P4 medicine: how systems medicine will transform the healthcare sector and society

Personalized Lifestyle Intervention and Functional Evaluation Health Outcomes SurvEy: Presentation of the LIFEHOUSE Study Using N-of-One Tent-Umbrella-Bucket Design

The working definition of health is often the simple absence of diagnosed disease. This common standard is limiting given that changes in functional health status represent early warning signs of impending health declines. Longitudinal assessment of functional health status may foster prevention of disease occurrence and modify disease progression. The LIFEHOUSE (Lifestyle Intervention and Functional Evaluation-Health Outcomes SurvEy) longitudinal research project explores the impact of personalized lifestyle medicine approaches on functional health determinants. Utilizing an adaptive tent-umbrella-bucket design, the LIFEHOUSE study follows the functional health outcomes of adult participants recruited from a self-insured employee population. Participants were each allocated to the tent of an all-inclusive N-of-one case series. After assessing medical history, nutritional physical exam, baseline functional status (utilizing validated tools to measure metabolic, physical, cognitive, emotional and behavioral functional capacity), serum biomarkers, and genomic and microbiome markers, participants were assigned to applicable umbrellas and buckets. Personalized health programs were developed and implemented using systems biology formalism and functional medicine clinical approaches. The comprehensive database (currently 369 analyzable participants) will yield novel interdisciplinary big-health data and facilitate topological analyses focusing on the interactome among each participant's genomics, microbiome, diet, lifestyle and environment.

Smartphone-based digital phenotyping for dry eye toward P4 medicine: a crowdsourced cross-sectional study

Multidimensional integrative data analysis of digital phenotyping is crucial for elucidating the pathologies of multifactorial and heterogeneous diseases, such as the dry eye (DE). This crowdsourced cross-sectional study explored a novel smartphone-based digital phenotyping strategy to stratify and visualize the heterogenous DE symptoms into distinct subgroups. Multidimensional integrative data were collected from 3,593 participants between November 2016 and September 2019. Dimension reduction via Uniform Manifold Approximation and Projection stratified the collected data into seven clusters of symptomatic DE. Symptom profiles and risk factors in each cluster were identified by hierarchical heatmaps and multivariate logistic regressions. Stratified DE subgroups were visualized by chord diagrams, co-occurrence networks, and Circos plot analyses to improve interpretability. Maximum blink interval was reduced in clusters 1, 2, and 5 compared to non-symptomatic DE. Clusters 1 and 5 had severe DE symptoms. A data-driven multidimensional analysis with digital phenotyping may establish predictive, preventive, personalized, and participatory medicine.

Enabling patients in effective self-management of breathlessness in lung cancer: the neglected pillar of personalized medicine

Globally, engagement of patients in the self management of disease and symptom problems has become a health policy priority to improve health outcomes in cancer. Unfortunately, little attention has been focused on the provision of self-management support (SMS)in cancer and specifically for complex cancer symptoms such as breathlessness. Current management of breathlessness, which includes treatment of underlying disease, pharmacological agents to address comorbidities and opiates and anxiolytics to change perception and reduce the sense of breathing effort, is inadequate. In this perspective paper, we review the rationale and evidence for a structured, multicomponent SMS program in breathlessness including four components: breathing retraining, enhancing positive coping skills, optimizing exertional capacity and reducing symptom burden and health risks. The integration of SMS in routine lung cancer care is essential to improve breathlessness, reduce psychological distress, suffering and improve quality of life.

Feasibility of a Sensor-Controlled Digital Game for Heart Failure Self-management: Randomized Controlled Trial

BACKGROUND

Poor self-management of heart failure (HF) contributes to devastating health consequences. Our innovative sensor-controlled digital game (SCDG) integrates data from sensors to trigger game rewards, progress, and feedback based on the real-time behaviors of individuals with HF.

OBJECTIVE

The aim of this study is to compare daily weight monitoring and physical activity behavior adherence by older adults using an SCDG intervention versus a sensors-only intervention in a feasibility randomized controlled trial.

METHODS

English-speaking adults with HF aged 55 years or older who owned a smartphone and could walk unassisted were recruited from Texas and Oklahoma from November 2019 to August 2020. Both groups were given activity trackers and smart weighing scales to track behaviors for 12 weeks. The feasibility outcomes of recruitment, retention, intervention engagement, and satisfaction were assessed. In addition to daily weight monitoring and physical activity adherence, the participants' knowledge, functional status, quality of life, self-reported HF behaviors, motivation to engage in behaviors, and HF-related hospitalization were also compared between the groups at baseline and at 6, 12, and 24 weeks.

RESULTS

A total of 38 participants with HF-intervention group (IG; 19/38, 50%) and control group (CG; 19/38, 50%)-were enrolled in the study. Of the 38 participants, 18 (47%) were women, 18 (47%) were aged 65 years or older, 21 (55%) had been hospitalized with HF in the past 6 months, and 29 (76%) were White. Furthermore, of these 38 participants, 31 (82%)-IG (15/19, 79%) and CG (16/19, 84%)-had both weight monitoring and physical activity data at the end of 12 weeks, and 27 (71%)-IG (14/19, 74%) and CG (13/19, 68%)-participated in follow-up assessments at 24 weeks. For the IG participants who installed the SCDG app (15/19, 79%), the number of days each player opened the game app was strongly associated with the number of days the player engaged in weight monitoring (r=0.72; P=.04) and the number of days with physical activity step data (r=0.9; P<.001). The IG participants who completed the satisfaction survey (13/19, 68%) reported that the SCDG was easy to use. Trends of improvement in daily weight monitoring and physical activity in the IG, as well as within-group improvements in HF functional status, quality of life, knowledge, self-efficacy, and HF hospitalization in both groups, were observed in this feasibility trial.

CONCLUSIONS

Playing an SCDG on smartphones was feasible and acceptable for older adults with HF for motivating daily weight monitoring and physical activity. A larger efficacy trial of the SCDG intervention will be needed to validate trends of improvement in daily weight monitoring and physical activity behaviors.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03947983; https://clinicaltrials.gov/ct2/show/NCT03947983.

Naturalistic smartphone keyboard typing reflects processing speed and executive function

OBJECTIVE

The increase in smartphone usage has enabled the possibility of more accessible ways to conduct neuropsychological evaluations. The objective of this study was to determine the feasibility of using smartphone typing dynamics with mood scores to supplement cognitive assessment through trail making tests.

METHODS

Using a custom-built keyboard, naturalistic keypress dynamics were unobtrusively recorded in individuals with bipolar disorder (n = 11) and nonbipolar controls (n = 8) on an Android smartphone. Keypresses were matched to digital trail making tests part B (dTMT-B) administered daily in two periods and weekly mood assessments. Following comparison of dTMT-Bs to the pencil-and-paper equivalent, longitudinal mixed-effects models were used to analyze daily dTMT-B performance as a function of typing and mood.

RESULTS

Comparison of the first dTMT-B to paper TMT-B showed adequate reliability (intraclass correlations = 0.74). In our model, we observed that participants who typed slower took longer to complete dTMT-B (b = 0.189, p < .001). This trend was also seen in individual fluctuations in typing speed and dTMT-B performance (b = 0.032, p = .004). Moreover, participants who were more depressed completed the dTMT-B slower than less depressed participants (b = 0.189, p < .001). A practice effect was observed for the dTMT-Bs.

CONCLUSION

Typing speed in combination with depression scores has the potential to infer aspects of cognition (visual attention, processing speed, and task switching) in people's natural environment to complement formal in-person neuropsychological assessments that commonly include the trail making test.

