tackle this relevant issue.

Assessment of spatial variability of multiple ecosystem services in grasslands of different intensities.

Grasslands provide multiple Ecosystem Services (ES) such as forage provision, carbon sequestration or habitat provision. Knowledge about the trade-offs between these ES is of great importance for grassland management. Yet, the outcome of different management strategies on ES provision is highly uncertain due to spatial variability. We aim to characterize the provision (level and spatial variability) of grassland ES under various management strategies. To do so, we combine empirical data for multiple ES with spatially explicit census data on land use intensities. We analyzed the variations of five ES (forage provision, climate regulation, pollination, biodiversity conservation and outdoor recreation) using data from biodiversity fieldwork, experimental plots for carbon as well as social network data from Flickr. These data were used to calculate the distribution of modelled individual and multiple ES values from different grassland management types in a Swiss case study region using spatial explicit information for 17,383 grassland parcels. Our results show that (1) management regime and intensity levels play an important role in ES provision but their impact depends on the ES. In general, extensive management, especially in pastures, favors all ES but forage provision, whereas intensive management favors only forage provision and outdoor recreation; (2) ES potential provision varies between parcels under the same management due to the influence of environmental drivers, related to topography and landscape structure; (3) there is a trade-offs between forage provision and other ES at the cantonal level but a synergy between forage provision and biodiversity conservation within the grassland categories, due to the negative impact of elevation on both ES. Information about multiple ES provision is key to support effective agri-environmental measures and information about the spatial variability can prevent uncertain outputs of decision-making processes.

Accurate fatty acid composition estimation of adipose tissue in the abdomen based on bipolar multi-echo MRI.

PURPOSE: To develop a bipolar multi-echo MRI method for the accurate estimation of the adipose tissue fatty acid composition (FAC) using clinically relevant protocols at clinical field strength. METHODS: The proposed technique jointly estimates confounding factors (field map, R2* , eddy-current phase) and triglyceride saturation state parameters by fitting multi-echo gradient echo acquisitions to a complex signal model. The noise propagation behavior was improved by applying a low-rank enforcing denoising technique and by addressing eddy-current-induced phase discrepancies analytically. The impact of the total echo train duration on the FAC parameter map accuracy was analyzed in an oil phantom at 3T. Accuracy and reproducibility assessment was based on in vitro oil phantom measurements at two field strengths (3T and 1.5T) and with two different protocols. Repeatability was assessed in vivo in patients (n = 8) with suspected fatty liver disease using test-retest acquisitions in the abdominal subcutaneous, perirenal and mesenteric fat depots. RESULTS: Echo train readout durations of at least five times the conventional in-phase time were required for accurate FAC estimation in areas of high fat content. In vitro, linear regression and Bland-Altman analyses demonstrated strong (r > 0.94) and significant (P â‰ª 0.01) correlations between measured and reference FACs for all acquisitions, with smaller overall intercepts and biases at 3T compared to 1.5T. In vivo, reported mean absolute differences between test and retest were 1.54%, 3.31%, and 2.63% for the saturated, mono-unsaturated, and poly-unsaturated fat component, respectively. CONCLUSIONS: Accurate and reproducible MRI-based FAC quantification within a breath-hold is possible at clinical field strengths.

Detection of Infantile Movement Disorders in Video Data Using Deformable Part-Based Model.

Movement analysis of infants' body parts is momentous for the early detection of various movement disorders such as cerebral palsy. Most existing techniques are either marker-based or use wearable sensors to analyze the movement disorders. Such techniques work well for adults, however they are not effective for infants as wearing such sensors or markers may cause discomfort to them, affecting their natural movements. This paper presents a method to help the clinicians for the early detection of movement disorders in infants. The proposed method is marker-less and does not use any wearable sensors which makes it ideal for the analysis of body parts movement in infants. The algorithm is based on the deformable part-based model to detect the body parts and track them in the subsequent frames of the video to encode the motion information. The proposed algorithm learns a model using a set of part filters and spatial relations between the body parts. In particular, it forms a mixture of part-filters for each body part to determine its orientation which is used to detect the parts and analyze their movements by tracking them in the temporal direction. The model is represented using a tree-structured graph and the learning process is carried out using the structured support vector machine. The proposed framework will assist the clinicians and the general practitioners in the early detection of infantile movement disorders. The performance evaluation of the proposed method is carried out on a large dataset and the results compared with the existing techniques demonstrate its effectiveness.

Data Sharing For Precision Medicine: Policy Lessons And Future Directions.

Data sharing is a precondition of precision medicine. Numerous organizations have produced abundant guidance on data sharing. Despite such efforts, data are not being shared to a degree that can trigger the expected data-driven revolution in precision medicine. We set out to explore why. Here we report the results of a comprehensive analysis of data-sharing guidelines issued over the past two decades by multiple organizations. We found that the guidelines overlap on a restricted set of policy themes. However, we observed substantial fragmentation in the policy landscape across specific organizations and data types. This may have contributed to the current stalemate in data sharing. To move toward a more efficient data-sharing ecosystem for precision medicine, policy makers should explore innovative ways to cope with central policy themes such as privacy, consent, and data quality; focus guidance on interoperability, attribution, and public engagement; and promote data-sharing policies that can be adapted to multiple data types.

Single-breath-hold abdominal [Formula: see text] mapping using 3D Cartesian Look-Locker with spatiotemporal sparsity constraints.

OBJECTIVE: Our aim was to develop and validate a 3D Cartesian Look-Locker [Formula: see text] mapping technique that achieves high accuracy and whole-liver coverage within a single breath-hold. MATERIALS AND METHODS: The proposed method combines sparse Cartesian sampling based on a spatiotemporally incoherent Poisson pattern and k-space segmentation, dedicated for high-temporal-resolution imaging. This combination allows capturing tissue with short relaxation times with volumetric coverage. A joint reconstruction of the 3D + inversion time (TI) data via compressed sensing exploits the spatiotemporal sparsity and ensures consistent quality for the subsequent multistep [Formula: see text] mapping. Data from the National Institute of Standards and Technology (NIST) phantom and 11 volunteers, along with reference 2D Look-Locker acquisitions, are used for validation. 2D and 3D methods are compared based on [Formula: see text] values in different abdominal tissues at 1.5 and 3 T. RESULTS: [Formula: see text] maps obtained from the proposed 3D method compare favorably with those from the 2D reference and additionally allow for reformatting or volumetric analysis. Excellent agreement is shown in phantom [bias[Formula: see text] < 2%, bias[Formula: see text] < 5% for (120; 2000) ms] and volunteer data (3D and 2D deviation < 4% for liver, muscle, and spleen) for clinically acceptable scan (20 s) and reconstruction times (< 4 min). CONCLUSION: Whole-liver [Formula: see text] mapping with high accuracy and precision is feasible in one breath-hold using spatiotemporally incoherent, sparse 3D Cartesian sampling.