Diving into CDC pregnancy data in the United States: longitudinal study and interactive application.

Objective: Preterm birth (PTB) is a major determinant of neonatal mortality, morbidity, and childhood disability. In this article, we present a longitudinal analysis of the risk factors associated with PTB and how they have varied over the years: starting from 1968 when the CDC first started, reporting the natality data, up until 2021. Along with this article, we are also releasing an RShiny web application that will allow for easy consumption of this voluminous dataset by the research community. Further, we hope this tool can aid clinicians in the understanding and prevention of PTB. Materials and Methods: This study used the CDC Natality data from 1968 to 2021 to analyze trends in PTB outcomes across the lens of various features, including race, maternal age, education, and interval length between pregnancies. Our interactive RShiny web application, CDC NatView, allows users to explore interactions between maternal risk factors and maternal morbidity conditions and the aforementioned features. Results: Our study demonstrates how CDC data can be leveraged to conduct a longitudinal analysis of natality trends in the United States. Our key findings reveal an upward trend in late PTBs, which is concerning. Moreover, a significant disparity exists between African American and White populations in terms of PTB. These disparities persist in other areas, such as education, body-mass index, and access to prenatal care later in pregnancy. Discussion: Another notable finding is the increase in maternal age over time. Additionally, we confirm that short interpregnancy intervals (IPIs) are a risk factor for PTBs. To facilitate the exploration of pregnancy risk factors, infections, and maternal morbidity, we developed an open-source RShiny tool called CDC NatView. This software offers a user-friendly interface to interact with and visualize the CDC natality data, which constitutes an invaluable resource. Conclusion: In conclusion, our study has shed light on the rise of late PTBs and the persistent disparities in PTB rates between African American and White populations in the US. The increase in maternal age and the confirmation of a short IPI as a risk factor for PTB are noteworthy findings. Our open-source tool, CDC NatView, can be a valuable resource for further exploration of the CDC natality data to enhance our understanding of pregnancy risk factors and the interaction of PTB outcomes and maternal morbidities.

Effect of substituents on the 1O2 production and biological activity of (N

Twelve (N^N^N)platinum pyridyl complexes, (N^N^N)Pt(pyF), were synthesised and investigated for their singlet oxygen generation and potential biological activities. They exhibited 1IL and 1MLCT absorption transitions at approximately 325 and 360 nm, identified through TD-DFT calculations. Luminescence was observed only in the L1-derived compounds in solution, with a dual emission with the main contribution of phosphorescence under deaerated conditions. Room temperature phosphorescence was detected in all solid-state cases. Electron-withdrawing substituents at specific positions (R1 and X) and the number of fluorine atoms in R2 were found to enhance the photosensitizing capabilities of these compounds. Biological assessments, including cytotoxicity and photocytotoxicity, were conducted to evaluate their potential as chemotherapeutic agents and photosensitizers. Complexes with chloro substitution in the N^N^N tridentate ligand of the central pyridine ring exhibited promising chemotherapeutic properties. Ancillary pyridine ring substitution became significant under irradiation conditions, with fluoromethylated substituents enhancing cytotoxicity. Complex 2-CF3 was the most efficient singlet oxygen producer and a highly effective photosensitizer. CHF2-substituted complexes also showed improved photosensitizing activity. DNA binding studies indicated moderate interactions with DNA, offering insights into potential biological applications.

Impact of lockdowns on the spread of COVID-19 in Saudi Arabia.

Epidemiological models have been used extensively to predict disease spread in large populations. Among these models, Susceptible Infectious Exposed Recovered (SEIR) is considered to be a suitable model for COVID-19 spread predictions. However, SEIR in its classical form is unable to quantify the impact of lockdowns. In this work, we introduce a variable in the SEIR system of equations to study the impact of various degrees of social distancing on the spread of the disease. As a case study, we apply our modified SEIR model on the initial spread data available (till April 9, 2020) for the Kingdom of Saudi Arabia (KSA). Our analysis shows that with no lockdown around 2.1 million people might get infected during the peak of spread around 2 months from the date the lockdown was first enforced in KSA (March 25th). On the other hand, with the Kingdom's current strategy of partial lockdowns, the predicted number of infections can be lowered to 0.4 million by September 2020. We further demonstrate that with a stricter level of lockdowns, the COVID-19 curve can be effectively flattened in KSA.