Patent Landscape of Automated Systems for Personalized Health Management (ASHM): Features, Shortcomings, and Implications for Developing an Optimal ASHM

The current struggle of national health care systems against global epidemic of non-communicable diseases (NCD) is both clinically ineffective and cost ineffective. On the other hand, rapid development of systems biology, P4 medicine and new digital and communication technologies are good prerequisites for creating an affordable and scalable automated system for personalized health management (ASHM). The current practice of ASHM is better represented in patent literature (36 relevant documents found in Google Patents and USPTO) than in scientific papers (17 documents found in PubMed and Google Scholar). However, only a small fraction of publications disclose a complete self-sufficient system. Problems that authors of ASHM aim to address, methodological approaches, and the most important technical solutions are reviewed and discussed along with shortcomings and limitations. Technical solutions for ASHM currently commercialized or described in literature generally fail to enable practicable, scalable and affordable automated and individualized screening, monitoring, prevention and correction of human health conditions. They also fail to provide a decision support system to patients that would help effectively prevent major NCD and their complications, be accessible and cost effective, consider individual lifestyle factors and involve patients in management of their individual health. Based on analysis of the literature, models of health and care, we propose conceptual framework for developing an ASHM that would be free from the mentioned problems.

A Vision of Future Healthcare: Potential Opportunities and Risks of Systems Medicine from a Citizen and Patient Perspective-Results of a Qualitative Study

Advances in (bio)medicine and technological innovations make it possible to combine high-dimensional, heterogeneous health data to better understand causes of diseases and make them usable for predictive, preventive, and precision medicine. This study aimed to determine views on and expectations of “systems medicine” from the perspective of citizens and patients in six focus group interviews, all transcribed verbatim and content analyzed. A future vision of the use of systems medicine in healthcare served as a stimulus for the discussion. The results show that although certain aspects of systems medicine were seen positive (e.g., use of smart technology, digitalization, and networking in healthcare), the perceived risks dominated. The high degree of technification was perceived as emotionally burdensome (e.g., reduction of people to their data, loss of control, dehumanization). The risk-benefit balance for the use of risk-prediction models for disease events and trajectories was rated as rather negative. There were normative and ethical concerns about unwanted data use, discrimination, and restriction of fundamental rights. These concerns and needs of citizens and patients must be addressed in policy frameworks and health policy implementation strategies to reduce negative emotions and attitudes toward systems medicine and to take advantage of its opportunities.

Towards Building a Quantitative Proteomics Toolbox in Precision Medicine: A Mini-Review

Precision medicine as a framework for disease diagnosis, treatment, and prevention at the molecular level has entered clinical practice. From the start, genetics has been an indispensable tool to understand and stratify the biology of chronic and complex diseases in precision medicine. However, with the advances in biomedical and omics technologies, quantitative proteomics is emerging as a powerful technology complementing genetics. Quantitative proteomics provide insight about the dynamic behaviour of proteins as they represent intermediate phenotypes. They provide direct biological insights into physiological patterns, while genetics accounting for baseline characteristics. Additionally, it opens a wide range of applications in clinical diagnostics, treatment stratification, and drug discovery. In this mini-review, we discuss the current status of quantitative proteomics in precision medicine including the available technologies and common methods to analyze quantitative proteomics data. Furthermore, we highlight the current challenges to put quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data with genomics data for future applications in precision medicine.

Disruptive innovations in the clinical laboratory: catching the wave of precision diagnostics

Disruptive innovation is an invention that disrupts an existing market and creates a new one by providing a different set of values, which ultimately overtakes the existing market. Typically, when disruptive innovations are introduced, their performance is initially less than existing standard technologies, but because of their ability to bring the cost down, and with gradual improvement, they end up replacing established service standards.Disruptive technologies have their fingerprints in health care. Pathology and laboratory medicine are fertile soils for disruptive innovations because they are heavily reliant on technology. Disruptive innovations have resulted in a revolution of our diagnostic ability and will take laboratory medicine to the next level of patient care. There are several examples of disruptive innovations in the clinical laboratory. Digitizing pathology practice is an example of disruptive technology, with many advantages and an extended scope of applications. Next-generation sequencing can be disruptive in two ways. The first is by replacing an array of laboratory tests, which each requires expensive and specialized instruments and expertise, with a single cost-effective technology. The second is by disrupting the current paradigm of the clinical laboratory as a diagnostic service by taking it into a new era of preventive or primary care pathology. Other disruptive innovations include the use of dry chemistry reagents in chemistry analyzers and also point of care testing. The use of artificial intelligence is another promising disruptive innovation that can transform the future of pathology and laboratory medicine. Another emerging disruptive concept is the integration of two fields of medicine to create an interrelated discipline such as "histogenomics and radiohistomics." Another recent disruptive innovation in laboratory medicine is the use of social media in clinical practice, education, and publication.There are multiple reasons to encourage disruptive innovations in the clinical laboratory, including the escalating cost of health care, the need for better accessibility of diagnostic care, and the increased demand on the laboratory in the era of precision diagnostics. There are, however, a number of challenges that need to be overcome such as the significant resistance to disruptive innovations by current technology providers and governmental regulatory bodies. The hesitance from health care providers and insurance companies must also be addressed.Adoption of disruptive innovations requires a multifaceted approach that involves orchestrated solutions to key aspects of the process, including creating successful business models, multidisciplinary collaborations, and innovative accreditation and regulatory oversight. It also must be coupled with successful commercialization plans and modernization of health care structure. Fostering a culture of disruptive innovation requires establishing unique collaborative models between academia and industry. It also requires uncovering new sources of unconventional funding that are open to high-risk high-reward projects. It should also be matched with innovative thinking, including new approaches for delivery of care and identifying novel cohorts of patients who can benefit from disruptive technology.

Quality of a Supporting Mobile App for Rheumatic Patients: Patient-Based Assessment Using the User Version of the Mobile Application Scale (uMARS)

Introduction: Mobile applications promise to improve current health care. However, current mobile app quality ratings are mostly physician-based. The aim of this study was (1) to assess the quality of the self-management app Rheuma Auszeit using the validated uMARS (User Version of the Mobile App Rating Scale) app quality assessment tool and (2) to evaluate the association between uMARS scores and patients' characteristics. Materials and Methods: Consecutive patients with rheumatoid arthritis, psoriatic arthritis and spondyloarthritis were seen at the rheumatology clinic at university hospital Erlangen, Germany. They were asked to test Rheuma Auszeit, evaluate its quality using uMARS and complete a paper-based survey evaluating the individual preferences, attitudes and ehealth literacy. The association between uMARS scores and patients' characteristics was further explored. Results: Between December 2018 and January 2019, a total of 126 patients evaluated Rheuma Auszeit using uMARS and filled out the paper-based survey. The median uMARS score was 3.9, IQR 0.7. Functionality was the domain with the highest rating (median 4.8, IQR 0.8), followed by aesthetics (median 4.0, IQR 0.7), information (median 3.5, IQR 0.8), and engagement (median 3.2, IQR 1.0). Subjective quality was average (median 3.0, IQR 1.0). The lowest scoring individual item was customization with a median of 2.5/5. Lower functionality scores were reported among older female rheumatic patients (P < 0.004). Older male rheumatic patients reported a higher subjective quality score (P < 0.024). Perceived disease activity and disease duration did not significantly correlate with any uMARS subdomain scores. eHealth literacy significantly correlated with functionality uMARS subdomain ratings (Rho = 0.18; P < 0.042). Preferred time of app usage significantly correlated with engagement (Rho = 0.20; P < 0.024), functionality (Rho = 0.19; P < 0.029), total uMARS score (Rho = 0.21; P < 0.017) and subjective quality score (Rho = 0.21; P < 0.017). The vast majority of rheumatic patients would consider recommending Rheuma Auszeit to other patients (117/126; 92.9%). Conclusion: Rheuma Auszeit was well-accepted by German patients suffering from rheumatoid arthritis, psoriatic arthritis and ankylosing spondyloarthritis. Lacking customization could lead to low app compliance and should be improved. Lower functionality scores among older female rheumatic patients highlight the need for patient education. The study underlines the potential and feasibility of therapeutic complementary digital solutions in rheumatology.

