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There are intense discussions about the ethical and societal implications of biomedical engineering, but little data to suggest how scientists think about the ethics of their work. The aim of this study is to describe how scientists frame the ethics of their research, with a focus on the field of molecular systems engineering. Semi-structured qualitative interviews were conducted during 2021–2022, as part of a larger study. This analysis includes a broad question about how participants view ethics as related to their work, with follow up probes about the topics they consider most important. Interviews were transcribed, inductively coded by two researchers to consensus, and analyzed thematically. Twenty-four scientists participated in the study. Interviewees hold positions as professors, principal investigators, and senior staff researchers in universities or research institutes in the United States and Europe. Among those scientists who reported reflecting on ethical considerations in their work, many equated ethics with research ethics topics (e.g., safety, replicability), or with regulation and guidelines. Participants expressed the view that ethical issues are primarily relevant for clinical trials of bioengineered products, or for those working with animal or human subjects. Scientists described their research as "too early" or "not examining anything living" with regard to ethical reflection. Finally, many felt that ethics is seen as territory for experts and therefore beyond scientists' competencies. Molecular systems engineering scientists currently focus on regulatory aspects as the framework for their ethical analyses. They describe using a framework to define when life arises, as a means to determine when further ethical engagement is warranted. Further research is needed to investigate how scientists relate to the ethics of their scientific work, and build consensus around concepts of life, autonomous behavior, and physiological relevance of bioengineered systems. [ABSTRACT FROM AUTHOR]

Over the last decade, bioengineering has seen a sustained growth in scientific publications, patents, and clinical trials. As the field attempts to bridge the gap between discovery and clinical application, a broader societal dialogue is needed to build public trust and address potential ethical, societal, and regulatory challenges. In this essay, we discuss societal aspects linked to the clinical use of biomedical engineering approaches and technologies, with a specific focus on molecular systems engineering. Drawing on data from interviews with 24 scientists, we identified four key aspects for fostering societal support for translational efforts in this domain: (1) effective science communication and internal awareness; (2) open societal dialogue; (3) fair and equitable access to new technologies; and (4) adequate science and technology policies. We conclude that molecular systems engineering would benefit from anticipating future challenges with the view of building a robust bond of trust with lay publics, regulators, and society at large. [ABSTRACT FROM AUTHOR]

Recent research has challenged the notion that dementia is an inevitable outcome of age-related cognitive decline, highlighting the possibility of preventing or delaying onset by addressing specific risk factors. This paradigm shift suggests that prevention through lifestyle modifications and early interventions is possible, potentially averting millions of cases worldwide. This study explores the translation of scientific evidence on dementia prevention into public health policy in Switzerland. Combining the analysis of official policy documents and qualitative interviews with stakeholders, the study explores potential barriers and challenges to implementing preventive intervenions or programs, as well as opportunities for improvement. Results indicate a significant gap in incorporating emerging scientific evidence on dementia prevention into health policies and disseminating information to the public in Switzerland. This study underscores the need for a collaborative and coordinated approach to address these barriers and effectively translate scientific findings into preventive policies and campaigns. These insights can inform policy and targeted programs in Switzerland both at the federal and the cantonal level, eventually serving as a model for other countries seeking to translate evidence-based dementia prevention strategies into public health policies. By bridging the gap between research and policy, significant progress can be made in preventing or delaying the onset of dementia, providing significant benefits to individuals, families, and society. [ABSTRACT FROM AUTHOR]

Drugs addressing unmet medical needs can change the lives of millions. Developing and validating new drugs can, however, take many years. To streamline the assessment of new drugs, regulatory agencies have long established shortened review pathways. Among these programs, Accelerated Approval (AA) has recently come under scrutiny due to the U.S. Food and Drug Administration's decision to authorize Aducanumab, the first Alzheimer's disease drug. This decision attracted fierce criticism due to the allegedly insufficient evidence about the safety and efficacy of the drug. While considerable scholarly attention has been devoted to this case, the ethical aspects of the AA regulatory pathway have so far remained relatively unexplored. In this paper, we set out to fill this gap. We illustrate six conditions that should be met for AA to be ethically acceptable: moral solicitude, evidence, risk mitigation, impartiality, sustainability, and transparency. We discuss such conditions and suggest practical steps to implement them in regulatory and oversight processes. Taken together, our six conditions represent a benchmark for assessing the ethical validity of AA processes and decisions. [ABSTRACT FROM AUTHOR]

