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Consensus Conference Series on Dysglycemia‑Based Chronic Disease (DBCD) in Latin America: The Chilean Transculturalization Cover

Consensus Conference Series on Dysglycemia‑Based Chronic Disease (DBCD) in Latin America: The Chilean Transculturalization

Open Access
|Jul 2026

Figures & Tables

Table 1

Summary of Affirmed and Emergent Concepts Based on Five Critical Questions.

QUESTIONAFFIRMED CONCEPTSEMERGENT CONCEPTS
Question 1
What is a comprehensive approach to T2D care?
The T2D approach must be comprehensive (addressing modifiable risk factors that impel DBCD and lead to complications) and provided through the DBCD chronic care model.DBCD broadens traditional T2D chronic care models to include relevant social, environmental, and cultural factors and therefore should be used in Chile.
Question 2.
What is prediabetes and is it important to diagnose?
Although it is associated with the presence of complications, prediabetes is considered a predisease and not a disease.Prediabetes, as stage 2 of the DBCD model, is an actionable condition. Prediabetes should be prevented, and if identified, treated.
The Prediabetes definition is based on glycemia cutoffs associated with a stipulated statistical risk for T2D.Lower cutoffs for prediabetes should be used for Latin American populations. Treatment goals for prediabetes are based on cardiorenal, neuropathic, and cognitive impairment outcomes.
Question 3
Is the diagnosis of DBCD useful in Chile and should screening and case finding be recommended?
Detection and treatment of DBCD is typically late (when T2D is diagnosed) and needs to occur earlier.Leveraging the DBCD model will expose opportunities for earlier detection (i.e., before actual T2D with/without complications) and improve outcomes.
FINDRISC is a useful T2D risk screening tool globally that is validated for the Latino population and may be useful for Chile.FINDRISC should be adopted in Chile as a T2D screening tool and implemented via eHealth technology over social networks.
Dysglycemia is not associated with increased adiposity in certain Latino populations.OGTT should be performed in any Chilean patient with a cardiometabolic risk factor regardless of age or BMI.
Question 4
What are the key features of a Chilean transcultural approach to DBCD?
Current chronic care models for T2D do not specifically consider transcultural factors though they should be considered for more precise clinical management.The transculturalized DBCD model, incorporating concepts from the validated tDNA in the region should be implemented as part of T2D care in Chile.
Migrant population health imposes a challenge for Chilean health systems and urgently needs to be addressed.Vulnerable migrant populations should be included in transculturalized DBCD recommendations in Chile.
Question 5
What are the core Chilean lifestyle interventions for each DBCD stage?
Prioritizing lifestyle medicine in T2D care is a significant practice gap that can be addressed by implementing the DBCD model.Specific Chilean transcultural adaptations of lifestyle interventions pertaining to each DBCD stage should be investigated, taught, and implemented.
The Coronavirus disease 2019 pandemic increased awareness of this practice gap and accelerated the use of telemedicine modalities.eHealth technologies can facilitate this process of transcultural lifestyle medicine in T2D care in Chile.

Abbreviations: A1C—glycated hemoglobin A1c; DBCD—dysglycemia‑based chronic disease; eHealth—electronic health; FBG—fasting blood glucose; FINDRISC—Finnish Diabetes Risk Score; OGTT—oral glucose tolerance test; T2D—type 2 diabetes; tDNA—transcultural diabetes nutrition algorithm; WC—waist circumference.

Figure 1

A multilevel framework for the prevention and management of the dysglycemia‑based chronic disease (DBCD) in Chile, depicting how biological, cultural, healthcare system, and policy factors interact across four stages of disease progression with the goal of preventive interruption at each stage.

Abbreviations: DBCD, Diabetes and Cardiometabolic Disease; FINDRISC, Finnish Diabetes Risk Score; WC, Waist Circumference; OGTT, Oral Glucose Tolerance Test; SLC16A11, Solute Carrier Family 16 Member 11; SES, Socioeconomic Status; FONASA, Fondo Nacional de Salud; ISAPRES, Instituciones de Salud Previsional; AUGE, Acceso Universal con Garantías Explícitas; EHR, Electronic Health Record; eHealth, Electronic Health.

Table 2

Dysglycemia‑Based Chronic Disease Evidence: Survey of Chilean Evidence.

