Systematic Mapping Research Articles

Offline to online: a systematic mapping review of evidence to inform nutrition-related policies applicable to online food delivery platforms

Offline to online: a systematic mapping review of evidence to inform nutrition-related policies applicable to online food delivery platforms

Characteristics of longitudinal maternal health studies in sub-Saharan Africa: A systematic mapping of literature between 2012 and 2022.

High maternal mortality rates in sub-Saharan Africa necessitate the need for aligned research focusing on prevalent causes and neglected conditions in the region. This mapping review aimed to describe the characteristics of longitudinal maternal health studies between 2012 and 2022 in sub-Saharan Africa and identify gaps in priority conditions or geographical locations. We identified references through a Medline (PubMed) search covering September 2012 to June 2022. We included prospective cohort or clinical trials that enrolled at least 1000 pregnant women, with a study site in sub-Saharan Africa, and published in English or French. Screening and data extraction were done in duplicate using EPPI-reviewer software. Descriptive analysis was used to summarize the results, identifying patterns in studies across time, country, study design, topics, and funders. We identified 213 eligible studies, which were covered in 534 publications. We identified studies in 33 of the 48 sub-Saharan African countries, with the majority in east and southern Africa. The predominant study topics were HIV (36.4%), nutrition (20%), and malaria (16.3%), with very few publications on hypertensive disorders of pregnancy (6.4%), ante/postpartum hemorrhage (3.7%), and sexually transmitted infections (3.2%). More studies were cohorts (115/213; 54%) than clinical trials. The National Institutes of Health (31.5%), Bill and Melinda Gates Foundation (22.1%), and USAID (10.8%) were the largest research funders. Identifying research trends and mismatches between research topics and disease burden provides useful information for guiding future research prioritization. In particular, gaps exist for studies on hypertensive disorders of pregnancy and ante/postpartum hemorrhage, among the top causes of maternal mortality in sub-Saharan Africa.

Mapping the Landscape of Team Roles: A Cluster Analysis of Key Authors

This paper is a continuation of the presentation of results from a systematic literature review aimed at identifying key authors in the field of team roles and grouping them into clusters of interconnected authors. It aims to define clusters of authors focusing on team roles. The results of this work can serve to facilitate future researchers' orientation to the different typologies of team roles. The defined clusters can also be used by practitioners in the field due to the clarity of studies describing team roles. The methodology utilized in this study involved a systematic literature review followed by an analysis of author relationships through systematic literature mapping. As described by Soaita et al (2020), systematic literature mapping is considered a valuable tool for comprehensively understanding the structure of a specific topic. Following the guidelines proposed by Kuckartz and Rädiker (2019) for conducting a literature review based on literature search, we proceeded through the described phases. The obtained results have brought about surprising insights, particularly the strongly developed cluster around J. E. Mathieu. The cluster centred around S. K. Parker is also interesting in terms of its gradual linking pattern, where authors build upon each other's work gradually. The presented results serve as an initial exploratory input for further research on theories, concepts and models of typologies and taxonomies. The groups of approaches to team roles depicted in this study clarify the

Predictors of weaning failure in ventilated intensive care patients: a systematic evidence map.

Ventilator weaning is of great importance for intensive care patients in order to avoid complications caused by prolonged ventilation. However, not all patients succeed in weaning immediately. Their spontaneous breathing may be insufficient, resulting in extubation failure and the subsequent need for reintubation. To identify patients at high risk for weaning failure, a variety of potential predictors has already been examined in individual studies and meta-analyses over the last decades. However, an overview of all the predictors investigated is missing. To provide an overview of empirically investigated predictors for weaning failure. A systematic evidence map was developed. To this end, we conducted a systematic search in the Medline, Cochrane, and CINAHL databases in December 2023 and added a citation search and a manual search in June 2024. Studies on predictors for weaning failure in adults ventilated in the intensive care unit were included. Studies on children, outpatients, non-invasive ventilation, or explanatory factors of weaning failure were excluded. Two reviewers performed the screening and data extraction independently. Data synthesis followed an inductive approach in which the predictors were thematically analyzed, sorted, and clustered. Of the 1388 records obtained, 140 studies were included in the analysis. The 112 prospective and 28 retrospective studies investigated a total of 145 predictors. These were assigned to the four central clusters 'Imaging procedures' (n = 22), 'Physiological parameters' (n = 61), 'Scores and indices' (n = 53), and 'Machine learning models' (n = 9). The most frequently investigated predictors are the rapid shallow breathing index, the diaphragm thickening fraction, the respiratory rate, the P/F ratio, and the diaphragm excursion. Predictors for weaning failure are widely researched. To date, 145 predictors have been investigated with varying intensity in 140 studies that are in line with the current weaning definition. It is no longer just individual predictors that are investigated, but more comprehensive assessments, indices and machine learning models in the last decade. Future research should be conducted in line with international weaning definitions and further investigate poorly researched predictors. Registration, Protocol: https://doi.org/10.17605/OSF.IO/2KDYU.