This paper describes the results of a multi-country survey of governance approaches for the use of digital contact tracing (DCT) in response to the COVID-19 pandemic. We argue that the countries in our survey represent two distinct models of DCT governance, both of which are flawed. The "data protection model" emphasizes privacy protections at the expense of public health benefit, while the "emergency response model" sacrifices transparency and accountability, prompting concerns about excessive governance surveillance. The ethical and effective use of DCT in the future requires a new governance approach that is better suited to this novel use of mobile phone data to promote public health." [ABSTRACT FROM AUTHOR]

They conclude by highlighting that the reframing of ageing I qua i risk has social and ethical implications, as it is generative of normative notions of what constitutes successful ageing and good citizenship. While philosophical discussions about the nature of human ageing have never been settled, they acquire new significance in the contemporary I milieu i . This becomes especially evident in light of recent discoveries of various levels of senescence underlying the ageing of individual organisms - a phenomenon known as "age mosaicism." This has raised awareness of the dynamic nature of the ageing process, as well as the diverse ways in which ageing affects people differently, because of biological factors as well as cultural and social determinants. [Extracted from the article]

In this paper, I present an emerging explanatory framework about ageing and care. In particular, I focus on how, in contrast to most classical accounts of ageing, biomedicine today construes the ageing process as a modifiable trajectory. This framing turns ageing from a stage of inexorable decline into the focus of preventive strategies, harnessing the functional plasticity of the ageing organism. I illustrate this shift by focusing on studies of the demographic dynamics in human population, observations of ageing as an intraspecifically heterogenous phenotype, and the experimental manipulation of longevity, in both model organisms and humans. I suggest that such an explanatory framework about ageing creates the epistemological conditions for the rise of a peculiar form of prevention that does not aim to address a specific condition. Rather it seeks to stall the age-related accumulation of molecular damage and functional deficits, boosting individual resilience against age-related decline. I call this preventive paradigm “ground-state prevention.” While new, ground-state prevention bears conceptual resemblance to forms of medical wisdom prominent in classic Galenic medicine, as well as in the Renaissance period. [ABSTRACT FROM AUTHOR]

The article presents the discussion on Machine learning (ML) having highly transformative approaches to the automation of numerous clinical tasks. Topics include computer scientists being most concerned with demonstrating the superiority of ML-driven systems at performing classificatory or predictive tasks; and focusing on ensuring the safety and effectiveness of medical devices, software, and drugs before receiving market authorization.

With the birth of genetically engineered twins in November 2018, international debate about human genome editing governance has moved from an emphasis on mutual engagement among multiple stakeholders to a self-regulatory model enacted through high-level expert groups with little or no public input. This article reconstructs this paradigm shift and suggests that inclusive public deliberation should still have a role in public decision making about genome editing. [ABSTRACT FROM AUTHOR]

In this article, the author reports Ethics, Values, and Responsibility in Human Genome Editing. Topics include CRISPR/Cas9 genome editing, an inexpensive and efficient tool to introduce changes in Deoxyribonucleic acid(DNA); include correcting congenital monogenic disorders, targeting disease-causing molecular lesions, and altering multiple genetic loci at the same time; and used to enhance human traits,3 such as resistance to infectious diseases, strength, or cognitive capacity.

The article focuses on the challenges in deploying digital contact tracing (DCT) apps to tackle coronavirus disease 2019. It mentions the number of uncertainties attributed to the general awareness of DCT apps, which include privacy risks, as well as public attitudes toward a potentially pervasive form of digital surveillance. The author suggests the need for policy-makers to set up mechanisms to test effectiveness, oversee the use of DCT apps and also monitor public attitudes.

