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The chapter analyses the re-emergence of gene editing as an object of policy attention at the European Union (EU) level. Editing the genome of plants and/or animals has been a rather controversial component of all EU policies on agricultural biotechnology since the late 1980s. The chapter examines in detail the various initiatives that have been assumed for the regulation of gene editing at the EU level. Since the first political and legislative attempts, the field has been revolutionized with the development of the CRISPR-Cas9 system, which is comparatively much easier to design, produce, and use. Beyond the pure, safety-driven scientific questions, gene editing, in its contemporary form, raises a series of ethical and regulatory questions that are discussed in the context of the legal options and competences of the EU legislators. Special attention is paid to questions about the legal status of gene editing in Europe and the adequacy of the current GMO framework to deal with all the challenges associated with the latest scientific developments in the field of gene editing with a special focus on gene drive. Given the ongoing discussions regarding the ethical tenets of gene editing, the chapter investigates the question on whether there is a need to shape an EU-wide “intervention” that will address the complex and dynamic socio-ethical challenges of gene editing and puts forward a series of proposals for the framing of an inclusive framework that will be based on the need to re-enforce public trust in the EU governance of emerging technologies.

For more than 20 years, genome editing has been one of the numerous technologies developed for the study and manipulation of the genome. However, since the relatively recent appearance of the so-called precision approaches, and especially through the “CRISPR revolution,” the modification of the genome of any living beings on our planet has become possible, despite recent results showing some unexpected and undesirable effects of this technology. The objective of this chapter is to illustrate how a mobilization of the scientific community through the setting-up of an association should allow a responsible and ethical use of these technologies with considerable impacts for our society.

Ovarian cancer (OC) is the most common type of gynecologic cancer in the world with a high rate of mortality. Due to manifestation of generic symptoms and absence of specific biomarkers, OC is usually diagnosed at a late stage. Machine learning models can be employed to predict driver genes implicated in causative mutations.

In the present study, a comprehensive next generation sequencing (NGS) analysis of whole exome sequences of 47 OC patients was carried out to identify clinically significant mutations. Nine functional features of 708 mutations identified were input into a machine learning classification model by employing the eXtreme Gradient Boosting (XGBoost) classifier method for prediction of OC driver genes.

The XGBoost classifier model yielded a classification accuracy of 0.946, which was superior to that obtained by other classifiers such as decision tree, Naive Bayes, random forest and support vector machine. Further, an interaction network was generated to identify and establish correlations with cancer-associated pathways and gene ontology data.

The final results revealed 12 putative candidate cancer driver genes, namely LAMA3, LAMC3, COL6A1, COL5A1, COL2A1, UGT1A1, BDNF, ANK1, WNT10A, FZD4, PLEKHG5 and CYP2C9, that may have implications in clinical diagnosis.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is difficult to diagnose accurately due to its heterogeneous clinical manifestations. Comprehensive models combining different big data approaches (e.g. neuroimaging, genetics, eye tracking, etc.) may offer the opportunity to characterize ASD from multiple distinct perspectives. This paper aims to provide an overview of a novel diagnostic approach for ASD classification and stratification based on these big data approaches.

Multiple types of data were collected and recorded for three consecutive years, including clinical assessment, neuroimaging, gene mutation and expression and response signal data. The authors propose to establish a classification model for predicting ASD clinical diagnostic status by integrating the various data types. Furthermore, the authors suggest a data-driven approach to stratify ASD into subtypes based on genetic and genomic data.

By utilizing complementary information from different types of ASD patient data, the proposed integration model has the potential to achieve better prediction performance than models focusing on only one data type. The use of unsupervised clustering for the gene-based data-driven stratification will enable identification of more homogeneous subtypes. The authors anticipate that such stratification will facilitate a more consistent and personalized ASD diagnostic tool.

This study aims to utilize a more comprehensive investigation of ASD-related data types than prior investigations, including proposing longitudinal data collection and a storage scheme covering diverse populations. Furthermore, this study offers two novel diagnostic models that focus on case-control status prediction and ASD subtype stratification, which have been under-explored in the prior literature.

Gliomas are common intracranial tumors with the characteristic of diffuse and invasive growth. The prognosis is poor, and the recurrence rate and mortality are higher. With the development of big data technology, many methods such as natural language processing, computer vision and image processing have been deeply applied in the medical field. This can help clinicians to provide personalized and precise diagnosis and therapeutic schedule for patients with different type of gliomas to achieve the best therapeutic effect. The purpose of this paper is to summarize and extract useful information from published research results by conducting a secondary analysis of the literature.

The PubMed and China National Knowledge Infrastructure (CNKI) literature database were used to retrieve published Chinese and English research papers about human gliomas. Comprehensive analysis was applied to conduct this research. The factors affecting survival and prognosis were screened and analyzed respectively in this paper, and different methods for multidimensional data of patients were discussed.

This paper identified biomarkers and therapeutic modalities associated with prognosis for different grade of gliomas. This paper investigated the relationship among these clinical prognostic factors and different histopathologic tying and grade of gliomas by comprehensive analysis. This paper summarizes the research progress of biomarker in medical imaging and genomics of gliomas to improve prognosis and the current status of treatment in China.

Combined with multimodal data such as genomics data, medical image data and clinical information data, this paper comprehensively analyzed the prognostic factors of glioma and provided guidance and evidence for rational treatment planning and improvement of clinical treatment prognosis.