AUTHOR, YEAR (REFERENCE)NGEOGRAPHYPOPULATIONENDPOINT(S)RESULTS
Santos et al., [24]196Rural Andean provinces (>2,000 m altitude, northern Chile)Adults >20 years oldPrevalence of cardiometabolic traitsPrevalence:
  • T2D: men 1.3%, women 1.7%.

  • IGT: men 2.6%, women 4.3%.

  • Obesity: men 12.8%, women 23.5%.

  • High total cholesterol (≥ 200 mg/dl): men 36.8%, women 37.4%.

  • Hypertension: men 19.2%, women 17.7%.

  • Sedentariness: men 5.1%, women 3.4%.

Bozanic et al., [25]3586 citiesAdult 65 years old (from Diabetes and Dementia project)Risk factors, prevalence, and association of cognitive impairment and T2D
  • T2D prevalence: 17.3%

  • Higher prevalence of cognitive impairment with vs. without T2D: 30.7% vs. 13.9%

  • Risk of cognitive impairment: 2.8 times higher with vs. without T2D

Celis‑Morales et al., [26]472Los Ríos, Bio‑Bio, and MetropolitanaAdults 20–60 years oldImpact of environmental/ethnicity factors on lifestyle markers
  • HOMA‑IR (significant ethnicity x environment interaction: P = 0.0003):

    • Rural Mapuche: 1.65 ± 2.03

    • Urban Mapuche: 4.90 ± 3.05

    • Rural European: 0.82 ± 0.61

    • Urban European: 1.55 ± 1.34

  • The effect of urbanization on HOMA‑IR was greater in Mapuche compared to European individuals

  • Ethnicity (significant interactions for all P < 0.004):

    • Adiposity on HOMA‑IR

    • Sedentary time on HOMA‑IR

    • PA on HOMA‑IR

  • The effects of adiposity, sedentary time, and PA on HOMA‑IR were greater in Mapuche compared to European individuals

Arteaga et al., [27]983Limache, ValparaisoAdults 22‑28 years oldPA and cardiovascular risk factors
  • PA levels:

    • Men: 3731 ± 3923 METs‑minutes/week

    • Women: 1360 ± 2303 METs‑minutes/week

  • Insufficient PA levels:

    • 50% of women

    • 21.5% of men

  • Intense PA levels:

    • 60% of men

    • 23.4% of women

  • Inverse association PA and insulin resistance

  • High PA was protective against low HDL‑c and high TGs, particularly among men

Lange et al., [31]60 (INT)
681 (CON)
SantiagoAdults 20‑64 years old (in Cardiovascular Health Program and with T2D not on insulin)Efficacy of a telecare self‑management support model on metabolic control
  • A1C levels:

    • INT: 8.3 ± 2.3% to 8.5 ± 2.2% (maintained, P = NS)

    • CON: 7.4 ± 2.3% to 8.8 ± 2.3% (deteriorated, P < 0.001)

  • Perception of self‑efficacy:

    • INT: improved, P < 0.001

    • CON: unchanged (P = NS)

  • INT and CON: no change in adherence to medication, PA, and foot care

  • INT: increased attendance with clinic visits and decreased emergency care visits

Matute et al., [28]6,233NationalPersons 15 years old from the National Health Survey (2016–2017).Medication use and effective coverage for T2D, dyslipidemia and hypertension in Chile, considering sociodemographic variables and SDOH
  • T2D prevalence: 12.3% (majority were women 58.1%)

Beneficiaries of the Public Health System (FONASA): 80.9%
  • Medication’s use among patients with diabetes: 60.7%

    • Higher medication’s use in women

    • Lower medication’s use in younger age groups <65 years old

    • Lower medication’s use among indigenous peoples

    • Medication use increased with more years of study

  • With effective coverage for diabetes management, 54.2% had their disease controlled

Piette et al., [30]569Puente Alto, SantiagoAdults 30‑75 years old in CVD programPatient characteristics and feasibility of extending reach with structured nurse telephone contacts between outpatient encounters
  • Medications:

    • Oral agents 79%; metformin 58%; glyburide 65%; tolbutamide 8%

      • Using one oral agent: 49%

      • Using two oral agents: 40%

    • Insulin: 3%

  • CVD program visits:

    • Met the target of two visits in the past 6 months: 33%

    • Made more than three visits: 32%

    • Inadequate program contact: 27% (many in poor health)