Sustainable Development Goals and wellbeing for resilient societies: shocks and recovery

AbstractThe ‘decade of action’ intended to accomplish the ambitious 17 Sustainable Development Goals (SDGs) faces notable challenges. Our investigation into the impact of the COVID-19 crisis on SDG progress reveals important lessons for shaping effective policy interventions to ensure resilient societies and overall well-being. Through systematic mapping and a rapid review approach, our analysis reveals that nearly 90% of the SDGs, specifically 144 targets, were adversely affected by the COVID-19 pandemic. Yet, there is a glimmer of opportunity: 66 targets stand to gain from the crisis-induced transformations, provided that the right choices are made. Achieving this goal demands a comprehensive approach and decisive leadership to steer an inclusive economic recovery that also safeguards the environment while safeguarding the environment. The intricate interplay between the ongoing planetary and post-COVID-19 crises, environmental challenges, and conflicts underscores the need for a proactive, deliberate and well-informed approach, marked by collaborative decision-making, which is imperative for effectively steering the ‘decade of action’ toward achieving the SDGs. These complex challenges demand collective, decisive action, all with the overarching aim of securing a just and sustainable future for all.

Green IN Artificial Intelligence from a Software Perspective: State-of-the-Art and Green Decalogue

This work presents a structured view of the state-of-the-art research on Artificial Intelligence (AI), from the point of view of efficiency and reduction of the energy consumption of AI software. We analysed the current research on energy consumption of AI algorithms and its improvements, which gave us a starting literature corpus of 2,688 papers that we identified as Green AI with a software perspective. We structure this corpus into Green IN AI and Green BY AI, which led us to discover that only 36 of them could be considered Green IN AI. After some quick insights about Green BY AI, we then introduce our main contribution: a systematic mapping of Green IN AI. We provide an in-depth analysis of the AI models that we observed during the mapping, and what solutions have been proposed for improving their energy efficiency. We also analyse the energy evaluation methodologies employed in Green IN AI, discovering that most papers opt for a software-based energy estimation approach and 27% of all papers do not document their methodology. We finish by synthetising our insights from the mapping into a Decalogue of Good Practices for Green AI.

Complexity‐Building Exhaustive Dearomatization of Benzenoid Aromatics within an ESIPT‐Initiated Three‐Step Photochemical Cascade.

AbstractDearomative cycloadditions offer rapid access to complex 3D molecular architectures, commonly via a sp2‐to‐sp3 rehybridization of two atoms of an aromatic ring. Here we report that the 6e π‐system of a benzenoid aromatic pendant could be exhaustively depleted within a single photochemical cascade. An implementation of this approach involves the initial dearomative [4+2] cycloaddition of the Excited State Intramolecular Proton Transfer (ESIPT)‐generated azaxylylene, followed by two consecutive [2+2] cycloadditions of auxiliary π moieties strategically positioned in the photoprecursor. Such photochemical cascade fully dearomatizes the benzenoid aromatic ring, saturating all six sp2 atoms to yield a complex sp3‐rich scaffold with high control of its 3D molecular shape, rendering it a robust platform for rapid systematic mapping of underexplored chemical space. Significant growth of molecular complexity—starting with a modular synthesis of photoprecursors from readily available building blocks—is quantified by Böttcher score calculations.