Healthy Ageing and Vaccines: Application of the P4 Medicine Concept to Immunizations

In today's tormented world, it appears useful to take advantage of communication channels to promote life-course immunization and affirm its major role in healthy ageing. Instead of developing the argument of chronological age, we demonstrate the life-course principle here based on the P4 medicine concept. Are vaccines "preventive, personalized, predictive, and participatory?" Based on detailed analysis of research findings, we successively demonstrate the seminal role of vaccines on preventable infectious diseases, post-sepsis functional decline, non-communicable diseases (cardio-neuro-vascular, respiratory, and renal diseases), community protection, antimicrobial resistance, and perhaps even old-age dementia. Healthy ageing and the promotion of immunization are closely dependent on health literacy and provision of information by skilled health-care professionals. However, personal autonomy and individual freedom are influenced by psycho-cognitive hurdles (cultural approaches, beliefs, emotions, and behaviours), the opinions of the public/family/friends, and the increasing role of social media, which challenges scientific evidence. A similar phenomenon exists when dealing with the issue of healthy ageing, whose success depends greatly on life-course immunization.

Data Dentistry: How Data Are Changing Clinical Care and Research

Data are a key resource for modern societies and expected to improve quality, accessibility, affordability, safety, and equity of health care. Dental care and research are currently transforming into what we term data dentistry, with 3 main applications: 1) medical data analysis uses deep learning, allowing one to master unprecedented amounts of data (language, speech, imagery) and put them to productive use. 2) Data-enriched clinical care integrates data from individual (e.g., demographic, social, clinical and omics data, consumer data), setting (e.g., geospatial, environmental, provider-related data), and systems level (payer or regulatory data to characterize input, throughput, output, and outcomes of health care) to provide a comprehensive and continuous real-time assessment of biologic perturbations, individual behaviors, and context. Such care may contribute to a deeper understanding of health and disease and a more precise, personalized, predictive, and preventive care. 3) Data for research include open research data and data sharing, allowing one to appraise, benchmark, pool, replicate, and reuse data. Concerns and confidence into data-driven applications, stakeholders’ and system’s capabilities, and lack of data standardization and harmonization currently limit the development and implementation of data dentistry. Aspects of bias and data-user interaction require attention. Action items for the dental community circle around increasing data availability, refinement, and usage; demonstrating safety, value, and usefulness of applications; educating the dental workforce and consumers; providing performant and standardized infrastructure and processes; and incentivizing and adopting open data and data sharing.

Machine Learning: The Next Paradigm Shift in Medical Education

Machine learning (ML) algorithms are powerful prediction tools with immense potential in the clinical setting. There are a number of existing clinical tools that use ML, and many more are in development. Physicians are important stakeholders in the health care system, but most are not equipped to make informed decisions regarding deployment and application of ML technologies in patient care. It is of paramount importance that ML concepts are integrated into medical curricula to position physicians to become informed consumers of the emerging tools employing ML. This paradigm shift is similar to the evidence-based medicine (EBM) movement of the 1990s. At that time, EBM was a novel concept; now, EBM is considered an essential component of medical curricula and critical to the provision of high-quality patient care. ML has the potential to have a similar, if not greater, impact on the practice of medicine. As this technology continues its inexorable march forward, educators must continue to evaluate medical curricula to ensure that physicians are trained to be informed stakeholders in the health care of tomorrow.

Programming of weight and obesity across the lifecourse by the maternal metabolic exposome: A systematic review

Exposome research aims to comprehensively understand the multiple environmental exposures that influence human health. To date, much of exposome science has focused on environmental chemical exposures and does not take a lifecourse approach. The rising prevalence of obesity, and the limited success in its prevention points to the need for a better understanding of the diverse exposures that associate with, or protect against, this condition, and the mechanisms driving its pathogenesis. The objectives of this review were to 1. evaluate the evidence on the maternal metabolic exposome in the programming of offspring growth/obesity and 2. identify and discuss the mechanisms underlying the programming of obesity. A systematic review was conducted following PRISMA guidelines to capture articles that investigated early life metabolic exposures and offspring weight and/or obesity outcomes. Scientific databases were searched using pre-determined indexed search terms, and risk of bias assessments were conducted to determine study quality. A final total of 76 articles were obtained and extracted data from human and animal studies were visualised using GOfER diagrams. Multiple early life exposures, including maternal obesity, diabetes and adverse nutrition, increase the risk of high weight at birth and postnatally, and excess adipose accumulation in human and animal offspring. The main mechanisms through which the metabolic exposome programmes offspring growth and obesity risk include epigenetic modifications, altered placental function, altered composition of the gut microbiome and breast milk, and metabolic inflammation, with downstream effects on development of the central appetite system, adipose tissues and liver. Understanding early life risks and protectors, and the mechanisms through which the exposome modifies health trajectories, is critical for developing and applying early interventions to prevent offspring obesity later in life.

Precision Health Care Elements, Definitions, and Strategies for Patients with Diabetes: A Literature Review

Diabetes is a prevalent disease with a high risk of complications. The number of people with diabetes worldwide was reported to increase every year. However, new integrated individualized health care related to diabetes is insufficiently developed. Purpose: The objective of this study was to conduct a literature review and discover precision health care elements, definitions, and strategies. Methods: This study involved a 2-stage process. The first stage comprised a systematic literature search, evidence evaluation, and article extraction. The second stage involved discovering precision health care elements and defining and developing strategies for the management of patients with diabetes. Results: Of 1337 articles, we selected 35 relevant articles for identifying elements and definitions of precision health care for diabetes, including personalized genetic or lifestyle factors, biodata- or evidence-based practice, glycemic target, patient preferences, glycemic control, interdisciplinary collaboration practice, self-management, and patient priority direct care. Moreover, strategies were developed to apply precision health care for diabetes treatment based on eight elements. Conclusions: We discovered precision health care elements and defined and developed strategies of precision health care for patients with diabetes. precision health care is based on team foundation, personalized glycemic target, and control as well as patient preferences and priority, thus providing references for future research and clinical practice.

Translational Applications of Artificial Intelligence and Machine Learning for Diagnostic Pathology in Lymphoid Neoplasms: A Comprehensive and Evolutive Analysis

Genomic analysis and digitalization of medical records have led to a big data scenario within hematopathology. Artificial intelligence and machine learning tools are increasingly used to integrate clinical, histopathological, and genomic data in lymphoid neoplasms. In this study, we identified global trends, cognitive, and social framework of this field from 1990 to 2020. Metadata were obtained from the Clarivate Analytics Web of Science database in January 2021. A total of 525 documents were assessed by document type, research areas, source titles, organizations, and countries. SciMAT and VOSviewer package were used to perform scientific mapping analysis. Geographical distribution showed the USA and People's Republic of China as the most productive countries, reporting up to 190 (36.19%) of all documents. A third-degree polynomic equation predicts that future global production in this area will be three-fold the current number, near 2031. Thematically, current research is focused on the integration of digital image analysis and genomic sequencing in Non-Hodgkin lymphomas, prediction of chemotherapy response and validation of new prognostic models. These findings can serve pathology departments to depict future clinical and research avenues, but also, public institutions and administrations to promote synergies and optimize funding allocation.