  • Program impact:

    • Greater use of CVD program associated with higher patient satisfaction (after controlling for confounders)

    • Many participants had difficulties with lifestyle changes

    • Greater use of CVD program not associated with healthier behaviors

  • Telephone access:

    • Reported telephone access: 95%

    • Used telephone to contact clinic: 37%

    • Majority willing to use telephone care for behavior change and emotional support

Leiva et al., [29]4700 (538 with and 4,162 without T2D)NationalSubjects > 15 years old from National Health Survey (2009–2010)Associations of T2D with SDOH and lifestyle factors
  • Subjects with vs. without T2D had lower educational level, lower SES, and higher BMI and WC

  • Subjects with T2D reported:

    • Lower total PA

    • Greater consumption of salt, fruits, and vegetables

    • Higher overall dietary score

    • Higher prevalence of ex‑smokers or non‑smokers

    • Poor to fair perception of their health/wellness.

    • Increased metabolic complications

    • Higher incidence of family history of T2D

  • Greater risk for T2D with:

    • Overweight/obesity

    • Sleep > 9 hours nightly

    • Physical inactivity

    • Hypertension

  • Lowed risk for T2D with:

    • Intermediate or higher educational level

    • Good perception of well‑being/health

These data are used for transculturalizing DBCD recommendations. Since only significant ORs were reported, 95%CI was omitted for simplicity.

Abbreviations: A1C—hemoglobin A1c, BMI—body mass index; CI—confidence interval, CVD—cardiovascular disease, CON—control group, DBCD—dysglycemia‑based chronic disease; FBG—fasting blood glucose; HCP—healthcare professional; HDL‑c—high‑density lipoprotein cholesterol, HOMA‑IR—Homeostatic Model Assessment for Insulin Resistance, IGT—impaired glucose tolerance, INT—intervention group, MET—metabolic equivalent of physical activity, OR—odd ratio, PA—physical activity, SDOH—social determinants of health; SES—socioeconomic status, T2D—type 2 diabetes; TGs—triglycerides; WC—waist circumference. Values expressed as mean standard deviation.

Table 3

Dysglycemia‑Related Factors Based on Chilean Evidence.

CATEGORYAUTHOR, YEAR (REFERENCE)OBJECTIVERESULTS
GeneticsMardones et al., [32]Association of SLC16A11 gene variants with obesity and metabolic markers in those without diabetes
  • 263 non‑diabetic adults, minor allele of SLC16A11 gene prevalence 29.7%

  • Higher BMI is independently associated with polymorphic SLC16A11 genotypes

Health LiteracyCuevas et al., [33]Identify barriers, perceptions, attitudes, behaviors, and barriers in obesity care
  • Survey completed by 1,000 patients with obesity and 200 HCPs, 74% of patients with obesity and 95% of HCPs view obesity as a chronic disease

  • Most patients with obesity believe they are personally responsible for their weight loss

  • Patients identified lack of exercise and cost of weight management as significant barriers to weight loss

NutritionRatner et al., [34]Analyze eating behaviors, nutritional status, and history of previous diseases in students of higher education
  • Among 6823 students 17–29 years old, 47% skipped breakfast and 35% skipped lunch daily

  • Daily consumption of vegetables, fruits, and dairy products was low; consumption of soft drinks, chips, cakes, and sweets was high

  • 76% of students were sedentary, 40.3% were smokers, and 27.4% were overweight/ obese, with the latter group having more diabetes, hypertension, and hypercholesterolemia

  • There was poor agreement between actual nutritional status and self‑perception, particularly among males

  • Students with a food scholarship from the Ministry of Education had a higher frequency of eating lunch

Mujica‑Coopman et al., [35]Assess relationships among malnutrition, SES, and ethnicity
  • NHS conducted in 2016–2017, over 75% with excess weight

  • Women with lower SES had higher excess weight and shorter stature

  • In men, excess weight did not vary significantly by SES, but short stature was more common with low SES

  • Obesity more frequent in indigenous women and men

Cediel et al., [36]Assess the consumption of ultra‑processed foods and associations with nutrients related to non‑communicable diseases
  • Chilean population aged ≥2 years (n 4920) from a NHS (2010)

