Publications by authors named "QiXuan Chen"
Owing to its topological properties and band collapse, Floquet helical photonic lattices have gained increasing attention as a purely classical setting to realize the optical analogues of a wide variety of quantum phenomena. We demonstrate both theoretically and numerically that light propagation in an appropriately designed helical superlattice can exhibit spatial photonic Zitterbewegung effect, i.e.
View Article and Find Full Text PDFBackground: Overdose mortality increased substantially during the COVID-19 pandemic, but it is unclear to what extent the COVID-19 mortality had contributed to this increase at the neighborhood level.
Methods: This was an ecological study based on New York City United Hospital Fund (NYC UHF) neighborhood-level data from 2019 to 2021, split into two time-windows: pre-COVID (2019) and during-COVID (2020 and 2021). Linear regression models were used to estimate the effect of cumulative COVID-19 mortality on the increase in drug overdose mortality from the pre-COVD to during-COVID periods at the neighborhood level, with and without adjusting for neighborhood characteristics.
Probability surveys are challenged by increasing nonresponse rates, resulting in biased statistical inference. Auxiliary information about populations can be used to reduce bias in estimation. Often continuous auxiliary variables in administrative records are first discretized before releasing to the public to avoid confidentiality breaches.
View Article and Find Full Text PDFAlzheimer's disease (AD) is a prevalent neurodegenerative disorder that severely diminishes the quality of life for millions. The NLRP3 inflammasome, a critical mediator of inflammation, has emerged as a promising therapeutic target for AD. In this study, we report the development and optimization of a novel series of sulfonylurea-based NLRP3 inhibitors, with a focus on compound MC1 for the treatment of AD.
View Article and Find Full Text PDFArticle Synopsis
- Participatory surveillance in Lesotho, called "LeCellPHIA," involved at-risk populations reporting influenza-like illness (ILI) symptoms via phone calls from interviewers during the COVID-19 pandemic.
- The study analyzed ILI trends and demographic factors from July 2020 to July 2021, revealing a 75% response rate with 122,985 reports, indicating higher ILI risk in older age groups, particularly those 60 and above.
- Findings were shared in real-time with health authorities to help monitor ILI trends and inform public health policies aimed at reducing COVID-19 transmission.
Article Synopsis
- The NLRP3 inflammasome is crucial in various hard-to-treat diseases, making it a key target for new therapies.
- A new orally effective NLRP3 inhibitor called SN3-1 was developed using advanced deep-learning techniques, which improved the identification of potential drug candidates.
- SN3-1 has shown strong safety and effectiveness in preclinical tests, marking it as a promising option for future NLRP3 inhibitor development.
Article Synopsis
- This study aimed to see if a web-based application could help non-chest radiologists better diagnose pulmonary fibrosis by reviewing various chest CT scans.
- Three radiologists examined multiple rounds of CT scans, initially diagnosing independently and later using suggested features from the application over time.
- Results showed an increase in diagnostic accuracy from 63% to 74% over the rounds, with specific improvements when refining definitions of features used for diagnosis, particularly enhancing accuracy for a type of fibrosis called NSIP.
Article Synopsis
- The study explores how trimer lattices can be linked and identifies the presence of stable edge and interface states that are topologically protected.
- It reveals that the number of these states can be adjusted based on the strength of the coupling and the topological characteristics of the connected lattices.
- Additionally, the research examines the dynamics of these interface states, observing stable oscillations that lead to potential applications in optical coupling, like directional coupling and beam splitting.
Article Synopsis
- The study explored the link between arsenic levels in community water systems and private wells and the incidence of type 2 diabetes (T2D) among participants in two major studies: the Strong Heart Family Study (SHFS) and the Multi-Ethnic Study of Atherosclerosis (MESA).
- A total of 7,568 participants (1,791 from SHFS and 5,777 from MESA) without T2D at baseline were monitored for new cases, finding a higher incidence of T2D associated with increased arsenic levels in the water supplies, particularly among certain demographics.
- Results indicated that even low to moderate levels of arsenic in drinking water (<10 µ
Article Synopsis
- Chemical reactions are essential for organic chemistry and drug design, with data-driven approaches revolutionizing the optimization and discovery of novel reactions using AI.
- Effective machine learning in this field requires developing strong representations and features from large reaction datasets to improve reaction performance.