Application of Spectral Imaging and Vegetation Index in Latin American Coffee Production: A Systematic Mapping

ABSTRACTCoffee production is a crucial economic, social, and cultural pillar in Latin America, facing numerous challenges, including integrating technological advancements such as multispectral imaging. This approach offers multiple advantages for coffee production; however, a knowledge gap in the domain is the need to methodologically review the available empirical evidence to delineate the field and the study region. Therefore, this systematic mapping aims to map the scientific corpus of multispectral imagery and vegetation index implemented in coffee production in the Latin American region. The study followed the PRISMA protocol; 42 primary studies were analyzed to identify key trends and research gaps. The main result of this research is that NDVI emerged as the most widely used spectral index, with applications in estimating critical biophysical parameters such as biomass and chlorophyll content. Other indices such as GNDVI, NDRE, and SAVI also proved valuable in assessing coffee plant health and development. There was an emerging trend to integrate multispectral imaging with machine learning techniques, promising greater accuracy in data interpretation. The study also revealed a concentration of research efforts in selected Latin American countries, particularly Brazil, indicating opportunities to expand research in other coffee‐producing regions. The study's main conclusion is that multispectral imaging, mainly through vegetation index, has emerged as a valuable tool for phenological monitoring and management of coffee production, offering several advantages over traditional methods. Finally, this review contributes to the existing knowledge base and identifies future research directions for applying multispectral imagery to sustainable coffee production in Latin America.

A Systematic Mapping Study and a Review of the Optimization Methods of Structures in Architectural Design

Structural optimization has gained popularity in modern structural design, helping to reduce material consumption while maintaining the structural performance of buildings. This process also significantly influences the architectural appearance, affecting various aspects such as cross-section sizing, structural forms, and the layout of structural members. Beyond minimizing materials or costs, structural optimization can serve as a powerful tool for making architecture more visually appealing. However, with the wide variety of structural optimization methods proposed, gaining a comprehensive overview has become challenging. To address this, a systematic mapping study has been conducted, focusing on methods introduced over the past decade. The relevant journal articles are categorized based on several factors, including types of optimization, materials used, structural typologies, areas of application, and optimization objectives. The results of this study provide both a broad overview of recent developments in structural optimization and valuable insights into research-rich and under-explored areas. Moreover, the paper discusses which types of structural optimization are more relevant when applied as part of the architectural design process. It is suggested that future research should focus on identifying gaps and challenges in effectively applying structural optimization to architectural design, thus enhancing both efficiency and aesthetic potential.

11099 Case Series: Diagnosis and Treatment of Four Rare Cancers by a Single Surgeon Due to Systematic Mapping and Near Contact Techniques

11099 Case Series: Diagnosis and Treatment of Four Rare Cancers by a Single Surgeon Due to Systematic Mapping and Near Contact Techniques

Single-cell transcriptional mapping reveals genetic and non-genetic determinants of aberrant differentiation in AML.

In acute myeloid leukemia (AML), genetic mutations distort hematopoietic differentiation, resulting in the accumulation of leukemic blasts. Yet, it remains unclear how these mutations intersect with cellular origins and whether they converge upon similar differentiation patterns. Single-cell RNA sequencing (scRNA-seq) has enabled high-resolution mapping of the relationship between leukemia and normal cell states, yet this application is hampered by imprecise reference maps of normal hematopoiesis and small sample sizes among patient cohorts. As a first step we constructed a reference atlas of human bone marrow hematopoiesis from 263,519 single-cell transcriptomes spanning 55 cellular states, that was benchmarked against independent datasets of immunophenotypically pure hematopoietic stem and progenitor cells. Using this reference atlas, we mapped over 1.2 million single-cell transcriptomes spanning 318 AML, mixed phenotype acute leukemia (MPAL), and acute erythroid leukemia (AEL) samples. This large-scale analysis, together with systematic mapping of genotype-to-phenotype associations between driver mutations and differentiation landscapes, revealed convergence of diverse genetic alterations on twelve recurrent patterns of aberrant differentiation in AML. This included unconventional lymphoid and erythroid priming linked to RUNX1 and TP53 mutations, respectively. We also identified non-genetic determinants of AML differentiation such as two subgroups of KMT2A-rearranged AML that differ in the identity of their leukemic stem cells (LSCs), likely reflecting distinct cellular origins. Furthermore, distinct LSC-driven hierarchies can co-exist within individual patients, providing insights into AML evolution. Together, precise mapping of normal and malignant cell states provides a framework for advancing the study and disease classification of hematologic malignancies thereby informing therapy development.

