Farmed fish welfare research status in Latin America: A review.

Latin America (LATAM) plays an important role in the world's production of aquatic animals and is the second most productive region in the world. Chile, Ecuador, Brazil, Mexico, Colombia, and Perú contribute 87% of LATAM aquaculture production. The fish welfare in aquaculture is of increasing public concern globally, and LATAM is no exception, growing in importance for fish farmers, authorities, and scientists. Although the topic is somewhat controversial, the welfare status of farmed fish has direct implications for their production and the sustainability of the industry. Therefore, this study analyses scientific papers on animal welfare in farmed fish, from the six countries in LATAM with the highest aquaculture production. The main objectives were to quantify the number of papers published between 2000 and 2023 on fish welfare by using scientific databases. A total of 285 papers were found for the period analysed. The country with the largest number of publications was Brazil (75.79%), followed by Chile (13.33%), Mexico (7.02%), Peru (1.75%), Ecuador, and Colombia (1.05%). Nile tilapia was the most studied species, appearing in 30.18% of the publications, with most of the studies mainly dealing with nutrition (32.28%). The growth of aquaculture is leading to joint efforts to generate knowledge on welfare issues, especially in poorly studied species with high production, to create policies that help minimize welfare risks. Given this, the insights generated by this review could be a useful addition to approaches investigating the trends and concepts of fish welfare in LATAM.

[Data processing in secure data processing environments using the example of MRI brain scans-a simultaneous plea for a legal provision for data processing for scientific research purposes]. / Datenverarbeitung in sicheren Verarbeitungsumgebungen am Beispiel von MRT-Gehirnscans ­ zugleich ein Plädoyer für eine rechtssichere Forschungsgrundlage.

The use of data for medical scientific research offers great potential for society as a whole, as the evaluation of large volumes of data with machine learning methods can result in new research approaches as well as new methods of diagnostics or treatment. However, the use of such data often fails due to high prerequisites or unclear requirements of data protection law.Processing of radiology data, such as MRI brain scans, is tied to specific risks for data subjects. This complicates the processing of such data for research purposes. Data trustees can help to reduce these risks through offering independent anonymization and pseudonymization services as well as secure processing environments in which health data is stored only for the time required for processing and analysis and is subsequently deleted.Thus, the use of data trustees can help to comply with data protection law, with risk-reduction being considered in favor of processing in decisions weighing the interests for and against data processing as necessary to comply with Art. 9 Para. 2 lit. j, Art. 89 Para 1 of the General Data Protection Regulation (GPDR) in conjunction with national law, or when assessing the compatibility of the secondary purpose of the processing with the purpose of collection. In this respect, the use of data trust models can contribute to the reduction of hurdles for the data processing of health data for scientific research purposes.

Large language models are changing landscape of academic publications. A positive transformation?

The advent of large language models (LLMs) based on neural networks marks a significant shift in academic writing, particularly in medical sciences. These models, including OpenAI's GPT-4, Google's Bard, and Anthropic's Claude, enable more efficient text processing through transformer architecture and attention mechanisms. LLMs can generate coherent texts that are indistinguishable from human-written content. In medicine, they can contribute to the automation of literature reviews, data extraction, and hypothesis formulation. However, ethical concerns arise regarding the quality and integrity of scientific publications and the risk of generating misleading content. This article provides an overview of how LLMs are changing medical writing, the ethical dilemmas they bring, and the possibilities for detecting AI-generated text. It concludes with a focus on the potential future of LLMs in academic publishing and their impact on the medical community.

[DEVELOPMENT OF THE SECTOR of R&D development in Russian HIGHER medical education in digitization conditions].

The article considers results of study of the R&D sector directions development in system of Russian medical higher education in the context of digitization. The analysis made it possible to substantiate timeliness and importance of solving problems of improving medical services quality against the background of necessity for medical workers to systematically master breakthrough digital technologies in current medical practice. This conditions importance to ensure efficiency of R&D in Russian higher medical education in the context of digitization. The main models of organization of activities in the field of R&D are characterized, taking into account sources of financing and staffing. Based on on-line surveys of students in Google docs about their attitude to their further participation in R&D during education and after graduation, weak motivation to be engaged in R&D during their university education was revealed that is justified by non-obviousness of prospects of financial remuneration. Along with this, study established high degree of interest among students to mastering breakthrough digital technologies in order to further apply them in medical practice together with the latest medical technologies.

Harmonization after the GDPR? Divergences in the rules for genetic and health data sharing in four member states and ways to overcome them by EU measures: Insights from Germany, Greece, Latvia and Sweden.

