Assessing the status of oral health integration in South East Asian Regional Office countries' Universal Health Coverage-A scoping review.

BACKGROUND: Oral diseases affect close to 3.5 billion people worldwide and there has been a call by the World Health Organization (WHO) to integrate oral health into the Universal Health Coverage (UHC) agenda. OBJECTIVES: To collate and synthesise information regarding the status of integration of oral health into the health systems covered by UHC across the 11 countries in the South East Asian Regional Office. METHODS: Drawing on the framework of the six building blocks of health systems as devised by WHO, we compared the public dental care coverage models, with a focus on outpatient dental care in these countries. We gathered this information from publicly available resources, databases and peer-reviewed publications to populate the template guided by the WHO Health System Building Blocks. RESULTS: We found a poor access to oral health care, lopsided distribution of manpower, rickety health information systems, and private sector domination and inadequate or absent financing mechanisms for outpatient procedures. The private sector was dominant in all countries except Thailand and Srilanka. Financing was absent in most countries and deficient in Thailand and Indonesia. Dental workforce was deficient in most countries except India, Srilanka, and Thailand. Health information systems were weak with no dental items under price control. Better UHC indicators did not guarantee a lower oral disease burden. CONCLUSIONS: Our review highlighted the close connection between service quality and human resources, governance, and finance. There is a need to establish standardised dental treatment guidelines that are uniformly adopted across countries, integrate oral health into national health and development programs, push for functional oral health research through collecting robust surveillance, economic, and social impact data and the development of cost-effective strategies tailored to each country's unique needs.

Strengthening the Interface of Evidence-Based Decision Making Across European Regulators and Health Technology Assessment Bodies.

OBJECTIVES: Access to medicines in Europe depends on a benefit-risk decision taken by regulators and a relative effectiveness assessment performed by health technology assessment bodies (HTABs) to inform, as one element, a reimbursement decision. Although various similarities in evidence needs exist, understanding of their needs is currently suboptimal and therefore the evidence generated does not always meet their needs. Subsequently, delays in decision making can be expected, negatively affecting access. To overcome this, this study reviewed the evidentiary needs of European regulators and HTABs at European level and analyzed how their collaboration can further facilitate optimal evidence generation plans, evidence use, and evidence presentation. METHODS: Through systematic literature review, expert interviews, and pairwise comparison of assessment reports by the European Medicines Agency and European network for health technology assessment, respective clinical evidence requirements and impact of product-specific collaboration between European Medicines Agency and HTABs were established. RESULTS: Clinical evidence needs are quite similar but differences exist in comparator choice, preferred efficacy endpoints, and target population. Results of the impact of collaboration to date were mixed: preapproval joint advice procedures were successful and highly valued by all stakeholders; information exchange at the time of regulatory decision is coming together, yet the European Public Assessment Report can be further optimized; and collaboration on postlicensing evidence generation requirements shows potential but needs solidifying. CONCLUSIONS: These findings demonstrate the potential to further improve the evidence utilization across stakeholders to avoid duplication and streamline decision making, to ultimately improve access to medicines for European patients.

Mapping of clinical research on artificial intelligence in the treatment of cancer and the challenges and opportunities underpinning its integration in the European Union health sector.

BACKGROUND: Although current efforts are made to diminish the incidence and burden of disease, cancer is still widely identified late at stage. This study aims to conduct a systematic review mapping the existent and emerging clinical research on artificial intelligence (AI) in the treatment of cancer and to underpin its integration challenges and opportunities in the European Union (EU) health sector. METHODS: A systematic literature review (SLR) evaluating global clinical trials (CTs; published between 2010 and 2020 or forthcoming) was concluded. Additionally, a horizon scanning (HS) exercise focusing on emerging trends (published between 2017 and 2020) was conducted. RESULTS: Forty-four CTs were identified and analyzed. Selected CTs were divided into three research areas: (i) potential of AI combined with imaging techniques, (ii) AI's applicability in robotic surgery interventions and (iii) AI's potential in clinical decision making. Twenty-one studies presented an interventional nature, nine papers were observational and 14 articles did not explicitly mention the type of study performed. The papers presented an increased heterogeneity in sample size, type of tumour, type of study and reporting of results. In addition, a shift in research is observed and only a small fraction of studies were completed in the EU. These findings could be further linked to the current socio-economic, political, scientific, technological and environmental state of the EU in regard to AI innovation. CONCLUSION: To overcome the challenges threatening the EU's integration of such technology in the healthcare field, new strategies taking into account the EU's socio-economic and political environment are deemed necessary.