Effy Vayena and colleagues argue that machine learning in medicine must offer data protection, algorithmic transparency, and accountability to earn the trust of patients and clinicians. [ABSTRACT FROM AUTHOR]

Effy Vayena and colleagues argue that machine learning in medicine must offer data protection, algorithmic transparency, and accountability to earn the trust of patients and clinicians. [ABSTRACT FROM AUTHOR]

Massive amounts of data are collected and stored on a routine basis in virtually all domains of human activities. Such data are potentially useful to biomedicine. Yet, access to data for research purposes is hindered by the fact that different kinds of individual-patient data reside in disparate, unlinked silos. We propose that data cooperatives can promote much needed data aggregation and consequently accelerate research and its clinical translation. Data cooperatives enable direct control over personal data, as well as more democratic governance of data pools. This model can realize a specific kind of data economy whereby citizens and communities are empowered to steer data use according to their motivations, preferences, and concerns. Policy makers can promote this model by recognizing citizens’ rights to access and to obtain a copy of their own data, and by funding distributed data infrastructures piloting new data aggregation models. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

To address the ethical challenges in big data health research we propose the concept of systemic oversight. This approach is based on six defining features (adaptivity, flexibility, monitoring, responsiveness, reflexivity, and inclusiveness) and aims at creating a common ground across the oversight pipeline of biomedical big data research. Current trends towards enhancing granularity of informed consent and specifying legal provisions to address informational privacy and discrimination concerns in data-driven health research are laudable. However, these solutions alone cannot have the desired impact unless oversight activities by different stakeholders acquire a common substantive orientation. [ABSTRACT FROM AUTHOR]

Empirical evidence suggests that while people hold the capacity to control their data in high regard, they increasingly experience a loss of control over their data in the online world. The capacity to exert control over the generation and flow of personal information is a fundamental premise to important values such as autonomy, privacy, and trust. In healthcare and clinical research this capacity is generally achieved indirectly, by agreeing to specific conditions of informational exposure. Such conditions can be openly stated in informed consent documents or be implicit in the norms of confidentiality that govern the relationships of patients and healthcare professionals. However, with medicine becoming a data-intense enterprise, informed consent and medical confidentiality, as mechanisms of control, are put under pressure. In this paper we explore emerging models of informational control in data-intense healthcare and clinical research, which can compensate for the limitations of currently available instruments. More specifically, we discuss three approaches that hold promise in increasing individual control: the emergence of data portability rights as means to control data access, new mechanisms of informed consent as tools to control data use, and finally, new participatory governance schemes that allow individuals to control their data through direct involvement in data governance. We conclude by suggesting that, despite the impression that biomedical big data diminish individual control, the synergistic effect of new data management models can in fact improve it. [ABSTRACT FROM AUTHOR]

With the launch of the Precision Medicine Initiative (PMI) in January 2015, the White House granted a high degree of federal support to an emerging biomedical paradigm. What explains this level of political recognition? Based on literature and policy analysis, we reconstruct the scientific and the legislative paths that led to the political endorsement of precision medicine. First, we describe the proliferation of personalized approaches to therapy ignited by the discovery of hemoprotein cytochrome P450 polymorphism in 1988. Then, we analyze the legislative history of precision medicine, from the unsuccessful introduction of Genomics and Personalized Medicine Acts in the second half of the last decade, to the highly acclaimed PMI. However, scientific progress and political contingency alone do not explain the upheaval of precision medicine as an institutionally supported initiative. On examination, the launch of a Precision Medicine Research Cohort and the incorporation of a participatory ethos into the fabric of the PMI proved to be crucial determinants of the political support for precision medicine. Weaving together the scientific and legislative antecedents of precision medicine, we illuminate how the mutual constitution of science and social order generates political recognition for innovative biomedical paradigms. [ABSTRACT FROM AUTHOR]

The article focuses on the challenges in finding a suitable expression in French to refer to CRISPR-Cas9, referencing the article ""Editing" genes: A case study about how language matters in bioethics" by M. O'Keefe and colleagues within the issue. Topics mentioned include how adopting the English wording would oppose a national language being a civic asset, the principle of dialogic responsibility, and the use of the expression targeted genome engineering to refer to CRISPR-Cas9 in general.