Perspectives on Precision Medicine Approaches to NAFLD Diagnosis and Management

Precision medicine defines the attempt to identify the most effective approaches for specific subsets of patients based on their genetic background, clinical features, and environmental factors. Nonalcoholic fatty liver disease (NAFLD) encompasses the alcohol-like spectrum of liver disorders (steatosis, steatohepatitis with/without fibrosis, and cirrhosis and hepatocellular carcinoma) in the nonalcoholic patient. Recently, disease renaming to MAFLD [metabolic (dysfunction)-associated fatty liver disease] and positive criteria for diagnosis have been proposed. This review article is specifically devoted to envisaging some clues that may be useful to implementing a precision medicine-oriented approach in research and clinical practice. To this end, we focus on how sex and reproductive status, genetics, intestinal microbiota diversity, endocrine and metabolic status, as well as physical activity may interact in determining NAFLD/MAFLD heterogeneity. All these factors should be considered in the individual patient with the aim of implementing an individualized therapeutic plan. The impact of considering NAFLD heterogeneity on the development of targeted therapies for NAFLD subgroups is also extensively discussed.

Patient-Centered Medicine: A Necessary Condition for the Management of Functional Somatic Syndromes and Bodily Distress

This paper argues that “functional,” “medically unexplained,” or “somatoform” symptoms and disorders necessarily require a patient-centered approach from the clinicians. In the first part, I address the multiple causes of the patients' suffering and I analyze the unease of the doctors faced with these disorders. I emphasize the iatrogenic role of medical investigations and the frequent failure in attempting to reassure the patients. I stress the difficulties in finding the right terms and concepts, despite overabundant nosological categories, to give a full account of psychosomatic complexity. Finally, I discuss the moral dimension attached to assigning a symptom, at times arbitrarily, to a psychogenic origin. The following part presents a brief reminder of the patient-centered approach (PCA) in medicine. In the last part, I aim to explain why and how patient-centered medicine should be applied in the context of functional disorders. First, because PCA focuses on the patients' experience of illness rather than the disease from the medical point of view, which is, indeed, absent. Second, because PCA is the only way to avoid sterile attribution conflicts. Last, because PCA allows doctors and patients to collaboratively create plausible and non-stigmatizing explanations for the symptoms, which paves the way toward effective management.

Governing Personalized Health: A Scoping Review

Genetic research is advancing rapidly. One important area for the application of the results from this work is personalized health. These are treatments and preventive interventions tailored to the genetic profile of specific groups or individuals. The inclusion of personalized health in existing health systems is a challenge for policymakers. In this article, we present the results of a thematic scoping review of the literature dealing with governance and policy of personalized health. Our analysis points to four governance challenges that decisionmakers face against the background of personalized health. First, researchers have highlighted the need to further extend and harmonize existing research infrastructures in order to combine different types of genetic data. Second, decisionmakers face the challenge to create trust in personalized health applications, such as genetic tests. Third, scholars have pointed to the importance of the regulation of data production and sharing to avoid discrimination of disadvantaged groups and to facilitate collaboration. Fourth, researchers have discussed the challenge to integrate personalized health into regulatory-, financing-, and service provision structures of existing health systems. Our findings summarize existing research and help to guide further policymaking and research in the field of personalized health governance.

Big data, integrative omics and network biology

A cell integrates various signals through a network of biomolecules that crosstalk to synergistically regulate the replication, transcription, translation and other metabolic activities of a cell. These networks regulate signal perception and processing that drives biological functions. The biological complexity cannot be fully captured by a single -omics discipline. The holistic study of an organism-in health, perturbation, exposure to environment and disease, is studied under systems biology. The bottom-up molecular approaches (genes, mRNA, protein, metabolite, etc.) have laid the foundation of current biological knowledge covering the horizon from viruses, bacteria, fungi, plants and animals. Yet, these techniques provide a rather myopic view of biology at the molecular level. To understand how the interconnected molecular components are formed and rewired in disease or exposure to environmental stimuli is the holy grail of modern biology. The omics era was heralded by the genomics revolution but advanced sequencing techniques are now also ubiquitous in transcriptomics, proteomics, metabolomics and lipidomics. Multi-omics data analysis and integration techniques are driving the quest for deeper insights into how the different layers of biomolecules talk to each other in diverse contexts.

Integrated Healthcare and the Dilemma of Public Health Emergencies

Traditional healthcare services have demonstrated structural shortcomings in the delivery of patient care and enforced numerous elements of integration in the delivery of healthcare services. Integrated healthcare aims at providing all healthcare that makes humans healthy. However, with mainly chronically ill people and seniors, typically suffering from numerous comorbidities and diseases, being recruited for care, there is a need for a change in the healthcare service structure beyond direct-patient care to be compatible in peacetime and during public health emergencies. This article’s objective is to discuss the opportunities and obstacles for increasing the effectiveness of healthcare through improved integration. A rapid evidence review approach was used by performing a systematic followed by a non-systematic literature review and content analysis. The results confirmed that integrated healthcare systems play an increasingly important role in healthcare system reforms undertaken in European Union countries. The essence of these changes is the transition from the episodic treatment of acute diseases to the provision of coordinated medical services, focused on chronic cases, prevention, and ensuring patient continuity. However, integrated healthcare, at a level not yet fully defined, will be necessary if we are to both define and attain the integrated practice of both global health and global public health emergencies. This paper attains the necessary global challenges to integrate healthcare effectively at every level of society. There is a need for more knowledge to effectively develop, support, and disseminate initiatives related to coordinated healthcare in the individual healthcare systems.

Fabrication, characterization and applications of graphene electronic tattoos

Numerous fields of science and technology, including healthcare, robotics and bioelectronics, have begun to switch their research direction from developing 'high-end, high-cost' tools towards 'high-end, low-cost' solutions. Graphene electronic tattoos (GETs), whose fabrication protocol is discussed in this work, are ideal building blocks of future wearable technology due to their outstanding electromechanical properties. The GETs are composed of high-quality, large-scale graphene that is transferred onto tattoo paper, resulting in an electronic device that is applied onto skin like a temporary tattoo. Here, we provide a comprehensive GET fabrication protocol, starting from graphene growth and ending with integration onto human skin. The methodology presented is unique since it utilizes high-quality electronic-grade graphene, while the processing is done by using low-cost and off-the-shelf methods, such as a mechanical cutter plotter. The GETs can be either used in combination with advanced scientific equipment to perform precision experiments, or with low-cost electrophysiology boards, to conduct similar operations from home. In this protocol, we showcase how GETs can be applied onto the human body and how they can be used to obtain a variety of biopotentials, including electroencephalogram (brain waves), electrocardiogram (heart activity), electromyogram (muscle activity), as well as monitoring of body temperature and hydration. With graphene available from commercial sources, the whole protocol consumes ~3 h of labor and does not require highly trained personnel. The protocol described in this work can be readily replicated in simple laboratories, including high school facilities.

Artificial intelligence in the diagnosis of pediatric allergic diseases

Artificial intelligence (AI) is a field of data science pertaining to advanced computing machines capable of learning from data and interacting with the human world. Early diagnosis and diagnostics, self-care, prevention and wellness, clinical decision support, care delivery, and chronic care management have been identified within the healthcare areas that could benefit from introducing AI. In pediatric allergy research, the recent developments in AI approach provided new perspectives for characterizing the heterogeneity of allergic diseases among patients. Moreover, the increasing use of electronic health records and personal healthcare records highlighted the relevance of AI in improving data quality and processing and setting-up advanced algorithms to interpret the data. This review aimed to summarize current knowledge about AI and discuss its impact on the diagnostic framework of pediatric allergic diseases such as eczema, food allergy, and respiratory allergy, along with the future opportunities that AI research can offer in this medical area.