Regulatory Science and Innovation Programme for Europe (ReScIPE): A proposed model.

Regulatory science underpins the objective evaluation of medicinal products. It is therefore imperative that regulatory science and expertise remain at the cutting edge so that innovations of ever-increasing complexity are translated safely and swiftly into effective, high-quality therapies. We undertook a comprehensive examination of the evolution of science and technology impacting on medicinal product evaluation over the next 5-10 years and this horizon-scanning activity was complemented by extensive stakeholder interviews, resulting in a number of significant recommendations. Highlighted in particular was the need for expertise and regulatory science research to fill knowledge gaps in both more fundamental, longer-term research, with respect to technological and product-specific challenges. A model is proposed to realise these objectives in Europe, comprising a synergistic relationship between the European Medicines Agency, the European Medicines Regulatory Network and academic research centres to establish a novel regulatory science and innovation platform.

Use of big data for drug development and for public and personal health and care.

The use of data analytics across the entire healthcare value chain, from drug discovery and development through epidemiology to informed clinical decision for patients or policy making for public health, has seen an explosion in the recent years. The increase in quantity and variety of data available together with the improvement of storing capabilities and analytical tools offer numerous possibilities to all stakeholders (manufacturers, regulators, payers, healthcare providers, decision makers, researchers) but most importantly, it has the potential to improve general health outcomes if we learn how to exploit it in the right way. This article looks at the different sources of data and the importance of unstructured data. It goes on to summarize current and potential future uses in drug discovery, development, and monitoring as well as in public and personal healthcare; including examples of good practice and recent developments. Finally, we discuss the main practical and ethical challenges to unravel the full potential of big data in healthcare and conclude that all stakeholders need to work together towards the common goal of making sense of the available data for the common good.

An accurate bacterial DNA quantification assay for HTS library preparation of human biological samples.

Sequencing and classification of microbial taxa within forensically relevant biological fluids has the potential for applications in the forensic science and biomedical fields. The quantity of bacterial DNA from human samples is currently estimated based on quantity of total DNA isolated. This method can miscalculate bacterial DNA quantity due to the mixed nature of the sample, and consequently library preparation is often unreliable. We developed an assay that can accurately and specifically quantify bacterial DNA within a mixed sample for reliable 16S ribosomal DNA (16S rDNA) library preparation and high throughput sequencing (HTS). A qPCR method was optimized using universal 16S rDNA primers, and a commercially available bacterial community DNA standard was used to develop a precise standard curve. Following qPCR optimization, 16S rDNA libraries from saliva, vaginal and menstrual secretions, urine, and fecal matter were amplified and evaluated at various DNA concentrations; successful HTS data were generated with as low as 20 pg of bacterial DNA. Changes in bacterial DNA quantity did not impact observed relative abundances of major bacterial taxa, but relative abundance changes of minor taxa were observed. Accurate quantification of microbial DNA resulted in consistent, successful library preparations for HTS analysis.

Toward the integration of Omics data in epidemiological studies: still a "long and winding road".

Primary and secondary prevention can highly benefit a personalized medicine approach through the accurate discrimination of individuals at high risk of developing a specific disease from those at moderate and low risk. To this end precise risk prediction models need to be built. This endeavor requires a precise characterization of the individual exposome, genome, and phenome. Massive molecular omics data representing the different layers of the biological processes of the host and the nonhost will enable to build more accurate risk prediction models. Epidemiologists aim to integrate omics data along with important information coming from other sources (questionnaires, candidate markers) that has been proved to be relevant in the discrimination risk assessment of complex diseases. However, the integrative models in large-scale epidemiologic research are still in their infancy and they face numerous challenges, some of them at the analytical stage. So far, there are a small number of studies that have integrated more than two omics data sets, and the inclusion of non-omics data in the same models is still missing in most of studies. In this contribution, we aim at approaching the omics and non-omics data integration from the epidemiology scope by considering the "massive" inclusion of variables in the risk assessment and predictive models. We also provide already available examples of integrative contributions in the field, propose analytical strategies that allow considering both omics and non-omics data in the models, and finally review the challenges imbedding this type of research.