The purpose of this paper is to examine the potential of agri-biotech to play a role in meeting the world’s food, feed, fiber and fuel needs. Using case studies, policy developments in the key Asian countries of China, India and Japan are also scrutinized to determine the extent to which they enable or obstruct biotech’s potential.

The authors first examine some key challenges facing the agriculture and agri-food sector and the potential role biotech can play in addressing them. These challenges include feeding the world’s growing population, improving nutrition worldwide, dealing with allergen risks, reducing nutrient and chemical loading in watersheds, addressing water scarcity issues, and reducing waste in the food system. The authors then turn their attention to the agri-biotech systems in three Asian giants, including China’s centralized governance approach, India’s central-local policy and regulations, and Japan’s pragmatic and evidence-based regulatory framework.

Each nation has evolved its own system of governance based on the different challenges facing the society, the recognized potential of different biotech interventions, and citizens’ collective perceptions regarding both the potential and the risks that biotech innovations embody. Systems that are less evidence-based appear to be more discretionary and therefore are less predictable in their outcomes. This increases risks to prospective exporting firms and importing firms, driving up system costs and effectively serving as barriers to entry and to trade. It also dampens and distorts entrepreneurial and innovation incentives.

From the review and observations the authors then discuss ways and means of establishing priorities through a risk assessment framework in which key risks are enumerated and assessed in terms of their likelihoods and their conceivable consequences. Such an approach would allow challenges to be met with a degree of foresight and adaptability.

The sometimes disjointed, sometimes strategic use of biotech regulations have fragmented markets and created fiefdoms which undermine the potential of novel technologies to address the challenges facing society.

For illustrative purposes, the authors touch on land and water governance, regulatory and institutional bottlenecks and reforms and the potential for agri-biotech to play an elevated role if vested interests and obstructions can be overcome.

This study draws on research and literature from several disciplines. It also includes discussions relating to bureaucratic and administrative behavior which erodes the extent to which markets can be contested. This results in balkanized markets and non-cooperative behavior that undermines and distorts incentives for entrepreneurial effort and innovation. That such behavior takes place in markets and disciplines that are fundamental to assuring food security, nutrition and health, as well as good governance of scarce water and land resources is of considerable concern.

Looks at memetics, a new science of memes (a unit of cultural material propagated by an imitation process). Examines its origins and attempts to show its significance for the business audience in relation to understanding customer behaviour. Concludes that memetics is still in its infancy and, because of this, it still has philosophical and methodological issues that need to be addressed before it can be considered to be a new paradigm for understanding customer behaviour.

This study aims to study the distribution characteristics of antibiotic resistance in direct-eating food and analysis of Citrobacter freundii genome and pathogenicity. Residual antibiotics and antibiotic resistance genes (ARGs) in the environment severely threaten human health and the ecological environment. The diseases caused by foodborne pathogenic bacteria are increasing daily, and the enhancement of antibiotic resistance of pathogenic bacteria poses many difficulties in the treatment of disease.

In this study, six fresh fruits and vegetable samples were selected for isolation and identification of culturable bacteria and analysis of antibiotic resistance. The whole genome of Citrobacter freundii isolated from cucumber was sequenced and analyzed by Oxford Nanopore sequencing.

The results show that 270 strains of bacteria were identified in 6 samples. From 12 samples of direct food, 2 kinds of probiotics and 10 kinds of opportunistic pathogens were screened. The proportion of Citrobacter freundii screened from cucumber was significantly higher than that from other samples, and it showed resistance to a variety of antibiotics. Whole genome sequencing showed that Citrobacter freundii was composed of a circular chromosome containing signal peptides, transmembrane proteins and transporters that could induce antibiotic efflux, indicating that Citrobacter freundii had strong adaptability to the environment. The detection of genes encoding carbohydrate active enzymes is more beneficial to the growth and reproduction of Citrobacter freundii in crops. A total of 29 kinds of ARGs were detected in Citrobacter freundii, mainly conferring resistance to fluoroquinolones, aminoglycosides, carbapenem, cephalosporins and macrolides. The main mechanisms are the change in antibiotic targets and efflux pumps, the change in cell permeability and the inactivation of antibiotics and the detection of virulence factors and ARGs, further indicating the serious risk to human health.

The detection of genomic islands and prophages increases the risk of horizontal transfer of virulence factors and ARGs, which spreads the drug resistance of bacteria and pathogenic bacteria more widely.

Scientists' perceptions of societal needs and priorities will shape the innovation trajectories of synthetic biology (SB). In turn, these will be shaped by the funding and regulatory environments in which their research is conducted. This study intends to investigate scientists' perspectives on co-innovation with the public regarding implementation of pathways associated with SB including its agrifood applications.

Semi-structured interviews were conducted with Chinese and EU scientists (N = 9 and 13, respectively). Six prominent themes emerged from the data based on thematic analysis method.

Both Chinese and EU scientists regarded SB as being high-benefit, low-risk and ethically acceptable, and predicted its rejection by the general public and attributed this to the public's knowledge deficit and irrationality. They endorsed the deficit model of science communication, independent of greater emphasis on responsible research and innovation (RRI) in EU research projects. The findings raised concerns that public fears might intensify once they have learned about scientists' biased risk perceptions of SB; this calls for better involvement of broader stakeholders.

As the sample size is relatively small, the generalisation of research findings needs to be cautious. However, the authors believe the findings have provided some insights that support increasingly RRI associated with SB.

This study has presented scientists' misunderstandings of societal responses to SB and science communication. It has also provided information to understand how SB-related issues and agenda can be better shaped in future.