On May 6th 2014, the European Court of Human Rights added yet a new element to the judicial history of stem cells as it ruled in Durisotto v. Italy [appeal n. 62804/13]. The ruling rejected a patient claim to access an unproven cell therapy-an outcome that is certainly to be welcomed. However, this ruling is a missed occasion to clarify and reaffirm some important legal distinctions that could have greatly benefited the whole field of regenerative medicine. We claim that the ethical and political assumptions that sustain the regulation of expanded access programs to new therapies should be carefully scrutinized, with particular attention to the justifications for the risks connected to unconventional therapies. A clear legal definition of what counts as compassionate cure as distinct from unregulated and untested therapies cannot be provided unless those points are previously addressed. [ABSTRACT FROM AUTHOR]

The article talks about informed consent of the participants in medical research and the disclosure of clinical results to the participants. Topics discussed include the field of genomic research, the patients undergoing genome sequencing and seeking information on the incidental findings, and the concept of the disclosure of results being a right of the patients.

Europe is ready to deploy its immense capital of knowledge into the development of effective cell-based therapies and delve into the global race for translating stem cell science into regenerative medicine. But what are the challenges and the emerging issues that lay ahead the realization of Europe's enormous potential in this field? Both researchers and industrial stakeholders tend to impute the slow pace of translation to specific suboptimal features of the regulatory environment in Europe. At the same time, a host of new issues are emerging as testified by a recent public controversy regarding the provision of unproven cell therapy in Italy. We will review this topic and suggest some solutions to foster the responsible development of innovative cell-based therapies in Europe. [ABSTRACT FROM AUTHOR]

What has been called the new mechanistic philosophy conceives of mechanisms as the main providers of biological explanation. We draw on the characterization of the p53 gene in molecular oncology, to show that explaining a biological phenomenon (cancer, in our case) implies instead a dynamic interaction between the mechanistic level—rendered at the appropriate degree of ontological resolution—and far more general explanatory tools that perform a fundamental epistemic role in the provision of biological explanations. We call such tools “explanatory frameworks”. They are called frameworks to stress their higher level of generality with respect to bare mechanisms; on the other hand, they are called explanatory because, as we show in this paper, their importance in explaining biological phenomena is not secondary with respect to mechanisms. We illustrate how explanatory frameworks establish selective and local criteria of causal relevance that drive the search for, characterisation and usage of biological mechanisms. Furthermore, we show that explanatory frameworks allow for changes of scientific perspective on the causal relevance of mechanisms going beyond the account provided by the new mechanistic philosophy. [Copyright &y& Elsevier]

This paper explores the epistemology of extrapolation from model organisms to humans in molecular medicine. We take into account two common views on the issue, the homology view and the disanalogy view. In response to both interpretations, we argue that the foundational basis of extrapolations cannot simply be provided by homology and that relevant disanalogies can, thanks to the techniques of molecular biology, be experimentally controlled and exploited to allow useful and reliable extrapolations. The case of "humanised mice" in the context of cancer stem cell research provides evidence of how animal models can be construed to approximate bona fide causal analogue models of human diseases. To supplement this view we show how the epistemology of model organisms needs to take into account the engineering side of molecular medicine. Model organisms are often manipulated to create analogies or remove disanalogies with the target system. We maintain that highlighting this feature is fundamental to explain what warrants extrapolation in the search for the molecular causes of disease. [ABSTRACT FROM AUTHOR]

