Functional consequences of SARS-CoV-2 infection in pregnant women, fetoplacental unit, and neonate

Carvajal, Jorge; Casanello, Paola; Farías, Marcelo; Carrasco-Negue, Karina; Araujo, Kenny; Valero, Paola; Fuenzalida, Javiera; Solari, C.; Sobrevía, Luis

doi:10.1016/j.bbadis.2022.166582

Cited by 10 publications

(11 citation statements)

References 168 publications

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“…Pathogen-causing SARS-CoV-2 DNA is used for COVID-19 detection because it contains four distinct genes: Adenine (A), Cytosine (C), Guanine (G), and Thymine (T). By using four non-binary symbols, the four states 2 2 i , i = 1 can be represented by natural numbers such as [0, 1,2,3] or by colours such as [red, green, blue, yellow] [63,64].…”

Section: Galois Field Mapping/galois Fields Demappingmentioning

confidence: 99%

“…It is unknown whether the current vaccines prevent severe symptoms, hospitalisation or death. Some research on new COVID-19 variants indicates that the virus is spreading faster than in the past [1] and has effects of maternal SARS-CoV-2 infection on pregnant women, foetuses, and newborns [2]. A study on the presence of COVID-19 and its association with respiratory syncytial virus was conducted during the winter of 2020-2021 in Europe and North America [3] to determine whether SARS-CoV-2 mutates similarly globally or whether it mutates differently in specific populations [4].…”

Section: Introductionmentioning

confidence: 99%

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A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning

Soto

Zamorano-Illanes

Becerra

et al. 2023

Sensors

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This article proposes a novel method for detecting coronavirus disease 2019 (COVID-19) in an underground channel using visible light communication (VLC) and machine learning (ML). We present mathematical models of COVID-19 Deoxyribose Nucleic Acid (DNA) gene transfer in regular square constellations using a CSK/QAM-based VLC system. ML algorithms are used to classify the bands present in each electrophoresis sample according to whether the band corresponds to a positive, negative, or ladder sample during the search for the optimal model. Complexity studies reveal that the square constellation N=22i×22i,(i=3) yields a greater profit. Performance studies indicate that, for BER = 10−3, there are gains of −10 [dB], −3 [dB], 3 [dB], and 5 [dB] for N=22i×22i,(i=0,1,2,3), respectively. Based on a total of 630 COVID-19 samples, the best model is shown to be XGBoots, which demonstrated an accuracy of 96.03%, greater than that of the other models, and a recall of 99% for positive values.

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Section: Galois Field Mapping/galois Fields Demappingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning

Soto

Zamorano-Illanes

Becerra

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…As an emerging enveloped virus, SARS-CoV-2 renders the current global respiratory distress syndrome (COVID-19). , SARS-CoV-2 leads to asymptomatic infection, mild illness, and severe pneumonia that can progress to acute respiratory distress syndrome. − Various prophylactic vaccines have been developed against SARS-CoV-2. , The present multiple vaccines have been developed, based on mRNA, viral vectors, inactivated viruses, and proteins . Protein-based vaccines are promising for their effectiveness, good safety profiles, and rapid production. , …”

Section: Introductionmentioning

confidence: 99%

Mucosal SARS-CoV-2 Nanoparticle Vaccine Based on Mucosal Adjuvants and Its Immune Effectiveness by Intranasal Administration