Personalized Medicine: What's in it for Rare Diseases?

Personalised Medicine has become a reality over the last years. The emergence of 'omics' and big data has started revolutionizing healthcare. New 'omics' technologies lead to a better molecular characterization of diseases and a new understanding of the complexity of diseases. The approach of PM is already successfully applied in different healthcare areas such as oncology, cardiology, nutrition and for rare diseases. However, health systems across the EU are often still promoting the 'one-size fits all' approach, even if it is known that patients do greatly vary in their molecular characteristics and response to drugs and other interventions. To make use of the full potentials of PM in the next years ahead several challenges need to be addressed such as the integration of big data, patient empowerment, translation of basic to clinical research, bringing the innovation to the market and shaping sustainable healthcare systems.

Success stories in genomic medicine from resource-limited countries.

In recent years, the translation of genomic discoveries into mainstream medical practice and public health has gained momentum, facilitated by the advent of new technologies. However, there are often major discrepancies in the pace of implementation of genomic medicine between developed and developing/resource-limited countries. The main reason does not only lie in the limitation of resources but also in the slow pace of adoption of the new findings and the poor understanding of the potential that this new discipline offers to rationalize medical diagnosis and treatment. Here, we present and critically discuss examples from the successful implementation of genomic medicine in resource-limited countries, focusing on pharmacogenomics, genome informatics, and public health genomics, emphasizing in the latter case genomic education, stakeholder analysis, and economics in pharmacogenomics. These examples can be considered as model cases and be readily replicated for the wide implementation of pharmacogenomics and genomic medicine in other resource-limited environments.

Whole genome prediction of bladder cancer risk with the Bayesian LASSO.

To build a predictive model for urothelial carcinoma of the bladder (UCB) risk combining both genomic and nongenomic data, 1,127 cases and 1,090 controls from the Spanish Bladder Cancer/EPICURO study were genotyped using the HumanHap 1M SNP array. After quality control filters, genotypes from 475,290 variants were available. Nongenomic information comprised age, gender, region, and smoking status. Three Bayesian threshold models were implemented including: (1) only genomic information, (2) only nongenomic data, and (3) both sources of information. The three models were applied to the whole population, to only nonsmokers, to male smokers, and to extreme phenotypes to potentiate the UCB genetic component. The area under the ROC curve allowed evaluating the predictive ability of each model in a 10-fold cross-validation scenario. Smoking status showed the highest predictive ability of UCB risk (AUCtest = 0.62). On the other hand, the AUC of all genetic variants was poorer (0.53). When the extreme phenotype approach was applied, the predictive ability of the genomic model improved 15%. This study represents a first attempt to build a predictive model for UCB risk combining both genomic and nongenomic data and applying state-of-the-art statistical approaches. However, the lack of genetic relatedness among individuals, the complexity of UCB etiology, as well as a relatively small statistical power, may explain the low predictive ability for UCB risk. The study confirms the difficulty of predicting complex diseases using genetic data, and suggests the limited translational potential of findings from this type of data into public health interventions.

Host genetic variations in glutathione-S-transferases, superoxide dismutases and catalase genes influence susceptibility to malaria infection in an Indian population.