  • Ultra‑processed foods are 28.6% of total energy intake

  • Positive association between ultra‑processed food consumption and higher intake of nutrients that promote non‑communicable diseases (e.g., free sugars, total fats, saturated fats, trans fats, and increased Na:K ratio; negative association with protective nutrients (e.g., potassium and fiber)

  • Apart from sodium, inadequate nutrient intake increased with higher consumption of ultra‑processed foods

  • Reducing ultra‑processed food intake to the lowest quintile could significantly reduce nutrient inadequacy

Physical activityCelis‑Morales et al., [37]Examine PA and sedentariness prevalences by SES
  • Chilean NHS (2009–2010), 5434 persons aged ≥15 years (59% women), 19.8% did not meet PA recommendations (≤600 MET min/week)

  • PA was more prevalent among subjects ≥65 years old, and women exhibited higher rates than men

  • Subjects with higher education or income levels showed lower PA

  • The overall prevalence of sedentary behavior (>4 hours sitting per day) was 35.9%

Díaz‑Martínez et al., [38]Investigating association between self‑reported sitting time and diabetes‑related markers
  • Chilean NHS (2009–2010), 4,457 adults aged ≥18 years, the OR for T2D increased by 1.10 for men and 1.08 for women for each additional hour of sitting time, independent of age, education, smoking, BMI, and total PA

  • The prevalence of T2D was 10.2% with lowest sitting time and 17.2% with highest sitting time

Díaz‑Martínez et al., [39]Investigate the association of PA with obesity, metabolic markers, T2D, hypertension, and metabolic syndrome
  • Chilean NHS (2009–2010), n = 5,157. Inactive men and women had higher ORs (1.77 and 1.25, respectively) for obesity than physically active peers

  • Inactive men and women had higher ORs (2.47 and 1.72, respectively) for T2D than physically active peers

  • Inactive men and women had higher ORs (1.66 and 1.83, respectively) for hypertension than physically active peers

  • An association between physical inactivity and central obesity (OR: 1.92) and metabolic syndrome (OR: 1.74) was observed only in men

Risk Assessment ToolsArancibia et al., [40]Assess OGTT serum insulin levels to gauge insulin resistance
  • Retrospective analysis of 1,815 OGTTs in non‑diabetic adults aged 18–75. 75th percentiles for serum insulin levels: 60 minutes ‑ 127 μU/mL; 120 minutes ‑ 81 μU/mL

  • High correlation (r = −0.89) between HOMA‑IR and composite whole‑body insulin sensitivity index

Petermann‑Rocha et al., [41]Identify sex‑specific cut‑off points for WC for metabolic syndrome diagnosis
  • Chilean NHS (2003, 2009–2010, 2016–2017), 8,182 persons aged ≥15 years.

  • Optimal cut‑off points for WC defining metabolic syndrome were 92.3 cm for men and 87.6 cm for women

Mental HealthBastias‑González et al., [42]Determine whether psychological variables and behavioral variables predict obesity
  • 344 adults (55.8% women). Sociodemographic covariates did not significantly predict BMI

  • Physiological covariates, behavioral variables, and weight stigma were associated with BMI

  • Weight stigma was the predictor explaining the most BMI variance

These factors are used for transculturalizing DBCD recommendations.

Abbreviations: BMI—body mass index; CI—confidence interval; CON—control group; CPAP—continuous positive airway pressure; DBCD—dysglycemia‑based chronic disease; HOMA‑IR—homeostatic model assessment for insulin resistance; INT—intervention group; LDL‑c—low‑density lipoprotein cholesterol; MET—metabolic equivalent of task; NHS—National Health Survey; OGTT—oral glucose tolerance test; OR—odd ratio; PA—physical activity; SES—socioeconomic status; T2D—type 2 diabetes.

Table 4

METRICS/LSP Consensus Conference on DBCD Transculturalization in Chile—Pillar Participants.

