Skip to content
#protein folding Open access

Placental Vascular Malperfusion and Perinatal Outcomes During the Vasculotropic Viral Surge of Endemic SARS-CoV-2: A 50-Month Multicenter Longitudinal Study

Oct 2026 · COVID · 19 references
COVID-19 Impact on Reproduction

Abstract

The re-emergence of seasonal respiratory pathogens has complicated obstetric care following the transition of coronavirus disease 2019 to an endemic state. The study examined the epidemiological impact and pathogenetic characteristics associated with endemic viruses among pregnant women. A multicenter retrospective cohort study was conducted using an epidemiological dataset of 9647 consecutive deliveries from 2022 to 2026. A nested clinical sub-cohort of 140 hospitalized patients was divided into coronavirus disease 2019 (67 cases) and other respiratory infections (73 cases) groups. The study compared epidemiological trends, predictive biomarkers (neutrophil-to-lymphocyte ratio and C-reactive protein level), and placental histopathology. The analysis showed an asymmetric U-shaped trend in adverse perinatal events over the study period (N = 9647). Following the nadir of eight stillbirths in 2024, a viral resurgence in 2025 resulted in a 2.6-fold increase in stillbirth risk, primarily linked to preeclampsia and placental abruption. Furthermore, within the clinical sub-cohort, the coronavirus disease 2019 group exhibited a significantly elevated neutrophil-to-lymphocyte ratio, which effectively predicted subclinical maternal vascular malperfusion. The increase in stillbirths between 2025 and 2026 may be exacerbated by waning population immunity and the vasculotropic properties of endemic coronavirus disease 2019. The neutrophil-to-lymphocyte ratio can serve as a useful biomarker for detecting subclinical thrombotic risk.

View source

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

Google DeepMind Blog Sep 30, 2026

Introducing SynthID Bio

Proof of concept for watermarking AI-generated proteins while preserving biological function.

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.