Antioxidant enzymes can contribute to disease susceptibility or determine response to therapy in individuals with malaria. Genetic variations due to polymorphisms in host genes encoding antioxidant enzymes such as glutathione S-transferases-theta, mu, pi (GSTT, GSTM, GSTP), superoxide dismutases (SOD) and catalase (CAT), may therefore, influence inter-individual response to malaria pathology and propensity of infection caused by Plasmodium vivax (Pv) and Plasmodium falciparum (Pf). Therefore, using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and DNA sequencing, we investigated the association of deletions of GSTT1 and GSTM1, single nucleotide polymorphisms (SNPs) of GSTP1 (rs1695), SOD1 (rs2234694), SOD2 (rs4880, rs1141718), SOD3 (rs2536512) and CAT (rs1001179) in individuals infected with Pf (n = 100) and Pv (n = 100) against healthy controls (n = 150). Our data suggest a significant role for GSTM1 deletions in complicated Pv (p = 0.0007) malaria with ODDs ratio 3.8 [with 95 % confidence interval (CI) 1.9-7.4]. The results also indicated that polymorphisms present in GSTP1, SOD1 and CAT genes may be associated with malaria susceptibility (p < 0.05), whereas SOD3 polymorphism may play a role in malarial resistance (p < 0.05). In addition, we observed significant SNP-SNP interactions with synergistic genetic effects in SOD2, SOD3 and CAT genes for Pv and in SOD2 and SOD3 genes for Pf. In conclusion, our results provide convincing evidence for a relationship between polymorphisms in host antioxidant enzymes and susceptibility to malaria infection.

Genetic similarities between tobacco use disorder and related comorbidities: an exploratory study.

BACKGROUND: Tobacco use disorder (TUD), defined as the use of tobacco to the detriment of a person's health or social functioning, is associated with various disorders. We hypothesized that mutual variation in genes may partly explain this link. The aims of this study were to make a non-exhaustive inventory of the disorders using (partially) the same genetic pathways as TUD, and to describe the genetic similarities between TUD and the selected disorders. METHODS: We developed a 3 stage approach: (i) selection of genes influencing TUD using Gene2Mesh and Ingenuity Pathway Analysis (IPA), (ii) selection of disorders associated with the selected genes using IPA and (iii) genetic similarities between disorders associated with TUD using Jaccard distance and cluster analyses. RESULTS: Fourteen disorders and thirty-two genes met our inclusion criteria. The Jaccard distance between pairs of disorders ranged from 0.00 (e.g. oesophageal cancer and malignant hypertension) to 0.45 (e.g. bladder cancer and addiction). A lower number in the Jaccard distance indicates a higher similarity between the two disorders. Two main clusters of genetically similar disorders were observed, one including coexisting disorders (e.g. addiction and alcoholism) and the other one with the side-effects of smoking (e.g. gastric cancer and malignant hypertension). CONCLUSIONS: This exploratory study partly explains the potential genetic components linking TUD to other disorders. Two principle clusters of disorders were observed (i) coexisting disorders of TUD and (ii) side-effects of TUD disorders. A further deepening of this observation in a real life study should allow strengthening this hypothesis.

Communicating genetics and smoking through social media: are we there yet?

BACKGROUND: Social media is a recent source of health information that could disseminate new scientific research, such as the genetics of smoking. OBJECTIVE: The objectives were (1) to evaluate the availability of genetic information about smoking on different social media platforms (ie, YouTube, Facebook, and Twitter) and (2) to assess the type and the content of the information displayed on the social media as well as the profile of people publishing this information. METHODS: We screened posts on YouTube, Facebook, and Twitter with the terms "smoking" and "genetic" at two time points (September 18, 2012, and May 7, 2013). The first 100 posts were reviewed for each media for the time points. Google was searched during Time 2 as an indicator of available information on the Web and the other social media that discussed genetics and smoking. The source of information, the country of the publisher, characteristics of the posts, and content of the posts were extracted. RESULTS: On YouTube, Facebook, and Twitter, 31, 0, and 84 posts, respectively, were included. Posts were mostly based on smoking-related diseases, referred to scientific publications, and were largely from the United States. From the Google search, most results were scientific databases. Six scientific publications referred to within the Google search were also retrieved on either YouTube or Twitter. CONCLUSIONS: Despite the importance of public understanding of smoking and genetics, and the high use of social media, little information on this topic is actually present on social media. Therefore, there is a need to monitor the information that is there and to evaluate the population's understanding of the information related to genetics and smoking that is displayed on social media.

[New genetic tests and their clinical utility for cancer screening]. / Neue genetische Tests und ihr Nutzen in der Krebsvorsorge.