PILLARSPARTICIPANTS
BiomedicalJeffrey I. Mechanick, MD (Chair)The Marie‑Josee and Henry R. Kravis Center for Cardiovascular Health at Mount Sinai Fuster Heart Hospital, Icahn School of Medicine at Mount Sinai, New York, NY, USA; and METRICS, USA
Ramfis Nieto‑Martinez, MD, MSc (Co‑Chair; DBCD‑CC General Coordinator)Precision Care Corp, Saint Cloud, FL, USA; Lown Scholar Program, Harvard TH Chan School of Public Health, Boston, MA, USA; FISPEVEN INC, Venezuela; and METRICS, USA
Carlos Grekin, MD (DBCD‑CC Chile Coordinator)Nutrition and Diabetes Unit, Clínica Red Salud Vitacura; Nutrition and Diabetes Service, Santiago Military Hospital; Universidad de Los Andes, Santiago, Chile; and METRICS, USA
Diana De Oliveira‑Gomes, MDDivision of Cardiovascular Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA; FISPEVEN INC, Venezuela; and METRICS, USA
Manuel Moreno, MD, MScPontificia Universidad Católica de Chile. Departamento de Nutrición, Diabetes y Metabolismo, Facultad de Medicina. Santiago, Chile
Carolina Ceron Reyes, MD, MBACentro Médico y Dental. Red Salud Arauco. Santiago, Chile.
Eduardo Figueroa PsiServicio de Neurología. Hospital Militar. Santiago, Chile
Alex Valenzuela Montero, MDFacultad de Medicina. Clínica Alemana Universidad del Desarrollo. Nutrición y Dietética, Santiago, Chile.
Víctor Saavedra, MDSociedad Chilena de Obesidad (SOCHOB), Santiago, Chile.
Claudia Cancino, RDRedSalud Arauco, Santiago, Chile
Education, Research, and Professional OrganizationsGoodarz Danae,i DSc (Keynote speaker)Director, LSP‑Harvard, Boston, MA, USA
Juan Pablo González, MD (DBCD‑CC Online Moderator)Lown Scholar Program, Harvard TH Chan School of Public Health, Boston, MA, USA; FISPEVEN INC, Venezuela, and METRICS, USA
Sandra López Arana, PhD, MSc, RDUniversidad Finis Terrae, Escuela de Nutrición y Dietética, Santiago, Chile; Lown Scholar Program, Harvard TH Chan School of Public Health, Boston, MA, USA
Báltica Cabieses, MSc, PhDUniversidad del Desarrollo, Centro de Salud Global Intercultural (CeSGI), Santiago, Chile
Guillermo Cortes, MScUniversidad Viña del Mar. Facultad de Ciencias Jurídicas, Sociales y de la Educación. Escuela de Educación, Viña del Mar. Chile
Sandra Vesga, MScUniversidad Viña del Mar. Facultad de Ciencias Jurídicas, Sociales y de la Educación. Escuela de Educación, Viña del Mar. Chile
Cecilia Albala, MD, MPHInstituto de Nutrición y Tecnología de los Alimentos (INTA), Universidad de Chile, Santiago, Chile.
Hernán Speisky Cosoy, PhDInstituto de Nutrición y Tecnología de los Alimentos (INTA), Universidad de Chile, Santiago, Chile
Francisco Pérez‑Bravo, PhDLaboratorio de Micronutrientes. Unidad de Nutrición Humana. Instituto de Nutrición y Tecnología de los Alimentos (INTA). Universidad de Chile, Santiago, Chile.
Healthcare IndustryFrancisco Javier Smart, PEBoston Consulting Group. Santiago, Chile
Arturo Avendaño Bravo, PECentral de Abastecimiento del Sistema Nacional de Servicios de Salud (CENABAST). Unidad de Inteligencia de Negocios. Santiago, Chile
Benjamín Medina, PhDNova Foods S.A. Santiago, Chile
Government/Regulatory and patient advocacyPedro Barria Gutierrez, JDUnidad de Mediación de Daños en Salud. Consejo de Defensa del Estado. Santiago, Chile
Claudia Pradenas, PatientDiabetes Araucania Temuco. Temuco, Chile

Abbreviations: DBCD Chile‑CC—Consensus Conference on Dysglycemia‑Based Chronic Disease (DBCD) Transculturalization in Chile; FISPEVEN INC—Foundation for Clinic, Public Health, and Epidemiology Research of Venezuela; METRICS—The MEchanick Transculturalization Research and Innovation ConSortium.