The EU member states' healthcare and health-related research sectors are both characterized by an emerging infrastructural coalescence on a national and European level. The culmination of this coalescence is the planned creation of a European Health Data Space, an EU-wide infrastructure for the processing of personal data for healthcare and for secondary uses such as scientific research. In contrast to growing technical interoperability, the legal framework for such integration is not yet defined in detail, particularly with regard to data protection law. Its development is accompanied by discussions about divergent member state implementations of the EU General Data Protection Regulation (GDPR) that affect data sharing between healthcare and scientific research actors and across various sectors driven by divergent processing purposes. The article presents four member states' main rules on data sharing based on the respective provision of the GDPR in six health-related contexts regarding data sharing across the healthcare and research sector and between the main actors of those sectors. The striking differences are then evaluated from the perspective of their factual effect on European data sharing depending on the legal characteristics of the GDPR provisions they rely on. Against this backdrop, the planned regulatory measures for the setup of the European Health Data Space are introduced and evaluated with regard to further harmonization between member states' laws and possibilities to overcome divergences in data protection rules relevant for European data sharing. The results of the analysis point to the conclusion that the destructive effect of divergent member state rules depends on the legal qualification of the EU provisions they rely on and that this qualification also determines which further EU regulatory measure would be the most effective to set the framework for the European Health Data Space.

Scientific research on food environments in Brazil: a scoping review.

OBJECTIVE: To map the scientific research on food environments in Brazil, based on the following questions: How many studies have addressed food environments?; What study designs and methodological approaches were applied?; What is the geographic scope of the studies?; What scenarios and dimensions of food environments were studied?; Which population groups were studied?; How were food environments conceptualised?; What are the main limitations of the studies? DESIGN: Scoping review conducted in four databases, from January 2005 to December 2022, using different food environment-related terms to cover the main types and dimensions proposed in the literature. The studies were independently selected by two authors. A narrative synthesis was used to summarise the findings. SETTING: Brazil. PARTICIPANTS: 130 articles. RESULTS: Scientific research on Brazilian food environments has been increasing. The analytical quantitative approach and the cross-sectional design were the most frequently used. Most articles were published in English. The majority of studies evaluated the community food environment, addressed aspects of the physical dimension, sampled the adult population, had food consumption as an outcome, used primary data, and were carried out in capital cities in the Southeast region. Furthermore, in most articles, no conceptual model was explicitly adopted. CONCLUSIONS: Gaps in literature are related to the need for conducting studies in the Brazilian countryside, the support for the formulation of research questions based on conceptual models, the use of valid and reliable instruments to collect primary data, in addition to the need for a greater number of longitudinal, intervention and qualitative studies.

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.

Best Practices for Using AI Tools as an Author, Peer Reviewer, or Editor.

The ethics of generative artificial intelligence (AI) use in scientific manuscript content creation has become a serious matter of concern in the scientific publishing community. Generative AI has computationally become capable of elaborating research questions; refining programming code; generating text in scientific language; and generating images, graphics, or figures. However, this technology should be used with caution. In this editorial, we outline the current state of editorial policies on generative AI or chatbot use in authorship, peer review, and editorial processing of scientific and scholarly manuscripts. Additionally, we provide JMIR Publications' editorial policies on these issues. We further detail JMIR Publications' approach to the applications of AI in the editorial process for manuscripts in review in a JMIR Publications journal.

Reducing Clinical Trial Monitoring Resources and Costs With Remote Monitoring: Retrospective Study Comparing On-Site Versus Hybrid Monitoring.

