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Cherukuri R, Kammala AK, Thomas TJ, Saylor L, Richardson L, Kim S, Ferrer M, Acedo C, Song MJ, Gaharwar AK, Menon R, Han A. High-Throughput 3D-Printed Model of the Feto-Maternal Interface for the Discovery and Development of Preterm Birth Therapies. ACS APPLIED MATERIALS & INTERFACES 2024; 16:41892-41906. [PMID: 39078878 DOI: 10.1021/acsami.4c08731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
Spontaneous preterm birth (PTB) affects around 11% of births, posing significant risks to neonatal health due to the inflammation at the fetal-maternal interface (FMi). This inflammation disrupts immune tolerance during pregnancy, often leading to PTB. While organ-on-a-chip (OOC) devices effectively mimic the physiology, pathophysiology, and responses of FMi, their relatively low throughput limits their utility in high-throughput testing applications. To overcome this, we developed a three-dimensional (3D)-printed model that fits in a well of a 96-well plate and can be mass-produced while also accurately replicating FMi, enabling efficient screening of drugs targeting FMi inflammation. Our model features two cell culture chambers (maternal and fetal cells) interlinked via an array of microfluidic channels. It was thoroughly validated, ensuring cell viability, metabolic activity, and cell-specific markers. The maternal chamber was exposed to lipopolysaccharides (LPS) to induce an inflammatory state, and proinflammatory cytokines in the culture supernatant were quantified. Furthermore, the efficacy of anti-inflammatory inhibitors in mitigating LPS-induced inflammation was investigated. Results demonstrated that our model supports robust cell growth, maintains viability, and accurately mimics PTB-associated inflammation. This high-throughput 3D-printed model offers a versatile platform for drug screening, promising advancements in drug discovery and PTB prevention.
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Affiliation(s)
- Rahul Cherukuri
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas 77840, United States
| | - Ananth Kumar Kammala
- Division of Basic Science and Translational Research, Department of Obstetrics & Gynecology, The University of Texas Medical Branch at Galveston, Galveston, Texas 77555, United States
| | - Tilu Jain Thomas
- Division of Basic Science and Translational Research, Department of Obstetrics & Gynecology, The University of Texas Medical Branch at Galveston, Galveston, Texas 77555, United States
| | - Leah Saylor
- Division of Basic Science and Translational Research, Department of Obstetrics & Gynecology, The University of Texas Medical Branch at Galveston, Galveston, Texas 77555, United States
| | - Lauren Richardson
- Division of Basic Science and Translational Research, Department of Obstetrics & Gynecology, The University of Texas Medical Branch at Galveston, Galveston, Texas 77555, United States
| | - Sungjin Kim
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas 77840, United States
| | - Marc Ferrer
- 3D Tissue Bioprinting Laboratory, National Centre for Advancing Translational Sciences, National Institute of Sciences, Bethesda, Maryland 20892, United States
| | - Cristina Acedo
- 3D Tissue Bioprinting Laboratory, National Centre for Advancing Translational Sciences, National Institute of Sciences, Bethesda, Maryland 20892, United States
| | - Min Jae Song
- 3D Tissue Bioprinting Laboratory, National Centre for Advancing Translational Sciences, National Institute of Sciences, Bethesda, Maryland 20892, United States
| | - Akhilesh K Gaharwar
- Department of Biomedical Engineering, Texas A&M University, College Station, Texas 77840, United States
| | - Ramkumar Menon
- Division of Basic Science and Translational Research, Department of Obstetrics & Gynecology, The University of Texas Medical Branch at Galveston, Galveston, Texas 77555, United States
| | - Arum Han
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas 77840, United States
- Department of Biomedical Engineering, Texas A&M University, College Station, Texas 77840, United States
- Department of Chemical Engineering, Texas A&M University, College Station, Texas 77840, United States
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Nonmedical Determinants of Congenital Heart Diseases in Children from the Perspective of Mothers: A Qualitative Study in Iran. Cardiol Res Pract 2021; 2021:6647260. [PMID: 34447593 PMCID: PMC8384533 DOI: 10.1155/2021/6647260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 06/17/2021] [Accepted: 08/12/2021] [Indexed: 11/17/2022] Open
Abstract
Introduction Mortality due to noncommunicable diseases has increased in the world today with the advent of demographic shifts, growing age, and lifestyle patterns in the world, which have been affected by economic and social crises. Congenital heart defects are one of the forms of diseases that have raised infant mortality worldwide. The objective of present study was to identify nonmedical determinants related to this abnormality from the mother's perspectives. Methods This research was a qualitative study and the data collection method was a semistructured interview with mothers who had children with congenital heart diseases referring to the Shahid Rajaei Heart Hospital in Tehran, Iran. A thematic analysis approach was employed to analyze transcribed documents assisted by MAXQDA Plus version 12. Results Four general themes and ten subthemes including social contexts (social harms, social interactions, and social necessities), psychological contexts (mood disorders and mental well-being), cultural contexts (unhealthy lifestyle, family culture, and poor parental health behaviors), and environmental contexts (living area and polluted air) were extracted from interviews with mothers of children with congenital heart diseases. Conclusions Results suggest that factors such as childhood poverty, lack of parental awareness of congenital diseases, lack of proper nutrition and health facilities, education, and lack of medical supervision during pregnancy were most related with the birth of children with congenital heart disease from mothers' prospective. In this regard, targeted and intersectorial collaborations are proposed to address nonmedical determinants related to the incidence of congenital heart diseases.
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Antenatal Antidepressant Prescription Associated With Reduced Fetal Femur Length but Not Estimated Fetal Weight: A Retrospective Ultrasonographic Study. J Clin Psychopharmacol 2021; 41:571-578. [PMID: 34412105 PMCID: PMC8440368 DOI: 10.1097/jcp.0000000000001446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
PURPOSE/BACKGROUND Antidepressants are among the most frequently prescribed medications during pregnancy and may affect fetal weight. Associations between antenatal antidepressant use and ultrasonographic measures of fetal development have rarely been examined. We hypothesized that the prescription of an antenatal antidepressant would be associated with lower estimated fetal weight (EFW). METHODS/PROCEDURES A retrospective analysis of routine ultrasonographic data extracted from electronic medical records was performed on a cohort of pregnant women with psychiatric diagnoses and grouped according to the presence of an antenatal antidepressant prescription (n = 32 antidepressant-prescribed and n = 44 antidepressant prescription-free). After stratifying for gestational age, comparisons included 13 ultrasonographic parameters, frequency of oligohydramnios and polyhydramnios and growth deceleration, and maternal serum protein markers assessed per routine care, including α-fetoprotein, free β-human chorionic gonadotropin, and unconjugated estriol levels, using t tests, nonparametric and Fisher tests, and effect sizes (ESs) were computed. FINDINGS/RESULTS No statistically significant EFW differences between groups at any time point were detected (P > 0.05). Antenatal antidepressant prescription was associated with lower femur length at weeks 33 to 40 (P = 0.046, ES = 0.75) and greater left ventricular diameter at weeks 25 to 32 (P = 0.04, ES = 1.18). No differences for frequency of oligohydramnios or polyhydramnios or growth deceleration were observed (P > 0.05). We did not detect group differences for maternal proteins (P > 0.05). IMPLICATIONS/CONCLUSIONS Our evidence suggested a lack of association between antenatal antidepressant prescription and lower EFW but indicated an association with lower femur length and greater left ventricular diameter in mid-late gestation. Future research should examine the clinical implications of these findings.
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