Integrated Climate Change Mitigation and Public Health Protection Strategies: The Case of the City of Bologna, Italy

Introduction: The ongoing process of global warming, driven by the escalating concentration of greenhouse gases generated by human activities, especially in urban areas, significantly impacts public health. Local authorities play an important role in health promotion and disease prevention, and some aim to achieve net-zero greenhouse gas emissions. There is a consistent action underway to reach this goal, hence the need for mapping and implementing effective strategies and regulations. Materials and Methods: This study includes the analysis of policy guidelines adopted by the city of Bologna, consulted in March and April 2024. Bologna is one of the 100 cities committed to achieving climate neutrality by 2030, 20 years ahead of the EU target. To identify the strategies adopted to mitigate climate change, the following methodology was used: (i) the systematic mapping of sources and spatial planning documents; (ii) the extrapolation of goals, measures, and target indicators; and (iii) the development of an overall matrix. Results: The main findings of the study and their connection to public health pertain to the identification of key macro-areas contributing to the reduction of greenhouse gas emissions, while reducing the impact of climate change on health: (1) built environment and renewable energy sources, (2) transport and mobility, (3) energy, (4) green areas and land use, and (5) citizen support. Within these five macro-areas, 14 goals have been identified, to which a total of 36 measures correspond, and, finally, a target indicator is determined, mainly with respect to the reduction of tons of CO2 equivalent per year. Conclusions: In order to protect public health, it is evident that buildings and urban activities should not produce carbon emissions throughout their lifecycle. This paper presents a method to evaluate municipal policies regarding dual-impact solutions that address both environmental protection through sustainability strategies and public health, in compliance with the Health in All Policies (HiAP) approach.

Understanding the intersectional stigma of ageing, disability, and place: a systematic literature mapping review

Stigma is a key concept for social scientists interested in how certain groups in society are judged and treated negatively. Within housing studies this scholarship reflects longstanding interests within the discipline regarding the spatial impacts of social and urban policies on both people, and the places in which they live. We augment these debates by advocating for a more intersectional understanding of how stigma is shaped by identity. It presents findings from a systematic literature mapping review of research that has a combined focus on ageing, disability, place, and stigma across OECD countries. Given global trends around ageing populations and the impacts for health, this is an important, but often neglected aspect to stigma research. Our review highlights the advantages of combining a spatial approach to stigma with intersectional insights foregrounded in age and disability. This includes the further development of stigma as a concept from the perspective of under-represented groups: older and disabled people.

Reporting social inequalities in health dashboards: data source mapping of 14 European countries

Abstract Background Monitoring health inequalities is an essential public health task. This includes reporting social inequalities using data dashboards to inform citizens and policy-makers. To date, there is a dearth of evidence on the extent of health inequality reporting and which equity dimensions are being reported in European countries. The aim of the study is to systematically map data sources and identify the equity dimensions reported in national and subnational data sources in 14 European countries. Methods Study design is a cross-sectional data source mapping in 14 European countries (Bulgaria, Estonia, Finland, France, Germany, Greece, Hungary, Italy, Iceland, Malta, Norway, Portugal, Slovenia, Spain). We will conduct a survey among more than 400 collaborators of the EU-funded Joint Action to Prevent NCDs (JAPreventNCD) to identify existing population health dashboards at national and subnational levels. On a second stage, we will carry out a structured content audit to identify inequality dimensions and health indicators in each dashboard. The dashboard content audit will be done in duplicate by native speakers using keyword search and annotated navigation. Inequality dimensions will be categorised using PROGRESS-plus categories. We will pre-register the protocol in OSF prior to data collection and analysis. Data analysis will use a modified version of the template developed by the World Health Organization. Data analyses will be conducted in R. Work is under development but given the resources committed to JAPreventNCD, results will be ready by November 2024. Key messages • Reporting social inequalities using data dashboards to inform citizens and policy-makers is an essential public health task. • Systematic data source mapping can be a reliable, efficient method to monitor the routine reporting of health inequalities.

