Asthma and respiratory diseasesPneumonia and Respiratory InfectionsChronic Obstructive Pulmonary Disease (COPD) ResearchInhalation and Respiratory Drug DeliverySchool Health and Nursing Education
We prepare their research opportunity report and reach out personally to introduce you — their contact details stay private.
Their published papers and profiles list institutional contact details.
This profile was built automatically from public publication records and has not yet been claimed by the researcher.
Research opportunities
Study designs adjacent to this body of work — each grounded in the published record and scoped so a trainee could run it.
Claim your researcher profile
This profile was built from your public publication record — claim it to manage it.
How do specific maternal microbiota profiles (gut, oral, or vaginal) during gestation correlate with the development of gestational diabetes mellitus (GDM) and subsequent long-term metabolic health in offspring?
Why this gap exists: While recent reviews [8] confirm GDM alters maternal gut microbiota and neonatal health, and older studies [0] note dysbiosis across maternal sites, the retrieved evidence lacks direct, longitudinal studies correlating specific gestational maternal microbiota profiles with the *long-term* metabolic health of offspring, leaving the core question unresolved.
Microbes in the Moonlight: How the Gut Microbiota Influences Sleep — arXiv preprint, 2025
To what extent do changes in the maternal microbiota (gut, oral, or vaginal) during pregnancy mediate the relationship between maternal perinatal anxiety/depression and the neurodevelopmental outcomes of the offspring?
Why this gap exists: While recent studies confirm associations between maternal mental health and microbiota composition (Abstract 5, 8) and suggest the microbiome-gut-brain axis influences neurodevelopment (Abstract 0, 2), the retrieved evidence does not contain studies that directly test the mediating role of maternal microbiota changes between perinatal anxiety/depression and offspring neurodevelopmental outcomes.
What are the specific long-term treatment strategies required to mitigate the risk of developing chronic non-communicable diseases in children born to mothers with gestational diabetes mellitus?
Why this gap exists: While the retrieved literature consistently establishes that maternal gestational diabetes mellitus (GDM) increases the long-term risk of cardiometabolic diseases in offspring [1][2][3], it focuses primarily on pathogenesis and risk association rather than defining specific, evidence-based long-term treatment strategies for the children to mitigate these risks.
What are the long-term developmental and health outcomes in children born to mothers who experienced COVID-19-related mental health stressors compared to those who did not, controlling for socioeconomic status?
Why this gap exists: While recent studies [0, 5, 6] link pandemic-related maternal distress to child neurodevelopmental issues, the retrieved evidence focuses on general pandemic exposure rather than specifically isolating COVID-19 mental health stressors while controlling for socioeconomic status, leaving the specific comparison unresolved.
What is the comparative efficacy of digital versus in-person delivery of mental health interventions for mitigating the increased risk of perinatal depression and anxiety in low-income and middle-income countries during future pandemic-like disruptions?
Why this gap exists: While abstracts [6] and [8] compare digital and in-person delivery during the pandemic, they are set in high-income contexts (Spain, unspecified high-income), and abstract [7] focuses on LMICs but lacks a comparative digital vs. in-person design, leaving the specific question of comparative efficacy in LMICs unresolved.
Detecting anxiety and depression in dialogues: a multi-label and explainable approach — de Arriba-Pérez, F., García-Méndez, S. (2024). Detecting anxiety and depression in dialogues: a multi-label and explainable approach. In Proceedings of the 3rd AIxIA Workshop on Artificial Intelligence For Healthcare (pp. 257-271), 2024
Detecting anxiety and depression in dialogues: a multi-label and explainable approach — de Arriba-Pérez, F., García-Méndez, S. (2024). Detecting anxiety and depression in dialogues: a multi-label and explainable approach. In Proceedings of the 3rd AIxIA Workshop on Artificial Intelligence For Healthcare (pp. 257-271), 2024
What is the comparative efficacy of household water treatment interventions versus improved water source infrastructure in reducing stunting among children under five in low- and middle-income countries?
Why this gap exists: While the retrieved literature confirms associations between water quality and child growth (e.g., Abstracts 2, 5, 8), no study directly compares the efficacy of household water treatment interventions against improved water source infrastructure for reducing stunting, leaving the specific comparative question unresolved.