In this paper we discuss the conditions for the possession of intentional states (especially beliefs) and for intentional agency. We then explore the implications of an analysis of intentionality in non-human animals for their entitlement to ethical treatment, and review the potential advantages and epistemological difficulties of relying on the scientific study of animal mindedness to draw ethical conclusions. In the end, we argue that ethical debates on the treatment of animals, and in particular considerations about welfare, can benefit considerably from the enterprise of exploring the extent to which non-human animals are minded [ABSTRACT FROM AUTHOR]

A new active substance called "dersimelagon" (MT-7117) is being tested as an alternative treatment option for Erythropoietic protoporphyria (EPP). At the moment, dersimelagon is being tested both in the US and in Europe in a phase III placebo-controlled RCT. However, given the availability of an already approved treatment option for EPP the use of a placebo arm is questionable from an ethics point of view. We analyze the issue and suggest that a noninferiority active-control trial without placebo is an ethically and scientifically more valid design to test the efficacy of dersimelagon as well as other EPP treatments. [ABSTRACT FROM AUTHOR]

The authors discuss the report "Do researchers have an obligation to actively look for genetic incidental findings?" by C. Gliwa and B. E. Berkman from the volume 13, number 2013 issue, which looks at ethical considerations related to the disclosure of secondary research results. It is noted that not all researchers in a project posses the expertise to accurately interpret incidental findings. Particular focus is given to pediatric genomics and the disclosure of autosomal recessive disorders.

The authors discuss the article "The argument from potentiality in the embryo protection debate: Finally 'depotentialized'?" by M. S. Stier and B. Schoene-Seifert from the volume 13 number 1, 2013 issue, with particular focus on the ethics and regulation of human embryonic stem cell (hESC) research. They argue that scientific evidence on cellular reprogramming necessitates changes to hESC research policies based on the potentiality argument (PA) of the moral status of embryos.

The article focuses on the benefits and disadvantages that genetic research participants and the families of genetic research participants could find from having the results of advanced genetic testing disclosed to them. In the article the authors offer their opinions on the moral and issues that are raised with the disclosure of genetic testing results and on several genetic testing programs.

Background: Explainability is one of the most heavily debated topics when it comes to the application of artificial intelligence (AI) in healthcare. Even though AI-driven systems have been shown to outperform humans in certain analytical tasks, the lack of explainability continues to spark criticism. Yet, explainability is not a purely technological issue, instead it invokes a host of medical, legal, ethical, and societal questions that require thorough exploration. This paper provides a comprehensive assessment of the role of explainability in medical AI and makes an ethical evaluation of what explainability means for the adoption of AI-driven tools into clinical practice.Methods: Taking AI-based clinical decision support systems as a case in point, we adopted a multidisciplinary approach to analyze the relevance of explainability for medical AI from the technological, legal, medical, and patient perspectives. Drawing on the findings of this conceptual analysis, we then conducted an ethical assessment using the "Principles of Biomedical Ethics" by Beauchamp and Childress (autonomy, beneficence, nonmaleficence, and justice) as an analytical framework to determine the need for explainability in medical AI.Results: Each of the domains highlights a different set of core considerations and values that are relevant for understanding the role of explainability in clinical practice. From the technological point of view, explainability has to be considered both in terms how it can be achieved and what is beneficial from a development perspective. When looking at the legal perspective we identified informed consent, certification and approval as medical devices, and liability as core touchpoints for explainability. Both the medical and patient perspectives emphasize the importance of considering the interplay between human actors and medical AI. We conclude that omitting explainability in clinical decision support systems poses a threat to core ethical values in medicine and may have detrimental consequences for individual and public health.Conclusions: To ensure that medical AI lives up to its promises, there is a need to sensitize developers, healthcare professionals, and legislators to the challenges and limitations of opaque algorithms in medical AI and to foster multidisciplinary collaboration moving forward. [ABSTRACT FROM AUTHOR]

