Artificial intelligence systems (ai-systems) (e.g. machine learning, generative artificial intelligence), in healthcare and medicine, have been received with hopes of better care quality, more efficiency, lower care costs, etc. Simultaneously, these systems have been met with reservations regarding their impacts on stakeholders\' privacy, on changing power dynamics, on systemic biases, etc. Fortunately, healthcare and medicine have been guided by a multitude of ethical principles, frameworks, or approaches, which also guide the use of ai-systems in healthcare and medicine, in one form or another. Nevertheless, in this article, I argue that most of these approaches are inspired by a local isolationist view on ai-systems, here exemplified by the principlist approach. Despite positive contributions to laying out the ethical landscape of ai-systems in healthcare and medicine, such ethics approaches are too focused on a specific local healthcare and medical setting, be it a particular care relationship, a particular care organisation, or a particular society or region. By doing so, they lose sight of the global impacts ai-systems have, especially environmental impacts and related social impacts, such as increased health risks. To meet this gap, this article presents a global approach to the ethics of ai-systems in healthcare and medicine which consists of five levels of ethical impacts and analysis: individual-relational, organisational, societal, global, and historical. As such, this global approach incorporates the local isolationist view by integrating it in a wider landscape of ethical consideration so to ensure ai-systems meet the needs of everyone everywhere.

There is clear evidence that the sympathetic nervous system (SNS) mediates bone metabolism. Histological studies show abundant SNS innervation of the periosteum and bone marrow-these nerves consist of noradrenergic fibers that immunostain for tyrosine hydroxylase, dopamine beta hydroxylase, or neuropeptide Y. Nonetheless, the brain sites that send efferent SNS outflow to bone have not yet been characterized. Using pseudorabies (PRV) viral transneuronal tracing, we report, for the first time, the identification of central SNS outflow sites that innervate bone. We find that the central SNS outflow to bone originates from 87 brain nuclei, sub-nuclei and regions of six brain divisions, namely the midbrain and pons, hypothalamus, hindbrain medulla, forebrain, cerebral cortex, and thalamus. We also find that certain sites, such as the raphe magnus (RMg) of the medulla and periaqueductal gray (PAG) of the midbrain, display greater degrees of PRV152 infection, suggesting that there is considerable site-specific variation in the levels of central SNS outflow to bone. This comprehensive compendium illustrating the central coding and control of SNS efferent signals to bone should allow for a greater understanding of the neural regulation of bone metabolism, and importantly and of clinical relevance, mechanisms for central bone pain.

BACKGROUND: The pathogenesis of multiple sclerosis (MS) requires both genetic factors and environmental events. The question remains, however, whether these factors and events completely describe the MS disease process. This question was addressed using the Canadian MS data, which includes 29 478 individuals, estimated to represent 65-83% of all Canadian patients with MS.
METHODS: The \'genetically-susceptible\' subset of the population, (G), includes everyone who has any non-zero life-time chance of developing MS, under some environmental conditions. A \'sufficient\' environmental exposure, for any genetically-susceptible individual, includes every set of environmental conditions, each of which is \'sufficient\', by itself, to cause MS in that person. This analysis incorporates many epidemiological parameters, involved in MS pathogenesis, only some of which are directly observable, and establishes \'plausible\' value ranges for each parameter. Those parameter value combinations (ie, solutions) that fall within these plausible ranges are then determined.
RESULTS: Only a small proportion of the population (≤52%) has any possibility of developing MS, regardless of any environmental conditions that they could experience. Moreover, some of these genetically-susceptible individuals, despite their experiencing a \'sufficient\' environmental exposure, will still not develop disease.
CONCLUSIONS: This analysis explicitly includes all of those genetic factors and environmental events (including their interactions), which are necessary for MS pathogenesis, regardless of whether these factors, events and interactions are known, suspected or as yet unrecognised. Nevertheless, in addition, a \'truly\' random mechanism also seems to play a critical role in disease pathogenesis. This observation provides empirical evidence, which undermines the widely-held deterministic view of nature. Moreover, both sexes seem to share a similar genetic and environmental disease basis. If so, then it is this random mechanism, which is primarily responsible for the currently-observed differences in MS disease expression between susceptible women and susceptible men.

