Introduction: Uniform chromosome abnormalities are commonly seen in early pregnancy loss, with analyses of the product of conception suggesting the presence of mosaic autosomal trisomy in ∼10% of cases. Although chromosomal mosaicism occurs in a minority of embryos, their relative commonality and uncertainty regarding associated transfer outcomes have created discussion at both the clinical and research levels, highlighting the need to understand the clinical conditions associated with the incidence of embryo mosaicism.
Methods: We took advantage of a preimplantation genetic testing for aneuploidy (PGT-A) database created from 2019 to 2022 in more than 160 in vitro fertilization (IVF) clinics in Brazil, the second-largest world market for IVF. We carried out descriptive statistical and associative analyses to assess the proportions of mosaicism associated with clinical conditions and reported incidence by chromosome, clinic origin, and biopsy operator.
Results: Chromosomal analysis revealed that most mosaic aneuploidies occurred in the last three chromosomes, with 78.06% of cases having only one chromosome affected. Low mosaicism in trisomy represented the most ordinary form, followed by low mosaicism in monosomy. We identified associations between low (negatively-associated) and high mosaicism (positively-associated) and maternal age, indication (male factor and uterus/ovarian factor negatively associated with low and high mosaic, respectively), day of blastocyst development (day five has an overall better outcome), morphology grade (lower quality increased the chances of low and high mosaicism), origin (vitrified oocyte and embryo increased the rates of low and high mosaicism, respectively), and embryo sex (male embryos negatively associated with low mosaic).
Discussion: With these results, we hope to foster an improved understanding of the chromosomal mosaicism linked with distinct clinical conditions and their associations in Brazil.
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http://dx.doi.org/10.3389/frph.2023.1132662 | DOI Listing |
Glob Ment Health (Camb)
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View Article and Find Full Text PDFThe aging population presents critical challenges to global healthcare systems, with Japan expected to have 35% of its population aged 65 or older by 2040. Older adults often experience multimorbidity, cognitive impairments, and physical frailties, increasing healthcare utilization and costs. Traditional medical approaches that focus on organ-specific diagnoses are insufficient for addressing these multifaceted needs.
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Medical Robot Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
This study developed an artificial intelligence (AI) system using a local-global multimodal fusion graph neural network (LGMF-GNN) to address the challenge of diagnosing major depressive disorder (MDD), a complex disease influenced by social, psychological, and biological factors. Utilizing functional MRI, structural MRI, and electronic health records, the system offers an objective diagnostic method by integrating individual brain regions and population data. Tested across cohorts from China, Japan, and Russia with 1,182 healthy controls and 1,260 MDD patients from 24 institutions, it achieved a classification accuracy of 78.
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