Public willingness to participate in personalized health research and biobanking: A large-scale Swiss survey

This paper reports survey findings on the Swiss public's willingness, attitudes, and concerns regarding personalized health research participation by providing health information and biological material. The survey reached a sample of 15,106 Swiss residents, from which we received 5,156 responses (34.1% response rate). The majority of respondents were aware of research using human biological samples (71.0%) and held a positive opinion towards this type of research (62.4%). Of all respondents, 53.6% indicated that they would be willing to participate in a personalized health research project. Willingness to participate was higher in younger, higher educated, non-religious respondents with a background in the health sector. Respondents were more willing to provide 'traditional' types of health data, such as health questionnaires, blood or biological samples, as opposed to social media or app-related data. All respondents valued the return of individual research results, including risk for diseases for which no treatment is available. Our findings highlight that alongside general positive attitudes towards personalized health research using data and samples, respondents have concerns about data privacy and re-use. Concerns included potential discrimination, confidentiality breaches, and misuse of data for commercial or marketing purposes. The findings of this large-scale survey can inform Swiss research institutions and assist policymakers with adjusting practices and developing policies to better meet the needs and preferences of the public. Efforts in this direction could focus on research initiatives engaging in transparent communication, education, and engagement activities, to increase public understanding and insight into data sharing activities, and ultimately strengthen personalized health research efforts.

The Quest for System-Theoretical Medicine in the COVID-19 Era

Precision medicine and molecular systems medicine (MSM) are highly utilized and successful approaches to improve understanding, diagnosis, and treatment of many diseases from bench-to-bedside. Especially in the COVID-19 pandemic, molecular techniques and biotechnological innovation have proven to be of utmost importance for rapid developments in disease diagnostics and treatment, including DNA and RNA sequencing technology, treatment with drugs and natural products and vaccine development. The COVID-19 crisis, however, has also demonstrated the need for systemic thinking and transdisciplinarity and the limits of MSM: the neglect of the bio-psycho-social systemic nature of humans and their context as the object of individual therapeutic and population-oriented interventions. COVID-19 illustrates how a medical problem requires a transdisciplinary approach in epidemiology, pathology, internal medicine, public health, environmental medicine, and socio-economic modeling. Regarding the need for conceptual integration of these different kinds of knowledge we suggest the application of general system theory (GST). This approach endorses an organism-centered view on health and disease, which according to Ludwig von Bertalanffy who was the founder of GST, we call Organismal Systems Medicine (OSM). We argue that systems science offers wider applications in the field of pathology and can contribute to an integrative systems medicine by (i) integration of evidence across functional and structural differentially scaled subsystems, (ii) conceptualization of complex multilevel systems, and (iii) suggesting mechanisms and non-linear relationships underlying the observed phenomena. We underline these points with a proposal on multi-level systems pathology including neurophysiology, endocrinology, immune system, genetics, and general metabolism. An integration of these areas is necessary to understand excess mortality rates and polypharmacological treatments. In the pandemic era this multi-level systems pathology is most important to assess potential vaccines, their effectiveness, short-, and long-time adverse effects. We further argue that these conceptual frameworks are not only valid in the COVID-19 era but also important to be integrated in a medicinal curriculum.

Artificial Intelligence in Differential Diagnostics of Meningitis: A Nationwide Study

Differential diagnosis between bacterial and viral meningitis is crucial. In our study, to differentiate bacterial vs. viral meningitis, three machine learning (ML) algorithms (multiple logistic regression (MLR), random forest (RF), and naïve-Bayes (NB)) were applied for the two age groups (0-14 and >14 years) of patients with meningitis by both conventional (culture) and molecular (PCR) methods. Cerebrospinal fluid (CSF) neutrophils, CSF lymphocytes, neutrophil-to-lymphocyte ratio (NLR), blood albumin, blood C-reactive protein (CRP), glucose, blood soluble urokinase-type plasminogen activator receptor (suPAR), and CSF lymphocytes-to-blood CRP ratio (LCR) were used as predictors for the ML algorithms. The performance of the ML algorithms was evaluated through a cross-validation procedure, and optimal predictions of the type of meningitis were above 95% for viral and 78% for bacterial meningitis. Overall, MLR and RF yielded the best performance when using CSF neutrophils, CSF lymphocytes, NLR, albumin, glucose, gender, and CRP. Also, our results reconfirm the high diagnostic accuracy of NLR in the differential diagnosis between bacterial and viral meningitis.

Deep learning in systems medicine

Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features needed for a given task from high-dimensional, heterogeneous data, deep learning (DL) holds great promise in this endeavour. This review paper addresses the main developments of DL algorithms and a set of general topics where DL is decisive, namely, within the SM landscape. It discusses how DL can be applied to SM with an emphasis on the applications to predictive, preventive and precision medicine. Several key challenges have been highlighted including delivering clinical impact and improving interpretability. We used some prototypical examples to highlight the relevance and significance of the adoption of DL in SM, one of them is involving the creation of a model for personalized Parkinson's disease. The review offers valuable insights and informs the research in DL and SM.

Public and patient involvement in health data governance (DATAGov): protocol of a people-centred, mixed-methods study on data use and sharing for rare diseases care and research

INTRODUCTION

International policy imperatives for the public and patient involvement in the governance of health data coexist with conflicting cross-border policies on data sharing. This can challenge the planning and implementation of participatory data governance in healthcare services locally. Engaging with local stakeholders and understanding how their needs, values and preferences for governing health data can be articulated with policies made at the supranational level is crucial. This paper describes a protocol for a project that aims to coproduce a people-centred model for involving patients and the public in decision-making processes about the use and sharing of health data for rare diseases care and research.

METHODS AND ANALYSIS

This multidisciplinary project draws on an explanatory sequential mixed-methods study. A hospital-based survey with patients, informal carers, health professionals and technical staff recruited at two reference centres for rare diseases in Portugal will be conducted first. The qualitative study will follow consisting of semi-structured interviews and scenario-based workshops with a subsample of the participant groups recruited at baseline. Quantitative data will be analysed using descriptive and inferential statistics. Inductive and deductive approaches will be combined to analyse the qualitative interviews. Data from scenario-based workshops will be iteratively compared using the constant comparison method to identify cross-cutting themes and categories.

ETHICS AND DISSEMINATION

The Ethics Committee for Health from the University Hospital Centre São João/Faculty of Medicine of University of Porto approved the study protocol (Ref. 99/19). Research findings will be disseminated at academic conferences and science promotion events, and through public meetings involving patient representatives, practitioners, policy-makers and students, a project website and peer-reviewed journal publications.

Conceptual innovation: 4P Medicine and 4P surgery

The aim of this article is to present the concept of "4P medicine" i.e., medicine that is Personalized, Preventive, Predictive, and Participatory. We will discuss the evolution from cure-focused traditional medicine toward personalized medicine based on genome analysis. This new approach is illustrated by several clinical examples such as prevention of cardiovascular diseases (primary and secondary), prophylactic cancer surgery, targeted therapies, targeted peri-operative care and patient participation in their care. Finally, it will discuss the impact of this development on the health system of the future and the ethical questions raised by this new approach.