BACKGROUND: The role of environmental factors in neurological disorders constitutes a topic of increasing importance. Teaching in European universities should expand and update this field gaining future health professionals including adjacent disciplines.
OBJECTIVE: To describe recent efforts to create courses that cover crucial interdisciplinary content that we believe should be included in modern education, and to adapt modern pedagogic strategies.
METHODS: In collaboration with RISE (Rencontres Internationales Santé Environnement), elective courses focused on Environmental Health and Medicine (EHM) were developed, in France, Sweden, and Turkey. The courses combined classic teaching methods and new pedagogic and digital solutions to create environment-related health awareness and facilitate future interprofessional collaboration in this field.
RESULTS: UPRISE is an innovative elective course introduced in 2020 in Sweden\'s Uppsala University with the participation of lecturers from several countries and aim to recruit students from different universities. A total of 45, mainly female students (68%), participated in the course. In Strasbourg, France, a novel course on environmental medicine was held in 2019-2023 and examined 90 students, of which more than half were female. Nine graduate nurse students in Turkey attended ten seminar series focused on EHM. Overall, students expressed satisfaction with the courses.
CONCLUSIONS: This European project for courses in higher education arising from RISE was met with appreciation and challenges from academic institutions. However, due to considerable efforts to introduce the EHM concept, a unique compulsory course for all medical students in the second year of training started in 2023 in all French medical faculties. In 2023, UPRISE was integrated into ENLIGHT, the European University Network to promote equitable quality of Life, sustainability, and Global engagement through Higher education Transformation.

World RugbyTM supports dedicated women\'s welfare, injury surveillance and medical/technical interventions, yet breast health has received limited attention. This article aims to provide insights into breast health issues in rugby, including breast impacts and injuries. We discuss how breast anatomy and position may be problematic in rugby. Breast volume relates to body size, which may be increasing in women\'s rugby, suggesting increased breast surface area and mass, potentially increasing injury risk. Breast health issues in rugby have been reported previously, with 58% of contact footballers (including rugby) experiencing breast injuries. There are damaging effects related to these breast health issues, with breast impacts often causing pain and swelling. Breast impacts may lead to haematomas, cysts and fat necrosis which can calcify over time making them difficult to distinguish from breast carcinoma, causing further investigation and anxiety. In sport, poor bra fit and insufficient support are associated with pain, skin strain and performance decrements. This article reports the potential implications of these breast health issues on performance in rugby. Recent breast-related projects supported by rugby communities may address recommendations identified in the literature for robust breast injury classifications, updated injury surveillance systems and prospective data collection on breast injury prevalence, severity and impact in rugby. These data should inform breast injury care pathways and intervention research, including evidence-based bra design. Understanding the implications of breast impacts on tissue properties, health and wellbeing is vital. Finally, data should inform rugby-specific breast education, raising awareness of this aspect of athlete health.

UNASSIGNED: Large language models (LLMs) have achieved great progress in natural language processing tasks and demonstrated the potential for use in clinical applications. Despite their capabilities, LLMs in the medical domain are prone to generating hallucinations (not fully reliable responses). Hallucinations in LLMs\' responses create substantial risks, potentially threatening patients\' physical safety. Thus, to perceive and prevent this safety risk, it is essential to evaluate LLMs in the medical domain and build a systematic evaluation.
UNASSIGNED: We developed a comprehensive evaluation system, MedGPTEval, composed of criteria, medical data sets in Chinese, and publicly available benchmarks.
UNASSIGNED: First, a set of evaluation criteria was designed based on a comprehensive literature review. Second, existing candidate criteria were optimized by using a Delphi method with 5 experts in medicine and engineering. Third, 3 clinical experts designed medical data sets to interact with LLMs. Finally, benchmarking experiments were conducted on the data sets. The responses generated by chatbots based on LLMs were recorded for blind evaluations by 5 licensed medical experts. The evaluation criteria that were obtained covered medical professional capabilities, social comprehensive capabilities, contextual capabilities, and computational robustness, with 16 detailed indicators. The medical data sets include 27 medical dialogues and 7 case reports in Chinese. Three chatbots were evaluated: ChatGPT by OpenAI; ERNIE Bot by Baidu, Inc; and Doctor PuJiang (Dr PJ) by Shanghai Artificial Intelligence Laboratory.
UNASSIGNED: Dr PJ outperformed ChatGPT and ERNIE Bot in the multiple-turn medical dialogues and case report scenarios. Dr PJ also outperformed ChatGPT in the semantic consistency rate and complete error rate category, indicating better robustness. However, Dr PJ had slightly lower scores in medical professional capabilities compared with ChatGPT in the multiple-turn dialogue scenario.
UNASSIGNED: MedGPTEval provides comprehensive criteria to evaluate chatbots by LLMs in the medical domain, open-source data sets, and benchmarks assessing 3 LLMs. Experimental results demonstrate that Dr PJ outperforms ChatGPT and ERNIE Bot in social and professional contexts. Therefore, such an assessment system can be easily adopted by researchers in this community to augment an open-source data set.