The concept of “mild behavioral impairment” (MBI) has been recently introduced and tentatively operationalized. The rationale supporting the need of such novel construct is that neuropsychiatric symptoms (NPS), even when they do not configure major psychiatric disorders, may still constitute early manifestations of neurodegenerative diseases, potentially anticipating the onset of dementia. The conception of MBI as a potential pre-dementia phenotype is surely of interest because posing special attention to neuropsychiatric symptoms and their negative implications. Nevertheless, several issues should be carefully considered in the definition of MBI and are discussed in the present Commentary. [ABSTRACT FROM AUTHOR]

Effy Vayena and colleagues argue that machine learning in medicine must offer data protection, algorithmic transparency, and accountability to earn the trust of patients and clinicians. [ABSTRACT FROM AUTHOR]

This study reports on 13 semistructured in-depth interviews to qualitatively explore the experiences of individuals who publicly shared their direct-to-consumer genetic testing results on the platform openSNP. In particular, we focused on interviewees' understanding of privacy. Participants reported that the likelihood and the magnitude of privacy harms depend on gender, ethnicity, sexual orientation, the stigma associated with certain clinical conditions, the existence of adequate legislation, and the nature of national health care systems. Some participants expressed the view that those who enjoy higher socioeconomic status or are better protected by their country's legislation have a responsibility to share their genetic data. Our study shows that people who share their genetic data publicly online—far from being insensitive to privacy risks—have a complex understanding of the social, relational, and contextual nature of genetic privacy. [ABSTRACT FROM AUTHOR]

We explored the characteristics and motivations of people who, having obtained their genetic or genomic data from Direct-To-Consumer genetic testing (DTC-GT) companies, voluntarily decide to share them on the publicly accessible web platform openSNP. The study is the first attempt to describe open data sharing activities undertaken by individuals without institutional oversight. In the paper we provide a detailed overview of the distribution of the demographic characteristics and motivations of people engaged in genetic or genomic open data sharing. The geographical distribution of the respondents showed the USA as dominant. There was no significant gender divide, the age distribution was broad, educational background varied and respondents with and without children were equally represented. Health, even though prominent, was not the respondents’ primary or only motivation to be tested. As to their motivations to openly share their data, 86.05% indicated wanting to learn about themselves as relevant, followed by contributing to the advancement of medical research (80.30%), improving the predictability of genetic testing (76.02%) and considering it fun to explore genotype and phenotype data (75.51%). Whereas most respondents were well aware of the privacy risks of their involvement in open genetic data sharing and considered the possibility of direct, personal repercussions troubling, they estimated the risk of this happening to be negligible. Our findings highlight the diversity of DTC-GT consumers who decide to openly share their data. Instead of focusing exclusively on health-related aspects of genetic testing and data sharing, our study emphasizes the importance of taking into account benefits and risks that stretch beyond the health spectrum. Our results thus lend further support to the call for a broader and multi-faceted conceptualization of genomic utility. [ABSTRACT FROM AUTHOR]

Introduction: Artificial intelligence (AI) has the potential to transform clinical decision-making as we know it. Powered by sophisticated machine learning algorithms, clinical decision support systems (CDSS) can generate unprecedented amounts of predictive information about individuals' health. Yet, despite the potential of these systems to promote proactive decision-making and improve health outcomes, their utility and impact remain poorly understood due to their still rare application in clinical practice. Taking the example of AI-powered CDSS in stroke medicine as a case in point, this paper provides a nuanced account of stroke survivors', family members', and healthcare professionals' expectations and attitudes towards medical AI. Methods: We followed a qualitative research design informed by the sociology of expectations, which recognizes the generative role of individuals' expectations in shaping scientific and technological change. Semi-structured interviews were conducted with stroke survivors, family members, and healthcare professionals specialized in stroke based in Germany and Switzerland. Data was analyzed using a combination of inductive and deductive thematic analysis. Results: Based on the participants' deliberations, we identified four presumed roles that medical AI could play in stroke medicine, including an administrative, assistive, advisory, and autonomous role AI. While most participants held positive attitudes towards medical AI and its potential to increase accuracy, speed, and efficiency in medical decision making, they also cautioned that it is not a stand-alone solution and may even lead to new problems. Participants particularly emphasized the importance of relational aspects and raised questions regarding the impact of AI on roles and responsibilities and patients' rights to information and decision-making. These findings shed light on the potential impact of medical AI on professional identities, role perceptions, and the doctor-patient relationship. Conclusion: Our findings highlight the need for a more differentiated approach to identifying and tackling pertinent ethical and legal issues in the context of medical AI. We advocate for stakeholder and public involvement in the development of AI and AI governance to ensure that medical AI offers solutions to the most pressing challenges patients and clinicians face in clinical care. [ABSTRACT FROM AUTHOR]