The promises resulting from the decoding of the human genome have not been fulfilled to the extent as expected. At the same time it is fair to say that the results of recent genetic research have not been useless. In the area of ​​​​familial cancer the clinical benefit of genetic testing for healthy family members is very convincing, where the risk of disease can be reduced substantially through preventive interventions. For example, prophylactic mastectomy and premenopausal ovariectomy can reduce the cancer risk in carriers of BRCA1 and BRCA2 mutations dramatically. In recent years, the research has moved towards the decoding of the genetic causes of sporadic cancers as well. Genome-wide and hypothesis-free association studies have linked different chromosome regions to cancer. By this, new insights into disease mechanisms could be gained, an important requirement for the development of diagnostics and drugs. However, what is missing is the evidence that the associated SNPs (Single Nucleotide Polymorphisms) could be useful for individual risk calculation or for stratification of the population into groups with different preventive or screening needs.

One Health Lens for Antimicrobial Resistance Research and Funding: A Systematic Review.

One Health (OH) offers conceptual and applied prospects to advance planetary health and integrative biology in the 21st century. For example, The World Health Organization (WHO) has declared antimicrobial resistance (AMR) one of humanity's top 10 health threats worldwide (AMR). The AMR research, as seen through the OH lens, recognizes the interdependence and the coproduction of the health of humans, nonhuman animals, and the environment (the OH triad). Moreover, research and development (R&D) is required to generate potential solutions to prevent, diagnose, and treat infections and control the spread and emergence of AMR. However, it is still unclear how well the OH approach is integrated into current AMR R&D. In this study, we present a systematic review on the OH funding landscape for cross-sectoral AMR R&D, and its alignment/gaps with the current global strategic agenda on AMR. A systematic literature review was conducted using public databases covering the period between January 2015 and May 2022. We included the studies and reviews on AMR encompassing more than one sector of the OH triad. Out of the 777 included studies, 475 (61%) encompassed the three OH sectors. A key finding of the present systematic review is that the environment was the most neglected sector in the OH triad. AMR surveillance, transmission, and interventions are the most commonly studied priority topics. In addition, both cross-sectoral AMR literature and investments have been increasing since 2017. The operational aspect of AMR is the most researched and funded area. However, certain priority topics in the strategic research and innovation agenda of the Joint Programming Initiative on AMR are underrepresented in OH AMR research, such as diagnosis and therapeutics. To the best of authors' knowledge, this is the first study that systematically reviews the cross-sectoral literature on AMR, classifies it, and aligns and contextualizes it in regard to the funding landscape of AMR. This systematic review identifies neglected areas in AMR R&D and could serve as critical information for policymaking so as to realize the objectives of the Global Action Plan on AMR. Going forward, more cross-sectoral AMR research and funding are needed. As integrative biology and omics systems science are poised to benefit from a rapprochement with the OH lens, the present article highlights the AMR research and funding landscapes.

How Can Omics Inform Diabetic Foot Ulcer Clinical Management? A Whole Genome Comparison of Four Clinical Strains of Staphylococcus aureus.

Foot ulcers and associated infections significantly contribute to morbidity and mortality in diabetes. While diverse pathogens are found in the diabetes-related infected ulcers, Staphylococcus aureus remains one of the most virulent and widely prevalent pathogens. The high prevalence of S. aureus in chronic wound infections, especially in clinical settings, is attributed to its ability to evolve and acquire resistance against common antibiotics and to elicit an array of virulence factors. In this study, whole genome comparison of four strains of S. aureus (MUF168, MUF256, MUM270, and MUM475) isolated from diabetic foot ulcer (DFU) infections showing varying resistance patterns was carried out to study the genomic similarity, antibiotic resistance profiling, associated virulence factors, and sequence variations in drug targets. The comparative genome analysis showed strains MUM475 and MUM270 to be highly resistant, MUF256 with moderate levels of resistance, and MUF168 to be the least resistant. Strain MUF256 and MUM475 harbored more virulence factors compared with other two strains. Deleterious sequence variants were observed suggesting potential role in altering drug targets and drug efficacy. This comparative whole genome study offers new molecular insights that may potentially inform evidence-based diagnosis and treatment of DFUs in the clinic.