BACKGROUND: Clinical research associates (CRAs) monitor the progress of a trial, verify the data collected, and ensure that the trial is carried out and reported in accordance with the trial protocol, standard operating procedures, and relevant laws and regulations. In response to monitoring challenges during the COVID-19 pandemic, Peking University Cancer Hospital launched a remote monitoring system and established a monitoring model, combining on-site and remote monitoring of clinical trials. Considering the increasing digitization of clinical trials, it is important to determine the optimal monitoring model for the general benefit of centers conducting clinical trials worldwide. OBJECTIVE: We sought to summarize our practical experience of a hybrid model of remote and on-site monitoring of clinical trials and provide guidance for clinical trial monitoring management. METHODS: We evaluated 201 trials conducted by our hospital that used on-site monitoring alone or a hybrid monitoring model, of which 91 trials used on-site monitoring alone (arm A) and 110 used a hybrid model of remote and on-site monitoring (arm B). We reviewed trial monitoring reports from June 20, 2021, to June 20, 2022, and used a customized questionnaire to collect and compare the following information: monitoring cost of trials in the 2 models as a sum of the CRAs' transportation (eg, taxi fare and air fare), accommodation, and meal costs; differences in monitoring frequency; the number of monitored documents; and monitoring duration. RESULTS: From June 20, 2021, to June 20, 2022, a total of 320 CRAs representing 201 sponsors used the remote monitoring system for source data review and the verification of data from 3299 patients in 320 trials. Arm A trials were monitored 728 times and arm B trials were monitored 849 times. The hybrid model in arm B had 52.9% (449/849) remote visits and 48.1% (409/849) on-site visits. The number of patients' visits that could be reviewed in the hybrid monitoring model increased by 34% (4.70/13.80; P=.004) compared with that in the traditional model, whereas the duration of monitoring decreased by 13.8% (3.96/28.61; P=.03) and the total cost of monitoring decreased by 46.2% (CNY ¥188.74/408.80; P<.001). These differences were shown by nonparametric testing to be statistically significant (P<.05). CONCLUSIONS: The hybrid monitoring model can ensure timely detection of monitoring issues, improve monitoring efficiency, and reduce the cost of clinical trials and should therefore be applied more broadly in future clinical studies.

Women Are Underrepresented Among Authors of Retracted Publications: Retrospective Study of 134 Medical Journals.

We examined the gender distribution of authors of retracted articles in 134 medical journals across 10 disciplines, compared it with the gender distribution of authors of all published articles, and found that women were underrepresented among authors of retracted articles, and, in particular, of articles retracted for misconduct.

Comparisons of Quality, Correctness, and Similarity Between ChatGPT-Generated and Human-Written Abstracts for Basic Research: Cross-Sectional Study.

BACKGROUND: ChatGPT may act as a research assistant to help organize the direction of thinking and summarize research findings. However, few studies have examined the quality, similarity (abstracts being similar to the original one), and accuracy of the abstracts generated by ChatGPT when researchers provide full-text basic research papers. OBJECTIVE: We aimed to assess the applicability of an artificial intelligence (AI) model in generating abstracts for basic preclinical research. METHODS: We selected 30 basic research papers from Nature, Genome Biology, and Biological Psychiatry. Excluding abstracts, we inputted the full text into ChatPDF, an application of a language model based on ChatGPT, and we prompted it to generate abstracts with the same style as used in the original papers. A total of 8 experts were invited to evaluate the quality of these abstracts (based on a Likert scale of 0-10) and identify which abstracts were generated by ChatPDF, using a blind approach. These abstracts were also evaluated for their similarity to the original abstracts and the accuracy of the AI content. RESULTS: The quality of ChatGPT-generated abstracts was lower than that of the actual abstracts (10-point Likert scale: mean 4.72, SD 2.09 vs mean 8.09, SD 1.03; P<.001). The difference in quality was significant in the unstructured format (mean difference -4.33; 95% CI -4.79 to -3.86; P<.001) but minimal in the 4-subheading structured format (mean difference -2.33; 95% CI -2.79 to -1.86). Among the 30 ChatGPT-generated abstracts, 3 showed wrong conclusions, and 10 were identified as AI content. The mean percentage of similarity between the original and the generated abstracts was not high (2.10%-4.40%). The blinded reviewers achieved a 93% (224/240) accuracy rate in guessing which abstracts were written using ChatGPT. CONCLUSIONS: Using ChatGPT to generate a scientific abstract may not lead to issues of similarity when using real full texts written by humans. However, the quality of the ChatGPT-generated abstracts was suboptimal, and their accuracy was not 100%.

Factors affecting the scientific research ability and the corresponding countermeasures in clinical postgraduates.