US health care use declined during the initial phase of the COVID-19 pandemic in 2020. Although utilization is known to have recovered in 2021 and 2022, it is unknown how revenue in 2020-22 varied by physician specialty and practice setting. This study linked medical claims from a large national federation of commercial health plans to physician and practice data to estimate pandemic-associated impacts on physician revenue (defined as payments to eligible physicians) by specialty and practice characteristics. Surgical specialties, emergency medicine, and medical subspecialties each experienced a greater than 9 percent adjusted gross revenue decline in 2020 relative to prepandemic baselines. By 2022, pathology and psychiatry revenue experienced robust recovery, whereas surgical and oncology revenue remained at or below baseline. Revenue recovery in 2022 was greater for physicians practicing in hospital-owned practices and in practices participating in accountable care organizations. Pandemic-associated revenue recovery in 2021 and 2022 varied by specialty and practice type. Given that physician financial instability is associated with health care consolidation and leaving practice, policy makers should closely monitor revenue trends among physicians in specialties or practice settings with sustained gross revenue reductions during the pandemic.

This essay questions, with regard to medicine, the idea of progress as technological development by focusing on people rather than things. It analyzes how the predominance of such an idea of progress converts today\'s societies to techno-fetishism that degrades community life and medical practice, contributing to the medicalization of social life. It is argued that the realization of technological potentialities depends on their forms of use; that the main motive of technological development is unlimited profit and that priority developments are those that enhance the social control that maintains the status quo. The intelligence as an intelligence quotient is criticized by proposing it as an attribute of the human being as a whole, manifested in the ways of thinking and proceeding of people in their circumstances, where affectivity and critical thinking are essential for their development; it is emphasized that its antecedent is the harmonic concert of planetary life that contrasts with the prevailing human disharmony. It is proposed that artificial intelligence is the most recent creation of techno-fetishism that deposits vital attributes in technology and that its forms of use will accentuate the degradation of human and planetary life. Another idea of medical progress is proposed, based on forms of organization conducive to the development of inquisitive, critical and collaborative skills that promote permanent improvement, whose distant horizon is dignifying progress: spiritual, intellectual, moral and convivial sublimation of collectivities in harmony with the planetary ecosystem.
Este ensayo cuestiona, a propósito de la medicina, la idea de progreso como desarrollo tecnológico al centrarlo en las personas y no en las cosas. Se analiza cómo el predominio de tal idea de progreso convierte a las sociedades actuales al tecno-fetichismo que degrada la vida comunitaria y la práctica médica contribuyendo a la medicalización de la vida social. Se argumenta que la realización de las potencialidades tecnológicas depende de sus formas de uso, que el móvil principal del desarrollo tecnológico es el lucro sin límites, y que los desarrollos prioritarios son los que potencian el control social que mantiene el statu quo. Se critica la idea de inteligencia como cociente intelectual al proponerla como atributo del ser humano como un todo, manifiesto en las formas pensar y proceder de las personas en sus circunstancias, donde la afectividad y el pensamiento crítico son imprescindibles para su desarrollo. Se destaca que su antecedente es el concierto armónico de la vida planetaria contrastante con la disarmonía humana imperante. Se plantea que la inteligencia artificial es la más reciente hechura del tecno-fetichismo que deposita en la tecnología atributos vitales, y que sus formas de uso acentuarán la degradación de la vida humana y planetaria. Se propone otra idea de progreso médico basado en formas de organización propicias para el desarrollo de aptitudes inquisitivas, críticas y colaborativas que impulsen la superación permanente, cuyo horizonte lejano es el progreso dignificante: sublimación espiritual, intelectual, moral y convivencial de las colectividades en armonía con el ecosistema planetario.

The generative artificial intelligence (AI) model ChatGPT holds transformative prospects in medicine. The development of such models has signaled the beginning of a new era where complex biological data can be made more accessible and interpretable. ChatGPT is a natural language processing tool that can process, interpret, and summarize vast data sets. It can serve as a digital assistant for physicians and researchers, aiding in integrating medical imaging data with other multiomics data and facilitating the understanding of complex biological systems. The physician\'s and AI\'s viewpoints emphasize the value of such AI models in medicine, providing tangible examples of how this could enhance patient care. The editorial also discusses the rise of generative AI, highlighting its substantial impact in democratizing AI applications for modern medicine. While AI may not supersede health care professionals, practitioners incorporating AI into their practices could potentially have a competitive edge.

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