Table 5

Chilean DBCD Recommendations, Key Strategies, and Implementation Tactics

COMPONENTRECOMMENDATIONSKEY STRATEGIESIMPLEMENTATION TACTICS
Risk ScreeningEnhance the detection of T2D and CVD risk in the Chilean population using culturally adapted tools.Validate risk assessment tools, such as FINDRISC, tailored to Chile’s biological, cultural, and socioeconomic context.
Use the Chilean version of GLOBORISK as CVD risk score.
Use the tDNA framework to address cultural differences in tool adaptation and validation.a
Involve community leaders to pragmatize these tools, enhancing their accuracy and cultural relevance.b
Conduct studies to assess the validity and implementability of these tools across diverse settings.c
Culture and SDOHIncorporate SDOH and ethnocultural factors to DBCD care.Collect and integrate socioeconomic and cultural data from Chileans into patient care strategies.Incorporate SDOH into public policies for inclusive care.d
Utilize community resources to address SDOH.e
Use accessible language and culturally relevant resources during HCP–patient interactions.Design and embed cultural competence training into HCPs curricula.Train healthcare teams in culturally sensitive communication.f
Partner with educational institutions and community organizations.g
Healthcare Access and EquityPromote equity in healthcare access.Ensure equitable access to quality healthcare, especially for vulnerable populations.Develop initiatives like PIAAM to integrate eHealth and comprehensive support for migrants.d
Work with organizations specialized in supporting indigenous populations such as Mapuches.b
Optimize access to clinical practice guidelines recommended medications.Improve access to effective and affordable T2D treatments.Establish policies for the provision of key medications.d
Inform professionals about optimized treatment options.f
Community Engagement and EducationCommunity integration and education.Use community resources to promote education and support health initiatives.Engage local leaders to strengthen education about prediabetes and T2D.e
Support healthy lifestyle changes with infrastructural resources.h
Education on alcohol consumption risks.Promote strategies to educate the public about the risks of alcohol consumption.Include diverse disciplines in alcohol education campaigns.i
Develop policies such as taxation to dissuade unhealthy habits.d
Strengthening community‑level nutrition education efforts.Promote primary prevention by implementing nutrition education initiatives focused on local healthy foods and dietary patterns.Implement initiatives like “Healthy Food Prescriptions” and school‑based programs such as “Kiosco Verde.”d
Individualized Care and RecommendationsIndividualized nutritional recommendations.Make dietary recommendations personalized, considering socioeconomic factors.Align nutritional recommendations with patients’ individual realities. j
Conduct studies on the effectiveness of personalized diets in various populations.c
Local disease progression understanding.Understand and address T2D progression in the Chilean context.Promote longitudinal studies to understand local disease patterns.c
Partner with local institutions to collect relevant data.g
Technological and Strategic IntegrationEfficient EHR useLeverage effective use of EHR to improve data quality and comprehensive treatmentEnhance electronic record systems.k
Encourage collaboration to maximize EHR effectiveness.i
Strategic planning and prioritization.Develop a strategic plan prioritizing actions based on local needs.Involving key participants in strategic planning.b
Create policies promoting evidence‑based local interventions.d
Evaluation and EffectivenessEvidence on cost‑effectiveness.Generate local evidence on the cost‑effectiveness of T2D prevention strategies.Conduct studies to assess cost‑effectiveness and guide public health policy.c
Publish documents supporting informed and effective decision‑making.l
Communication and Language UseUsing appropriate language.Educate HCPs on the importance of respectful and non‑stigmatizing language.Train in using patient‑centered language.f
Ensure language is culturally sensitive and appropriate.a

By consensus, affirmed and emergent concepts were used to formulate recommendations, which were then interpreted as specific strategies with respective implementation tactics.

Abbreviations: DBCD—dysglycemia‑based chronic disease; EHR—electronic health record, HCP—healthcare professional; SDOH—social determinants of health; SES—socioeconomic status, T2D—type 2 diabetes.

Implementation tactics are: transculturalization,a stakeholder engagement,b research,c public policies,d community‑based interventions and engagement,e healthcare team education and training,f collaboration and networking,g lifestyle medicine infrastructure,h multidisciplinary teams,i patient‑centered approach,j health information technology,k and white papers.l

DOI: https://doi.org/10.5334/aogh.5370 | Journal eISSN: 2214-9996
Language: English
Page range: 65 - 65
Submitted on: May 30, 2026
Accepted on: Jun 19, 2026
Published on: Jul 13, 2026
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services

© 2026 Ramfis Nieto-Martinez, Carlos Grekin, Diana De Oliveira-Gomes, Juan P. Gonzalez-Rivas, Sandra Lopez-Arana, Jeffrey I. Mechanick, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.