A Comprehensive Bioinformatics Resource Guide for Genome-Based Antimicrobial Resistance Studies.

The use of high-throughput sequencing technologies and bioinformatic tools has greatly transformed microbial genome research. With the help of sophisticated computational tools, it has become easier to perform whole genome assembly, identify and compare different species based on their genomes, and predict the presence of genes responsible for proteins, antimicrobial resistance, and toxins. These bioinformatics resources are likely to continuously improve in quality, become more user-friendly to analyze the multiple genomic data, efficient in generating information and translating it into meaningful knowledge, and enhance our understanding of the genetic mechanism of AMR. In this manuscript, we provide an essential guide for selecting the popular resources for microbial research, such as genome assembly and annotation, antibiotic resistance gene profiling, identification of virulence factors, and drug interaction studies. In addition, we discuss the best practices in computer-oriented microbial genome research, emerging trends in microbial genomic data analysis, integration of multi-omics data, the appropriate use of machine-learning algorithms, and open-source bioinformatics resources for genome data analytics.

Emerging Pathogens in Planetary Health and Lessons from Comparative Genome Analyses of Three Clostridia Species.

Clostridioides difficile (CD) is a major planetary health burden. A Gram-positive opportunistic pathogen, CD, colonizes the large intestine and is implicated in sepsis, pseudomembranous colitis, and colorectal cancer. C. difficile infection typically following antibiotic exposure results in dysbiosis of the gut microbiome, and is one of the leading causes of diarrhea in the elderly population. While several studies have focused on the toxigenic strains of CD, gut commensals such as Clostridium butyricum (CB) and Clostridium tertium (CT) could harbor toxin/virulence genes, and thus pose a threat to human health. In this study, we sequenced and characterized three isolates, namely, CT (MALS001), CB (MALS002), and CD (MALS003) for their antimicrobial, cytotoxic, antiproliferative, genomic, and proteomic profiles. Although in vitro cytotoxic and antiproliferative potential were observed predominantly in CD MALS003, genome analysis revealed pathogenic potential of CB MALS002 and CT MALS001. Pangenome analysis revealed the presence of several accessory genes typically involved in fitness, virulence, and resistance characteristics in the core genomes of sequenced strains. The presence of an array of virulence and antimicrobial resistance genes in CB MALS002 and CT MALS001 suggests their potential role as emerging pathogens with significant impact on planetary health.

Barriers and Facilitators for the Donation and Acceptance of Human Breast milk: A Scoping Review.

PURPOSE OF REVIEW: Human milk is the best source of nutrients for all infants. When a mother's own milk is unavailable, the World Health Organization suggests using donor human milk for premature neonates with or without medical complications. Exploring the barriers and facilitators for breast milk donation and its acceptability is essential for developing this intervention. A scoping review was conducted based on a methodological framework developed by Arksey and O'Malley (Int J Soc Res Methodol 8:19-32, 2005). A search was conducted in PubMed (NCBI), CINAHL (EBSCO), and Web of Science (Elsevier). A two-stage sequential screening process was adopted. Data extraction was done using a piloted data extraction form. RECENT FINDINGS: We included 20 articles for narrative synthesis. Barriers and facilitators for donating and accepting breast milk were categorized under six themes: individual, family, community, workplace, health system, and policy-related. The common individual barriers were time requirements for BMD, personal dislike of the process, lack of knowledge, insufficient milk, negative opinions, and lack of information. Family stigma, negative rumors, less educated family members, and illness of a family member were identified as family-related barriers. Community-related barriers include cultural or religious unacceptable practices, societal taboos, and distance to milk banks. The major barriers identified in relation to the health system were lack of practical and psychological support, lack of information, storing and transportation issues, lack of knowledge among HCWs, and logistical challenges of creating a milk lab. The common work-related barriers were the lack of adequate time, philosophical objections, and incomprehension at returning to work. Policy-related barriers identified include the need for hygiene requirements, donation costs, and lack of standardized guidelines. Making the donation process faster, providing pick-up services for donors, and community education and male partner engagement regarding breast milk donation could help to boost the acceptability of breast milk donation.