BACKGROUND: Scientific research ability (SRA) is very important for clinical postgraduates. However, the factors affecting students' SRA are constantly changing with the development of medicine. The aim of this study was to investigate the current situation of SRA in clinical postgraduates and exploring the potential factors and the corresponding countermeasures under the background of new medical science. METHODS: A total of 133 postgraduates (first- or second-year) were investigated by questionnaire in the Second Affiliated Hospital of Fujian Medical University. All results were analyzed by R software. RESULTS: In terms of the SRA, academic-degree postgraduate students (ADPSs) were significantly better than professional-degree postgraduate students (PDPSs) (P = 0.001), the students with scientific research interest were remarkably better than those without scientific research interest (P = 0.004), the students who mastered statistical analysis methods were more prominent than those who did not (P = 0.007), the students with paper-writing skills were obviously superior to those without it (P = 0.003), and the second-year students were notably better than the first-year students (P = 0.003). Stratified analysis by the above factors except the degree type showed no significant difference in the first-year postgraduates. In the second-year postgraduates, the ADPSs were remarkably superior to the PDPSs (P = 0.002), the students with scientific research interest were obviously better than those without scientific research interest (P = 0.014), the students with more time investment in scientific research were more prominent than those with less time investment in scientific research (P = 0.025), the students with paper-writing skills were notably superior to those without it (P = 0.031), and the students with plotting ability were better than those without it (P = 0.013). CONCLUSION: The important factors affecting the SRA of clinical postgraduates include the degree type, the grade of student, scientific research interest, time investment in scientific research, statistical analysis methods, paper-writing skills, plotting ability. In short, earlier systematic SRA training contributes to the improvement of SRA in clinical postgraduates, especially in PDPSs.

Creativity in Scientific Research: Multidisciplinarity Fosters Depth of Ideas Among Scientists in Electronic "Brainwriting" Groups.

OBJECTIVE: The aim of this study was to examine the potential benefits of multidisciplinarity among agri-food researchers working in small groups to generate ideas to stimulate innovation in the context of a laboratory project. BACKGROUND: Research on the role of multidisciplinarity in scientific research teams remains limited, particularly regarding the generation of ideas to innovate in a real laboratory project, and on a task with a real challenge for innovation. METHOD: Researchers and agri-food research staff were assigned to small groups of either multidisciplinary or unidisciplinary composition to produce ideas on a cross-cutting theme for an innovative laboratory project using an electronic "brainwriting" application. RESULTS: A greater depth in idea generation (number of ideas per category) was observed in the multidisciplinary condition than in the unidisciplinary condition. CONCLUSION: The main benefits of this study were to experimentally examine the effects of multidisciplinarity in small scientific research groups on the production of ideas in a field study conducted on the premises of an agri-food laboratory. APPLICATION: This study provides advice on how to promote innovative projects by stimulating ideation processes, which includes constructing small multidisciplinary groups and using an electronic "brainwriting" technique.

How publications and patents are contributing to the development of municipal solid waste management: Viewing the UN Sustainable Development Goals as ground zero.

Academia and industry have strengthened each other under the guidelines of regulatory institutions to contribute theoretical knowledge and practical solutions for society, which can be presented in a combination of publishing research and filing patents. In the case of municipal solid waste management (MSWM), a great transformation from a linear to a circular view has been in process. In this study, we investigated the role of the United Nations Sustainable Development Goals (SDGs) in MSWM-related development and transformation. The authors examined the contributions of academic and industrial spheres to MSWM in the past 70 years by examining Web of Science's Core Collection and Derwent Innovations Index. The results showed that SDGs not only accelerated the research on MSWM but also pulled MSWM-related knowledge and innovation to new fronts that focus on sustainable and circular methods. Based on the current findings, we derived implications for academia, industry, and policymakers.

Cannabis for the treatment of amyotrophic lateral sclerosis: What is the patients' view?

Cannabis may have therapeutic benefits to relieve symptoms of amyotrophic lateral sclerosis (ALS) thanks to its pleiotropic pharmacological activity. This study is the first to present a large questionnaire-based survey about the "real-life" situation regarding cannabis use in the medical context in ALS patients in France. There were 129 respondents and 28 reported the use of cannabis (21.7%) to relieve symptoms of ALS. Participants mostly reported the use of cannabidiol (CBD) oil and cannabis weed and declared benefits both on motor (rigidity, cramps, fasciculations) and non-motor (sleep quality, pain, emotional state, quality of life, depression) symptoms and only eight reported minor adverse reactions (drowsiness, euphoria and dry mouth). Even if cannabis is mostly used outside medical pathways and could expose patients to complications (street and uncontrolled drugs, drug-drug interactions, adverse effects…), most of the participants reported "rational" consumption (legal cannabinoids, with only few combustion and adverse reactions). Despite some limitations, this study highlights the need for further research on the potential benefits of cannabis use for the management of ALS motor and non-motor symptoms. Indeed, there is an urgent need and call for and from patients to know more about cannabis and secure its use in a medical context.

[ChatGPT in scientific research: a guide to informed use]. / ChatGPT nella ricerca scientifica: guida all'uso consapevole.