Key competencies for global health research: systematic literature review and mapping

Abstract Background Despite a boom in global health programmes and trainings, there is a lack of clarity and standardisation about which competencies are essential for researchers in global health, who stem from diverse disciplines and backgrounds. The objective was to map key competencies for global health research and approaches to progressively develop them in education and training. Methods We performed a systematic review in English in PubMed/MEDLINE, Web of Science, and Psychinfo/EBCSO host of literature published since 1 January 2010. 1827 articles were screened in duplicate. Data was extracted from 84 publications about focus in global health, recommended competencies and educational approaches, with two researchers giving a relevancy rating. AI-assisted extraction was conducted on 40 high-relevance publications to garner further information, informing development and application of a coding framework to these articles. Results Emerging results point to eight main domains and numerous subdomains related to competencies seen as critical for global health research. In addition to traditionally emphasised cognitive competencies (e.g. methodological), the literature underlined the importance of critical analyse of how systems related to globalisation, political economy and structural injustice shape health at local level. Also highlighted was the need for more focus on affective and practical competencies for conducting global health research in alignment with equity principles, including through innovative pedagogical approaches. Conclusions Our review identifies competencies seen as essential for global health researchers, including skills to critically analyse geopolitical, colonial and structural drivers, as well as self-reflexivity, (cultural) humility and other key affective competencies. It also highlights, however, the significant diversity of perspectives, lack of consensus, and ongoing disconnect between principles and practice. Key messages • Greater clarity and consensus is needed around the specific competencies required to work as a researcher in global health, taking account of diversity across disciplines, sectors and stages. • Global health researchers require skills to critically analyse geopolitical, colonial and structural drivers, as well as self-reflexivity, (cultural) humility and other key affective competencies.

Editorial

Dear Readers, It gives me great pleasure to announce the tenth regular issue of 2024. I would like to thank all the authors for their sound research papers and the editorial board and our guest reviewers for their extremely valuable reviews and suggestions for improvement. These contributions and the generous support of the consortium members enable us to run our journal and maintain its quality. I would also like to thank our broader community for reading and incorporating sound J.UCS papers into their research. Still, I would like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and emerging trends. In this regular issue, I am very pleased to introduce six accepted papers involving 17 authors from six different countries (Argentina, Brazil, Ecuador, Hong Kong, India, Saudi Arabia). Álex dos Santos Moura, Fábio Gomes Rocha, and Michel S. Soares from Brazil propose in their research a recommendation tool based on information retrieval to assist developers in choosing the suitable microservices pattern to solve a given problem. In a collaborative research effort between Ecuador and Argentina, Gonzalo P. Espinel-Mena, José L. Carrillo-Medina, Eddie E. Galarza, and Mario Matias Urbieta discuss a systematic mapping of configuration management activities in software product line. Edward Kai Fung Dang, Robert Wing Pong Luk, and Qing Li from Hong Kong contribute to the forum for negative results with their study on word bigrams for pseudo-relevance feedback in information retrieval. Prateek Thakral and Yugal Kumar from India present in their work an improved water flow optimizer (IWFO) algorithm for cluster analysis that can address the issues of traditional and heuristic algorithms. Samit Bhanja, Banani Ghose, and Abhishek Das from India highlight their findings on multi-step-ahead time series forecasting using a deep learning and fuzzy time series-based error correction method. And last but not least, Abdullilah A. Alotaibi and Salman A. AlQahtani from Saudi Arabia present in their research an intelligent distributed channel selection framework with hybrid mode selection for interference mitigation in D2D based 5G networks.  Enjoy Reading! Best regards,  Christian Gütl, Managing Editor Graz University of Technology, Graz, Austria

Recent One Decade Trends in Mathematical Representation Research: Systematic Mapping Study

Research can change over time and can be influenced by technological developments, educational trends, and current social issues. Developments on trends in mathematical representation research over the past 10 years are discussed in this systematic mapping study (SMS). The question of review research with the systematic mapping study method is how the trend of mathematical representation research over the last 1 decade and what new topics have the opportunity to be researched by future researchers related to the themes of mathematical representation. The method used in this review is the PRISMA method which includes 5 stages carried out: 1) defining eligibility criteria, 2) determining information sources, 3) data selection, 4) data collection, and 5) data collection. In this systematic mapping study, it starts from searching for articles on the topic of mathematical representation during the last 1 decade, namely the range of 2013-2023, articles obtained from the scopus database in July 2023 with the keywords "representations" AND : Mathematics" initial data obtained 1907 articles after the exclusion process obtained 120 articles which were then analyzed using R-Studio and Vos-Viewer tools. The results of SMS obtained the relationship of representation topics in the last 10 years of research with the topics of visual, computer software, computer aid instruction, data mining, open source software, network architecture, natural language processing systems, intelligent systems and information analysis. In addition, research over the past 1 decade on the topic of representation has led more to data mining, security of data and STEM. Artificial Intelligence or artificial intelligence is the latest topic that over the past 3 years has grown in various articles that deal with the theme of mathematical representation and accompanied by the theme of multi-representation. The evolution of research topics related to mathematical representations that used to be only related to visual representations and image representations now leads to computer programs, programming algorithms and artificial intelligence, this shows that over the past 1 decade there has been an evolution of research in the implementation of representations in technology.