Metal Oxide Nanorods-Based Sensor Array for Selective Detection of Biomarker Gases

The breath gas analysis through gas phase chemical analysis draws attention in terms of non-invasive and real time monitoring. The array-type sensors are one of the diagnostic methods with high sensitivity and selectivity towards the target gases. Herein, we presented a 2 × 4 sensor array with a micro-heater and ceramic chip. The device is designed in a small size for portability, including the internal eight-channel sensor array. In₂O₃ NRs and WO₃ NRs manufactured through the E-beam evaporator's glancing angle method were used as sensing materials. Pt, Pd, and Au metal catalysts were decorated for each channel to enhance functionality. The sensor array was measured for the exhaled gas biomarkers CH₃COCH₃, NO₂, and H₂S to confirm the respiratory diagnostic performance. Through this operation, the theoretical detection limit was calculated as 1.48 ppb for CH₃COCH₃, 1.9 ppt for NO₂, and 2.47 ppb for H₂S. This excellent detection performance indicates that our sensor array detected the CH₃COCH₃, NO₂, and H₂S as biomarkers, applying to the breath gas analysis. Our results showed the high potential of the gas sensor array as a non-invasive diagnostic tool that enables real-time monitoring.

Next-Generation Continuous Metabolite Sensing toward Emerging Sensor Needs

This article discusses the emergent biosensor technology focused on continuous biosensing of metabolites by non-invasive sampling of body fluids emphasized on physiological monitoring in mobility-constrained populations, resource-challenged settings, and harsh environments. The boom of innovative ideas and endless opportunities in healthcare technologies has transformed traditional medicine into a sustainable link between medical practitioners and patients to provide solutions for faster disease diagnosis. The future of healthcare is focused on empowering users to manage their own health. The confluence of big data and predictive analysis and the internet of things (IoT) technology have shown the potential of converting the abundant health profile data amassed from medical diagnosis of patients into useable information, whilst allowing caregivers to provide suitable treatment plans. The implementation of the IoT technology has opened up advanced approaches in real-time, continuous, remote monitoring of patients. Wearable, point-of-care biosensors are the future roadmap to providing direct, real-time information of health status to the user and medical professionals in this digitized era.

Monitoring of Dynamic Plantar Foot Temperatures in Diabetes with Personalised 3D-Printed Wearables

Diabetic foot ulcers (DFUs) are a life-changing complication of diabetes that can lead to amputation. There is increasing evidence that long-term management with wearables can reduce incidence and recurrence of this condition. Temperature asymmetry measurements can alert to DFU development, but measurements of dynamic information, such as rate of temperature change, are under investigated. We present a new wearable device for temperature monitoring at the foot that is personalised to account for anatomical variations at the foot. We validate this device on 13 participants with diabetes (no neuropathy) (group name D) and 12 control participants (group name C), during sitting and standing. We extract dynamic temperature parameters from four sites on each foot to compare the rate of temperature change. During sitting the time constant of temperature rise after shoe donning was significantly (p < 0.05) faster at the hallux (p = 0.032, 370.4 s (C), 279.1 s (D)) and 5th metatarsal head (p = 0.011, 481.9 s (C), 356.6 s (D)) in participants with diabetes compared to controls. No significant differences at the other sites or during standing were identified. These results suggest that temperature rise time is faster at parts of the foot in those who have developed diabetes. Elevated temperatures are known to be a risk factor of DFUs and measurement of time constants may provide information on their development. This work suggests that temperature rise time measured at the plantar surface may be an indicative biomarker for differences in soft tissue biomechanics and vascularisation during diabetes onset and progression.

Online Communities as a Driver for Patient Empowerment: Systematic Review

BACKGROUND

The use of online resources has changed how people manage health care processes. Patients seek information about health conditions, guidance in treatment, and support from peers online, complementary to traditional health care trajectories. Online communities have the potential to contribute to the quality of care by increasing patient empowerment; however, there is a gap in research regarding in what way online communities contribute to patient empowerment.

OBJECTIVE

We synthesized research regarding how online communities contribute to patient empowerment to address the research question "In what ways can participation in online communities support patient empowerment?" by studying how patient empowerment is operationalized in different studies. The definition of patient empowerment used in this paper is enablement for people to develop mastery over actions and control over decisions that influence their lives. The mastery is both through processes and outcomes of the development.

METHODS

A systematic review was conducted by searching in the following databases: Scopus, ACM Digital Library, EBSCO (CINAHL and MEDLINE), PubMed, and Web of Science. In total, there were 1187 papers after excluding duplicates, and through selection processes using an analytical framework with definitions of patient empowerment and related concepts, 33 peer-reviewed papers were included.

RESULTS

Findings indicated that online communities support patient empowerment both as a process and as outcomes of these processes. Additionally, it was seen as a complement to traditional health care and encouragement for health care professionals to have a more positive attitude toward patients' usage. There was a mix between deductive (19/33, 58%), inductive (11/33, 33%), and a mixed approach (3/33, 9%) of studying patient empowerment in various forms. The online communities in most papers (21/33, 64%) were well-established and represented patients' initiatives.

CONCLUSIONS

There is a need to include professionals' perspectives regarding how health care can embrace patient empowerment through online communities. This systematic review's main contribution is the proposal of a new framework and conceptualization of how patient empowerment in online communities can be understood from different hierarchical levels.

One Digital Health: A Unified Framework for Future Health Ecosystems

One Digital Health is a proposed unified structure. The conceptual framework of the One Digital Health Steering Wheel is built around two keys (ie, One Health and digital health), three perspectives (ie, individual health and well-being, population and society, and ecosystem), and five dimensions (ie, citizens’ engagement, education, environment, human and veterinary health care, and Healthcare Industry 4.0). One Digital Health aims to digitally transform future health ecosystems, by implementing a systemic health and life sciences approach that takes into account broad digital technology perspectives on human health, animal health, and the management of the surrounding environment. This approach allows for the examination of how future generations of health informaticians can address the intrinsic complexity of novel health and care scenarios in digitally transformed health ecosystems. In the emerging hybrid landscape, citizens and their health data have been called to play a central role in the management of individual-level and population-level perspective data. The main challenges of One Digital Health include facilitating and improving interactions between One Health and digital health communities, to allow for efficient interactions and the delivery of near–real-time, data-driven contributions in systems medicine and systems ecology. However, digital health literacy; the capacity to understand and engage in health prevention activities; self-management; and collaboration in the prevention, control, and alleviation of potential problems are necessary in systemic, ecosystem-driven public health and data science research. Therefore, people in a healthy One Digital Health ecosystem must use an active and forceful approach to prevent and manage health crises and disasters, such as the COVID-19 pandemic.

Precision Medicine: Applied Concepts of Pharmacogenomics in Patients with Various Diseases and Polypharmacy

Over the last century, the process of choosing medications to treat certain diseases has evolved significantly [...].

Neuroadaptability and Habit: Modern Medicine and Ayurveda

In our increasingly stressed world, especially with the COVID-19 pandemic, the activation of the threat network in everyday situations can adversely affect our mental and physical health. Neurophysiological response to these threats/challenges depends on the type of challenge and the individual’s neuroadaptability. Neuroadaptability is defined as the ability of the nervous system to alter responsiveness over time to reoccurring stimuli. Neuroadaptability differs from neuroplasticity, which is more inclusive and refers to the ability of the nervous system to change and learn from any experience. We examine neuroadaptability and how it affects health from the perspective of modern medicine and Ayurveda.

Personalized and Patient-Centered Strategies to Improve Positive Airway Pressure Adherence in Patients with Obstructive Sleep Apnea

Obstructive sleep apnea (OSA), a common sleep disorder characterized by repeated pauses in breathing during sleep, is effectively treated with positive airway pressure (PAP) therapy. The magnitude of improvements in daily functioning and reduced negative health risks are dependent on maintaining PAP adherence, which is a significant challenge. Evidence-based interventions to improve PAP use are not easily translated to clinical practice because they are labor-intensive and require specialty expertise. Further, to date, individualized care, inclusive of personalized medicine and patient- and person-centered care have been marginally incorporated in the field's understanding of OSA and PAP adherence. This integrative review describes current PAP adherence assessment processes, interventions to improve adherence, and outlines future opportunities to advance the field, particularly as it relates to individualizing care and the use of implementation science to apply evidence to practice.