The expression "public opinion" has long been part of common parlance. However, its value as a scientific measure has been the topic of abundant academic debates over the past several decades. Such debates have produced more variety and contestations rather than consensus on the very definition of public opinion, let alone on how to measure it. This study reports on the usefulness of web-based big data digital network analytics in deciphering the distributed meanings and sense making related to controversial biotechnology applications. Using stem cell therapies as a case study, we argue that such digital network analysis can complement the traditional opinion polls while avoiding the sampling bias that is typical of opinion polls. Although the polls cannot account for the opinion dynamics, combining them with web-based big data analysis can shed light on three dimensions of public opinion essential for sense making: counts or volume of opinion data, content, and movement of opinions. This approach is particularly promising in the case of ongoing scientific controversies that increasingly overflow into the public sphere morphing into public political debates. In particular, our study focuses as a case study on public controversies over the clinical provision of stem cell therapies. Using web entities specifically addressing stem cell issues, including their dynamic aggregation, the internal architecture of the web corpus we report in this study brings the third dimension of public opinion (movement) into sharper focus. Notably, the corpus of stem cell networks through web connectivity presents hot spots of distributed meaning. Large-scale surveys conducted on these issues, such as the Eurobarometer of Biotechnology, reveal that European citizens only accept research on stem cells if they are highly regulated, while the stem cell digital network analysis presented in this study suggests that distributed meaning is promise centeredness. Although major scientific journals and companies tend to structure public opinion networks, our finding of promise centeredness as a key ingredient of distributed meaning and sense making is consistent with therapeutic tourism that remains as an important facet of the stem cell community despite the lack of material standards. This new approach to digital network analysis has crosscutting corollaries for rethinking the notion of public opinion, be it in electoral preferences or as we discuss in this study, for new ways to measure, monitor, and democratically govern emerging technologies. [ABSTRACT FROM AUTHOR]

Highlights: [•] Familial Alzheimer's disease (FAD) is attracting a growing scientific interest. [•] PSEN2 mutations represent the less common cause of FAD. [•] Mutations of the PSEN2 gene are mostly associated to a “typical” AD phenotype. [•] Improved phenotyping of FAD cases may have a relevant impact. [Copyright &y& Elsevier]

Transcription factor (TF)--induced reprogramming of somatic cells into induced pluripotent stem cells (iPSC) is associated with genome-wide changes in chromatin modifications. Polycomb-mediated histone H3 lysine-27 trimethylation (H3K27me3) has been proposed as a defining mark that distinguishes the somatic from the iPSC epigenome. Here, we dissected the functional role of H3K27me3 in TF--induced reprogramming through the inactivation of the H3K27 methylase EZH2 at the onset of reprogramming. Our results demonstrate that surprisingly the establishment of functional iPSC proceeds despite global loss of H3K27me3. iPSC lacking EZH2 efficiently silenced the somatic transcriptome and differentiated into tissues derived from the three germ layers. Remarkably, the genome-wide analysis of H3K27me3 in Ezh2 mutant iPSC cells revealed the retention of this mark on a highly selected group of Polycomb targets enriched for developmental regulators controlling the expression of lineage specific genes. Erasure of H3K27me3 from these targets led to a striking impairment in TF--induced reprogramming. These results indicate that PRC2-mediated H3K27 trimethylation is required on a highly selective core of Polycomb targets whose repression enables TF--dependent cell reprogramming. [ABSTRACT FROM AUTHOR]