A Systematic Mapping of Configuration Management Activities in Software Product Line

In the software product line (SPL), configuration management (CM) is a multidimensional problem that is taking great attention in software development.  Although much research has been developed on this topic, there is no clear view of the current state of it. In this study, we used a systematic method to develop a map of configuration management across product lines to classify relevant literature. The resulting map provides an overview of this research through the identification of the main activities of the CM, the types and trends of research as well as the maturity of existing contributions. Because the CM in SPL is still in its formative stage, we believe that this work will contribute to the process of providing a more common and coherent conceptual basis for its understanding. In addition, it can help to detect important research problems and gaps.

How mature is requirements engineering for AI-based systems? A systematic mapping study on practices, challenges, and future research directions

AbstractArtificial intelligence (AI) permeates all fields of life, which resulted in new challenges in requirements engineering for artificial intelligence (RE4AI), e.g., the difficulty in specifying and validating requirements for AI or considering new quality requirements due to emerging ethical implications. It is currently unclear if existing RE methods are sufficient or if new ones are needed to address these challenges. Therefore, our goal is to provide a comprehensive overview of RE4AI to researchers and practitioners. What has been achieved so far, i.e., what practices are available, and what research gaps and challenges still need to be addressed? To achieve this, we conducted a systematic mapping study combining query string search and extensive snowballing. The extracted data was aggregated, and results were synthesized using thematic analysis. Our selection process led to the inclusion of 126 primary studies. Existing RE4AI research focuses mainly on requirements analysis and elicitation, with most practices applied in these areas. Furthermore, we identified requirements specification, explainability, and the gap between machine learning engineers and end-users as the most prevalent challenges, along with a few others. Additionally, we proposed seven potential research directions to address these challenges. Practitioners can use our results to identify and select suitable RE methods for working on their AI-based systems, while researchers can build on the identified gaps and research directions to push the field forward.

Genetic polymorphisms and bruxism: A scoping review

BackgroundRecent studies have highlighted the multifactorial nature of bruxism, with behavioral, psychosocial, and physiological factors, including genetic predisposition, contributing to its development. However, the role of genetic markers in determining susceptibility to bruxism remains poorly understood, with limited studies offering significant findings. ObjectivesTo identify the current knowledge to investigate the susceptibility of genetic markers for sleep (SB) and/or awake bruxism (AB). Materials and methodsSeven electronic databases and two grey literature platforms were searched up to January 2024. We included studies that related different types of genes and/or genetic polymorphisms with different types of bruxism, regardless of age or sex of the participants. To be included the study must have described the form of detection of bruxism. ResultsA total of 21 reports were included. Of these, 16 were primary research reports. The remaining five articles consisted of four systematic reviews and a literature review incorporating a systematic mapping process, and network visualization. Within the pool of 16 primary study reports, seven focused on the association of genetic polymorphisms with both SB and AB, while seven concentrated solely on the association with SB. One primary study reported results related to probable AB and one article did not specify the bruxism type. Regarding all the studied genes and polymorphisms, significant association results were obtained for 15 polymorphisms from 11 different genes. Self-reported SB was associated with genes from the serotonergic (5HTR2A) and dopaminergic pathways (DRD2, DRD3, and ANKK1), as well as genes encoding enzymes (COMT and MMP9) and proteins (ACTN3 and ANKK1). Instrumentally reported SB was linked only to the reverse telomerase gene (TERT). Self-reported AB was associated with the ACTN3 and ANKK1 genes. ConclusionThis review identified 30 genes and 56 polymorphisms variations potentially associated with either SB or AB. However, few presented significant results regarding positive associations, mostly acting at neurotransmitter pathways. The authors recommend further studies to determine the susceptibility of genetic markers as a risk factor for bruxism.