An Interactive Text Message Survey as a Novel Assessment for Bedtime Routines in Public Health Research: Observational Study

BACKGROUND

Traditional research approaches, especially questionnaires and paper-based assessments, limit in-depth understanding of the fluid dynamic processes associated with child well-being and development. This includes bedtime routine activities such as toothbrushing and reading a book before bed. The increase in innovative digital technologies alongside greater use and familiarity among the public creates unique opportunities to use these technical developments in research.

OBJECTIVE

This study aimed to (1) examine the best way of assessing bedtime routines in families and develop an automated, interactive, text message survey assessment delivered directly to participants' mobile phones and (2) test the assessment within a predominately deprived sociodemographic sample to explore retention, uptake, feedback, and effectiveness.

METHODS

A public and patient involvement project showed clear preference for interactive text surveys regarding bedtime routines. The developed interactive text survey included questions on bedtime routine activities and was delivered for seven consecutive nights to participating parents' mobile phones. A total of 200 parents participated. Apart from the completion of the text survey, feedback was provided by participants, and data on response, completion, and retention rates were captured.

RESULTS

There was a high retention rate (185/200, 92.5%), and the response rate was high (160/185, 86.5%). In total, 114 participants provided anonymized feedback. Only a small percentage (5/114, 4.4%) of participants reported problems associated with completing the assessment. The majority (99/114, 86.8%) of participants enjoyed their participation in the study, with an average satisfaction score of 4.6 out of 5.

CONCLUSIONS

This study demonstrated the potential of deploying SMS text message-based surveys to capture and quantify real-time information on recurrent dynamic processes in public health research. Changes and adaptations based on recommendations are crucial next steps in further exploring the diagnostic and potential intervention properties of text survey and text messaging approaches.

A multi-stakeholder approach to eHealth development: Promoting sustained healthy living among cardiovascular patients

BACKGROUND

Healthy living is key in the prevention and rehabilitation of cardiovascular disease (CVD). Yet, supporting and maintaining a healthy lifestyle is exceptionally difficult and people differ in their needs regarding optimal support for healthy lifestyle interventions.

OBJECTIVE

The goals of this study were threefold: to uncover stakeholders' needs and preferences, to translate these to core values, and develop eHealth technology based on these core values. Our primary research question is: What type of eHealth application to support healthy living among people with (a high risk of) CVD would provide the greatest benefit for all stakeholders?

METHODS

User-centered design principles from the CeHRes roadmap for eHealth development were followed to guide the uncovering of important stakeholder values. Data were synthesized from various qualitative studies (i.e., literature studies, interviews, think-aloud sessions, focus groups) and usability tests (i.e., heuristic evaluation, cognitive walkthrough, think aloud study). We also developed an innovative application evaluation tool to perform a competitor analysis on 33 eHealth applications. Finally, to make sure to take into account all end-users needs and preferences in eHealth technology development, we created personas and a customer journey.

RESULTS

We uncovered 10 universal values to which eHealth-based initiatives to support healthy living in the context of CVD prevention and rehabilitation should adhere to (e.g., providing social support, stimulating intrinsic motivation, offering continuity of care). These values were translated to 14 desired core attributes and then prototype designs. Interestingly, we found that the primary attribute of good eHealth technology was not a single intervention principle, but rather that the technology should be in the form of a digital platform disseminating various interventions, i.e., a 'one-stop-shop'.

CONCLUSION

Various stakeholders in the field of cardiovascular prevention and rehabilitation may benefit most from utilizing one personalized eHealth platform that integrates a variety of evidence-based interventions, rather than a new tool. Instead of a one-size-fits-all approach, this digital platform should aid the matchmaking between patients and specific interventions based on personal characteristics and preferences.

Gastric Cytoprotection as Basis of Gastrointestinal Mucosa Protection and Repair in Erosive Ulcerative Lesions of Various Aetiologies

Aim.Assessment of efficacy and the mechanism of action of gastrointestinal mucosa (GM) protection in current treatment settings with methylmethionine-sulfonium chloride (vitamin U) to illustrate its applicability in erosive ulcerative lesions of various aetiologies.

Key points.Aside to damage prevention in exposure to aggressive agents, gastroprotection implies healing promotion under the preserved level of hydrochloric acid secretion. Prostaglandins (PG) and SH-antioxidants are key mediators of gastroprotection in acute and chronic damage. SH-containing endogenous substances (L-cysteine, D,L-methionine, GSH) and exogenous molecules (methylmethionine-sulfonium chloride (MMSC), N-acetylcysteine) prevent damage due to the ability to absorb/neutralise free radicals released in xenobiotic-triggered cell damage, inhibit TNF-α expression, reduce the aspirin-induced leukocyte-endothelium adhesion and stimulate mucin release. In experiment, MMSC prevented the ethanol-induced GM damage, stimulated mucin release and its redistribution on the GM surface; in clinical trials, MMSC effectively facilitated remission in duodenal ulcer.

Conclusion.Preparations exerting a protective effect on gastroduodenal mucosa, such as methylmethionine-sulfonium chloride (vitamin U), may improve basic treatment settings and facilitate remission in erosive ulcerative lesions of upper gastrointestinal tract.

"…This Has to Do With My Identity. And I Don't Want to Make it Totally Transparent." Identity Relevance in the Attitudes of Affected People and Laypersons to the Handling of High-Throughput Genomic Data

With the establishment of genome sequencing, the influence of genomic information on self-understanding and identity construction has become increasingly important. New sequencing methods far exceed previous genetic tests in terms of scope and quantity. Despite theoretical approaches, however, there are few empirical findings on the identity-relevant influence of genomic information. The present study examines genomic information's identity-relevant influences and considers whether developments in the field of genome sequencing may generate problems that are not yet addressed by existing identity concepts based on traditional genetic tests. The study is based on 10 partially standardized interviews with personally affected persons and four focus groups with medical laypersons as representatives of the public, which were evaluated on the basis of qualitative content analysis. As a result, this paper presents five thematic areas with identity-relevant references within subjective attitudes toward the handling of genomic information, and also derives two basic identity concepts. The results indicate that the lay discourse is still strongly based on older debates about genetic testing and that the view on the complexity of genomic information established in the scientific context has thus far no influence on the perspectives either of those affected or laypersons.

Personalized medicine, digital technology and trust: a Kantian account

Trust relations in the health services have changed from asymmetrical paternalism to symmetrical autonomy-based participation, according to a common account. The promises of personalized medicine emphasizing empowerment of the individual through active participation in managing her health, disease and well-being, is characteristic of symmetrical trust. In the influential Kantian account of autonomy, active participation in management of own health is not only an opportunity, but an obligation. Personalized medicine is made possible by the digitalization of medicine with an ensuing increased tailoring of diagnostics, treatment and prevention to the individual. The ideal is to increase wellness by minimizing the layer of interpretation and translation between relevant health information and the patient or user. Arguably, this opens for a new level of autonomy through increased participation in treatment and prevention, and by that, increased empowerment of the individual. However, the empirical realities reveal a more complicated landscape disturbed by information 'noise' and involving a number of complementary areas of expertise and technologies, hiding the source and logic of data interpretation. This has lead to calls for a return to a mild form of paternalism, allowing expertise coaching of patients and even withholding information, with patients escaping responsibility through blind or lazy trust. This is morally unacceptable, according to Kant's ideal of enlightenment, as we have a duty to take responsibility by trusting others reflexively, even as patients. Realizing the promises of personalized medicine requires a system of institutional controls of information and diagnostics, accessible for non-specialists, supported by medical expertise that can function as the accountable gate-keeper taking moral responsibility required for an active, reflexive trust.