Xiao

Wang

Shen

et al. 2023

ACS Appl. Mater. Interfaces

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SARS-CoV-2 is a respiratory virus that causes significant threats to human health. Mucosal immunity provides a first-line defense to prevent the infection of SARS-CoV-2 in the respiratory tract. Because most SARS-CoV-2 vaccines could not stimulate mucosal immunity in the respiratory tract, appropriate mucosal adjuvants or delivery systems are needed for mucosal vaccine development. Mannan, polyarginine, and 2′,3′-cGAMP are three mucosal adjuvants that could stimulate mucosal immunity. In the present study, the three adjuvants were assembled with a receptor-binding domain (RBD) by electrostatic interaction to generate a nanoparticle vaccine (RBD-MP-cG). RBD-MP-cG elicited mucosal IgA and IgG response in bronchoalveolar lavage and nasal lavage by intranasal administration. It induced a robust RBD-specific antibody response, high levels of protective neutralizing antibody, and ACE2-blocking activity in the mouse sera. It stimulated the splenic secretion of high levels of Th1-, Th2-, and Th17-type cytokines. Thus, RBD-MP-cG elicited strong mucosal immunity and systematic immunity by intranasal administration. RBD-MP-cG was expected to act as a safe, effective, and easily produced mucosal nanoparticle vaccine to combat the infection of SARS-CoV-2.

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“…Maternal infection with SARS-CoV-2 during pregnancy may expose the fetus to both direct and indirect systemic effects triggered by the virus ( 1 ). The consequences of the maternal and fetal inflammatory response with the production of potentially cytotoxic cytokines, in addition to the effect of the use of antiviral medications, have not been adequately studied to date ( 1 , 2 ).…”

Section: Introductionmentioning

confidence: 99%

Neuroimaging assessment of pediatric cerebral changes associated with SARS-CoV-2 infection during pregnancy

et al. 2023

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BackgroundSARS-CoV-2 infection and perinatal neurologic outcomes are still not fully understood. However, there is recent evidence of white matter disease and impaired neurodevelopment in newborns following maternal SARS-CoV-2 infection. These appear to occur as a consequence of both direct viral effects and a systemic inflammatory response, with glial cell/myelin involvement and regional hypoxia/microvascular dysfunction. We sought to characterize the consequences of maternal and fetal inflammatory states in the central nervous system of newborns following maternal SARS-CoV-2 infection.MethodsWe conducted a longitudinal prospective cohort study from June 2020 to December 2021, with follow-up of newborns born to mothers exposed or not exposed to SARS-CoV-2 infection during pregnancy. Brain analysis included data from cranial ultrasound scans (CUS) with grayscale, Doppler studies (color and spectral), and ultrasound-based brain elastography (shear-wave mode) in specific regions of interest (ROIs): deep white matter, superficial white matter, corpus callosum, basal ganglia, and cortical gray matter. Brain elastography was used to estimate brain parenchymal stiffness, which is an indirect quantifier of cerebral myelin tissue content.ResultsA total of 219 single-pregnancy children were enrolled, including 201 born to mothers exposed to SARS-CoV-2 infection and 18 from unexposed controls. A neuroimaging evaluation was performed at 6 months of adjusted chronological age and revealed 18 grayscale and 21 Doppler abnormalities. Predominant findings were hyperechogenicity of deep brain white matter and basal ganglia (caudate nuclei/thalamus) and a reduction in the resistance and pulsatility indices of intracranial arterial flow. The anterior brain circulation (middle cerebral and pericallosal arteries) displayed a wider range of flow variation than the posterior circulation (basilar artery). Shear-wave US elastography analysis showed a reduction in stiffness values in the SARS-CoV-2 exposed group in all analyzed regions of interest, especially in the deep white matter elasticity coefficients (3.98 ± 0.62) compared to the control group (7.76 ± 0.77); p-value < 0.001.ConclusionThis study further characterizes pediatric structural encephalic changes associated with SARS-CoV-2 infection during pregnancy. The maternal infection has been shown to be related to cerebral deep white matter predominant involvement, with regional hyperechogenicity and reduction of elasticity coefficients, suggesting zonal impairment of myelin content. Morphologic findings may be subtle, and functional studies such as Doppler and elastography may be valuable tools to more accurately identify infants at risk of neurologic damage.

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Functional consequences of SARS-CoV-2 infection in pregnant women, fetoplacental unit, and neonate

Cited by 10 publications

References 168 publications

A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning

A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning

Mucosal SARS-CoV-2 Nanoparticle Vaccine Based on Mucosal Adjuvants and Its Immune Effectiveness by Intranasal Administration

Neuroimaging assessment of pediatric cerebral changes associated with SARS-CoV-2 infection during pregnancy

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