Using ChatGPT in scientific research offers revolutionary opportunities thanks to its natural language interaction capabilities and production of coherent and sophisticated text.Artificial intelligence can automate activities such as information synthesis and schematization, improving scientific communication and computer code writing.However, the lack of a complete understanding of context, the risk of spreading misleading information, and the possibility of plagiarism represent some of the biggest limitations in the current use of this technology.The role of human experience remains fundamental for in-depth understanding of context, exercising critical thinking, and ensuring respect for the ethical principles of scientific research.A responsible and aware use of tools such as ChatGPT can offer great benefits to the scientific community, but it is essential to remember that these tools are only a support and cannot replace human judgment and experience.

Stereoselective Plasmonic Interaction in Peptide-tethered Photopolymerizable Diacetylenes Doped with Chiral Gold Nanoparticles.

Designing polymeric systems with ultra-high optical activity is instrumental in the pursuit of smart artificial chiroptical materials, including the fundamental understanding of structure/property relations. Herein, we report a diacetylene (DA) moiety flanked by chiral D- and L-FF dipeptide methyl esters that exhibits efficient topochemical photopolymerization in the solid phase to furnish polydiacetylene (PDA) with desired control over the chiroptical properties. The doping of the achiral gold nanoparticles provides plasmonic interaction with the PDAs to render asymmetric shape to the circular dichroism bands. With the judicious design of the chiral amino acid ligand appended to the AuNPs, we demonstrate the first example of selective chiral amplification mediated by stereo-structural matching of the polymer-plasmonic AuNP hybrid pairs. Such ordered self-assembly aided by topochemical polymerization in peptide-tethered PDA provides a smart strategy to produce soft responsive materials for applications in chiral photonics.

Promoting scientific literacy in evolution through citizen science.

Evolutionary understanding is central to biology. It is also an essential prerequisite to understanding and making informed decisions about societal issues such as climate change. Yet, evolution is generally poorly understood by civil society and many misconceptions exist. Citizen science, which has been increasing in popularity as a means to gather new data and promote scientific literacy, is one strategy through which people could learn about evolution. However, despite the potential for citizen science to promote evolution learning opportunities, very few projects implement them. In this paper, we make the case for incorporating evolution education into citizen science, define key learning goals, and suggest opportunities for designing and evaluating projects in order to promote scientific literacy in evolution.

Patients' and public views and attitudes towards the sharing of health data for research: a narrative review of the empirical evidence.

INTRODUCTION: International sharing of health data opens the door to the study of the so-called 'Big Data', which holds great promise for improving patient-centred care. Failure of recent data sharing initiatives indicates an urgent need to invest in societal trust in researchers and institutions. Key to an informed understanding of such a 'social license' is identifying the views patients and the public may hold with regard to data sharing for health research. METHODS: We performed a narrative review of the empirical evidence addressing patients' and public views and attitudes towards the use of health data for research purposes. The literature databases PubMed (MEDLINE), Embase, Scopus and Google Scholar were searched in April 2019 to identify relevant publications. Patients' and public attitudes were extracted from selected references and thematically categorised. RESULTS: Twenty-seven papers were included for review, including both qualitative and quantitative studies and systematic reviews. Results suggest widespread-though conditional-support among patients and the public for data sharing for health research. Despite the fact that participants recognise actual or potential benefits of data research, they expressed concerns about breaches of confidentiality and potential abuses of the data. Studies showed agreement on the following conditions: value, privacy, risk minimisation, data security, transparency, control, information, trust, responsibility and accountability. CONCLUSIONS: Our results indicate that a social license for data-intensive health research cannot simply be presumed. To strengthen the social license, identified conditions ought to be operationalised in a governance framework that incorporates the diverse patient and public values, needs and interests.

Ethical issues in computational pathology.

This paper explores ethical issues raised by whole slide image-based computational pathology. After briefly giving examples drawn from some recent literature of advances in this field, we consider some ethical problems it might be thought to pose. These arise from (1) the tension between artificial intelligence (AI) research-with its hunger for more and more data-and the default preference in data ethics and data protection law for the minimisation of personal data collection and processing; (2) the fact that computational pathology lends itself to kinds of data fusion that go against data ethics norms and some norms of biobanking; (3) the fact that AI methods are esoteric and produce results that are sometimes unexplainable (the so-called 'black box'problem) and (4) the fact that computational pathology is particularly dependent on scanning technology manufacturers with interests of their own in profit-making from data collection. We shall suggest that most of these issues are resolvable.