Ayurgenomics and Modern Medicine

Within the disciplines of modern medicine, P4 medicine is emerging as a new field which focuses on the whole patient. The development of Ayurgenomics could greatly enrich P4 medicine by providing a clear theoretical understanding of the whole patient and a practical application of ancient and modern preventative and therapeutic practices to improve mental and physical health. One of the most difficult challenges today is understanding the ancient concepts of Ayurveda in terms of modern science. To date, a number of researchers have attempted this task, of which one of the most successful outcomes is the creation of the new field of Ayurgenomics. Ayurgenomics integrates concepts in Ayurveda, such as Prakriti, with modern genetics research. It correlates the combination of three doshas, Vata, Pitta and Kapha, with the expression of specific genes and physiological characteristics. It also helps to interpret Ayurveda as an ancient science of epigenetics which assesses the current state of the doshas, and uses specific personalized diet and lifestyle recommendations to improve a patient’s health. This review provides a current update of this emerging field.

Displacement in root apex and changes in incisor inclination affect alveolar bone remodeling in adult bimaxillary protrusion patients: a retrospective study

BACKGROUND

Periodontal health is of great concern for periodontists and orthodontists in the inter-disciplinary management of patients with bimaxillary protrusion. The aim of present study is to investigate changes in the alveolar bone in the maxillary incisor region and to explore its relationship with displacement of root apex as well as changes in the inclination of maxillary incisors during incisor retraction.

METHODS

Samples in this retrospective study consisted of 38 patients with bimaxillary protrusion. Cone-beam computed tomography (CBCT) images was taken before(T0) and after (T1) treatment. Alveolar bone thickness (ABT), height (ABH) and area (ABA) were utilized to evaluate changes in the alveolar bone, while incisor inclination and apex displacement were used to assess changes in the position of maxillary central and lateral incisors. Correlations between alveolar bone remodeling and apex displacement as well as changes in the inclination were investigated.

RESULTS

The labial ABT of central and lateral incisors at the mid-root third was increased. In contrast, the palatal ABT at crestal, mid-root and apical third level were consistently decreased. ABH was not altered on the labial side, while significantly decreased on the palatal side. ABA was not significantly increased on the labial side, but significantly decreased on the palatal side, leading to a significantly reduced total ABA. Orthodontic treatment significantly reduced inclination of upper incisors. Changes in the amount (T1-T0) of ABA was remarkably correlated with apex displacement and changes of inclination (T1-T0); in addition, using the multivariate linear regression analysis, changes of ABA on the palatal side (T1-T0) can be described by following equation: Changes of palatal ABA (T1-T0) = - 3.258- 0.139× changes of inclination (T1-T0) + 2.533 × apex displacement (T1-T0).

CONCLUSIONS

Retraction of incisors in bimaxillary protrusion patients may compromise periodontal bone support on the palatal side. An equation that incorporated the displacement of root apex and change in the incisor inclination may enable periodontist-orthodontist interdisciplinary coordination in assessing treatment risks and developing an individualized treatment plan for adult patients with bimaxillary protrusion. Moreover, the equation in predicating area of alveolar bone may reduce the risks of placing the teeth out of the bone boundary during 3D digital setups.

Prevention in the age of personal responsibility: epigenetic risk-predictive screening for female cancers as a case study

Epigenetic markers could potentially be used for risk assessment in risk-stratified population-based cancer screening programmes. Whereas current screening programmes generally aim to detect existing cancer, epigenetic markers could be used to provide risk estimates for not-yet-existing cancers. Epigenetic risk-predictive tests may thus allow for new opportunities for risk assessment for developing cancer in the future. Since epigenetic changes are presumed to be modifiable, preventive measures, such as lifestyle modification, could be used to reduce the risk of cancer. Moreover, epigenetic markers might be used to monitor the response to risk-reducing interventions. In this article, we address ethical concerns related to personal responsibility raised by epigenetic risk-predictive tests in cancer population screening. Will individuals increasingly be held responsible for their health, that is, will they be held accountable for bad health outcomes? Will they be blamed or subject to moral sanctions? We will illustrate these ethical concerns by means of a Europe-wide research programme that develops an epigenetic risk-predictive test for female cancers. Subsequently, we investigate when we can hold someone responsible for her actions. We argue that the standard conception of personal responsibility does not provide an appropriate framework to address these concerns. A different, prospective account of responsibility meets part of our concerns, that is, concerns about inequality of opportunities, but does not meet all our concerns about personal responsibility. We argue that even if someone is responsible on grounds of a negative and/or prospective account of responsibility, there may be moral and practical reasons to abstain from moral sanctions.

Salivary biomarkers for discriminating periodontitis in the presence of diabetes

AIM

Salivary biomarkers can help in assessment of periodontitis; however, concentrations may be altered in the presence of diabetes. Hence, the ability of salivary biomarkers to discriminate periodontally healthy type II diabetics (T2DM) from T2DM who have periodontitis was examined.

METHODS

Ninety-two participants (29 with T2DM with chronic periodontitis, DWP; 32 T2DM without chronic periodontitis, DWoP; and 31 Not Periodontitis, NP) provided saliva and clinical parameters of periodontal health were recorded. Salivary concentrations of interleukin (IL)-1β, IL-6, matrix metalloproteinase-8 (MMP-8), macrophage inflammatory protein-1α (MIP-1α), adiponectin and resistin were measured by immunoassay.

RESULTS

Salivary analyte concentrations for IL-1β, MMP-8 and resistin correlated with clinical parameters of periodontitis, with MMP-8 demonstrating the strongest positive correlation with PD ≥5 mm (p < 0.0001). Periodontal health was reflected in salivary analyte concentrations by group, with concentrations of IL-1β and MMP-8 showing significant associations with periodontitis (p ≤ 0.04) that increased in concentration from health to DWoP to DWP. Odds ratio (OR) analyses showed that MMP-8 discriminated periodontitis from NP (OR of 8.12; 95% CI: 1.01-65.33; p = 0.03) and in the presence of T2DM (DWP vs DWoP, OR = 5.09; 95% CI: 1.24-20.92; p = 0.03).

CONCLUSION

Salivary MMP-8 and IL-1β discriminate periodontitis in T2DM.

Impact of predictive, preventive and precision medicine strategies in epilepsy

Over the last decade, advances in genetics, neuroimaging and EEG have enabled the aetiology of epilepsy to be identified earlier in the disease course than ever before. At the same time, progress in the study of experimental models of epilepsy has provided a better understanding of the mechanisms underlying the condition and has enabled the identification of therapies that target specific aetiologies. We are now witnessing the impact of these advances in our daily clinical practice. Thus, now is the time for a paradigm shift in epilepsy treatment from a reactive attitude, treating patients after the onset of epilepsy and the initiation of seizures, to a proactive attitude that is more broadly integrated into a 'P4 medicine' approach. This P4 approach, which is personalized, predictive, preventive and participatory, puts patients at the centre of their own care and, ultimately, aims to prevent the onset of epilepsy. This aim will be achieved by adapting epilepsy treatments not only to a given syndrome but also to a given patient and moving from the usual anti-seizure treatments to personalized treatments designed to target specific aetiologies. In this Review, we present the current state of this ongoing revolution, emphasizing the impact on clinical practice.