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What is already known about this topic? COVID-19 infection in pregnancy leads to an increase in adverse maternal outcomes. Owing to paucity of data regarding SARS-CoV-2 vaccine use in pregnancy there is uncertainty regarding safety of use and subsequent pregnancy outcomes. What does this study add? Provides an overview of the available SARS-CoV-2 vaccines, their mechanisms of action and feasibility of use in pregnancy. Summarises recommendations regarding vaccination of pregnant or lactating women. Data Availability-Data sharing is not applicable to this article as no new data were created or analyzed in this study. Acknowledgements:We would like to acknowledge Mr Mohesh K Mohan for his assistance in the illustration, Ms Cecille Laureano Asibal for her administrative support.

The helix angle configuration of the myocardium is understood to contribute to the heart function, as finite element (FE) modeling of postnatal hearts showed that altered configurations affected cardiac function and biomechanics. However, similar investigations have not been done on the fetal heart. To address this, we performed image-based FE simulations of fetal left ventricles (LV) over a range of helix angle configurations, assuming a linear variation of helix angles from epicardium to endocardium. Results showed that helix angles have substantial influence on peak myofiber stress, cardiac stroke work, myocardial deformational burden, and spatial variability of myocardial strain. A good match between LV myocardial strains from FE simulations to those measured from 4D fetal echo images could only be obtained if the transmural variation of helix angle was generally between 110 and 130°, suggesting that this was the physiological range. Experimentally discovered helix angle configurations from the literature were found to produce high peak myofiber stress, high cardiac stroke work, and a low myocardial deformational burden, but did not coincide with configurations that would optimize these characteristics. This may suggest that the fetal development of myocyte orientations depends concurrently on several factors rather than a single factor. We further found that the shape, rather than the size of the LV, determined the manner at which helix angles influenced these characteristics, as this influence changed significantly when the LV shape was varied, but not when a heart was scaled from fetal to adult size while retaining the same shape. This may suggest that biomechanical optimality would be affected during diseases that altered the geometric shape of the LV.

Intrauterine hematopoietic cell transplantation (IUT), a promising therapy for congenital haematological disease, is limited by subtherapeutic donor cell chimerism (DCC). Microchimerism of maternal immune cells (MMc) trafficked into fetal IUT recipients may directly influence immune-mediated donor cell clearance. We investigated if maternal dendritic cell (DC) suppression reduces recipient alloresponsiveness to donor cells, improving DCC. IUT was performed at E14 in pregnancies resulting from crossing CD11c.DTR(B6) females and Balb/c males, with semiallogenic Balb/c or C57BL/6, or fully allogenic C3H donor cells, 24h after administering diphtheria toxin to the dam, transiently suppressing maternal DC. This resulted in reduced MMc in recipient fetuses, greatest after Balb/c transplantation, also associated with the highest DCC, and lowest with C3H. Maternal-derived T-cell receptor (TCR) clonotypes were enriched in IUT recipients and displayed substantially reduced diversity. Recipient pups with reduced MMc increased expression of regulatory T-cell subtypes, reduced expression of proinflammatory cytokines, and demonstrated enhanced TCR clonotype diversity. DCC was primarily related to donor cell type and not influenced by MMc. Our data indicate that donor cell origin and MMc are distinct factors determining IUT effectiveness. MMc independently influences DCC and recipient tolerance to donor cells and may present novel therapeutic targets to improve transplantation outcomes.

site and comparatively less leakage to peripheral organs compared with bolus injection. Preliminary experiments delivering rAAV9-ABCD1 at 0.5X10 11 GC by intracerebroventricular approach suggest behavioral improvement in the Abcd1-/-mouse despite localized expression in brain. We therefore anticipate even better performance at this dose using the outlined intrathecal pump delivery. We conclude that rAAV9-mediated ABCD1 gene transfer via intrathecal osmotic pump leads to more uniform and widespread gene delivery to CNS with reduced leakage into the systemic circulation compared with intrathecal bolus injection.

gene marking in the competitive PGK arm reached 60% in both dogs. In contrast, the EF1α arm peaked at 42 days after in vivo gene therapy and never expanded above 10%. The expansion of gene-marked lymphocytes was followed by the appearance of a therapeutic level of CD3+ T cells in both dogs ( Fig 1B). For comparison, this level of lymphocyte gene marking was achieved in only 2 of 5 dogs after 122 and 160 days, respectively, in our previous EF1α-only cohort. The dual-arm dogs exhibit normal peripheral blood cell counts, diverse TCRVΒ rearrangement, and functional response to T cell activating mitogen. These data highlight the utility of the competitive in vivo gene therapy experiments to explore key parameters of vector design and delivery for primary immunodeficiencies and other blood diseases.

The objective of the study is to investigate the effect of Nuchal Fold (NF) in predicting Fetal Growth Restriction (FGR) using machine learning (ML), to explain the model's results using model-agnostic interpretable techniques, and to compare the results with clinical guidelines. This study used second-trimester ultrasound biometry and Doppler velocimetry were used to construct six FGR (birthweight < 3rd centile) ML models. Interpretability analysis was conducted using Accumulated Local Effects (ALE) and Shapley Additive Explanations (SHAP). The results were compared with clinical guidelines based on the most optimal model. Support Vector Machine (SVM) exhibited the most consistent performance in FGR prediction. SHAP showed that the top contributors to identify FGR were Abdominal Circumference (AC), NF, Uterine RI (Ut RI), and Uterine PI (Ut PI). ALE showed that the cutoff values of Ut RI, Ut PI, and AC in differentiating FGR from normal were comparable with clinical guidelines (Errors between model and clinical; Ut RI: 15%, Ut PI: 8%, and AC: 11%). The cutoff value for NF to differentiate between healthy and FGR is 5.4 mm, where low NF may indicate FGR. The SVM model is the most stable in FGR prediction. ALE can be a potential tool to identify a cutoff value for novel parameters to differentiate between healthy and FGR.