- This review explores various reaction featurization methods, discusses the strengths and weaknesses of different representation techniques like SMILES and molecular graphs, and proposes new ideas for chemical reaction pretraining.
Rapid single-particle chemical imaging of nanoplastics by SRS microscopy.
Proc Natl Acad Sci U S A
January 2024
Article Synopsis
- Plastics are everywhere in our lives, and the emergence of microplastics and nanoplastics has sparked health concerns due to their potential toxicity and ability to enter the human body.
- Detecting nanoplastics is challenging because it requires sensitive techniques that can specifically identify different types of plastics at extremely small sizes.
- A new imaging technology was developed that allows for high-speed detection and identification of nanoplastics in bottled water, revealing a much higher concentration of nanoplastics than previously reported, and offering insights into their diverse characteristics.
Article Synopsis
- Multilevel regression and poststratification (MRP) is increasingly used for population inference, but its accuracy can be influenced by model details and validation practices are under-researched.
- The study investigates leave-one-out cross-validation (LOO) methods, focusing on Pareto smoothed importance sampling (PSIS-LOO) and a survey-weighted alternative (WTD-PSIS-LOO), using simulations to assess their effectiveness in ranking model performance.
- Findings reveal that while both PSIS-LOO and WTD-PSIS-LOO can identify the best and worst models, they struggle with accurately ranking models for MRP, particularly in small-area estimations, indicating a need for caution in relying solely
Article Synopsis
- Accurate diagnosis of pulmonary fibrosis patterns is critical but complicated due to similar radiographic features.
- A study analyzed 400 patients using machine learning techniques to identify key radiographic characteristics and developed a diagnostic app.
- The Bayesian additive regression tree outperformed other methods by accurately predicting diagnoses and providing uncertainty intervals, making it a valuable tool for radiologists.
Article Synopsis
- Rhinitis is a common chronic nasal condition in children that is linked to asthma, although its development over time is not well understood.
- * The study tracked 688 children from infancy to age 11, identifying five types of rhinitis trajectories and their relationship to asthma symptoms through various questionnaires and assessments.
- * Results indicated that persistent and late-onset frequent rhinitis types were strongly associated with higher asthma diagnosis rates and more frequent asthma symptoms.
Article Synopsis
- The study aimed to evaluate a participatory surveillance system for influenza-like illness (ILI) in Lesotho, which has limited COVID-19 testing capabilities, and compare its effectiveness in estimating COVID-19 case counts.
- Data were collected through weekly phone calls to a nationally-representative sample, and the results showed significant correlations between ILI reports and COVID-19 case counts, particularly during peak times.
- The findings suggest that the participatory surveillance system can provide valuable insights into disease trends in resource-limited settings, helping local authorities track infectious diseases like COVID-19 more effectively.
Contribution of arsenic and uranium in private wells and community water systems to urinary biomarkers in US adults: The Strong Heart Study and the Multi-Ethnic Study of Atherosclerosis.
Maya Spaur Ronald A Glabonjat Kathrin Schilling Melissa A Lombard Marta Galvez-Fernandez Qixuan Chen
J Expo Sci Environ Epidemiol
January 2024
Article Synopsis
- Chronic exposure to inorganic arsenic (As) and uranium (U) in the U.S. primarily comes from private wells and community water systems, with assumptions that their contribution to total exposure is low when concentrations are low.
- The study investigated how much these water sources contributed to urinary biomarkers in American Indian and diverse urban communities, analyzing data from over 8,000 participants.
- Results indicated that both As and U levels in urine significantly increased with higher concentrations of these contaminants in the water, highlighting their substantial impact on internal exposure to these harmful substances.
Article Synopsis
- Simultaneous alcohol and marijuana (SAM) use has decreased among 12th graders in the US overall from 2000 to 2020, but has paradoxically increased among those who have never used cigarettes or vaped nicotine.
- Among students who have used cigarettes or vaped, SAM peaked during 2010-2014 and then declined, while marijuana-only use significantly rose among their non-smoker peers.
- The findings suggest a complex relationship where traditional tobacco use may influence patterns of alcohol and marijuana use, indicating a changing landscape of substance use among adolescents over time.
Article Synopsis
- Measurement error is a common issue in environmental epidemiologic studies, and traditional methods for correcting it in regression models with multiple exposures have not been thoroughly explored.
- The proposed constrained chained equations multiple imputation (CEMI) algorithm addresses measurement error by incorporating calibration data and allowing for nondetects in the main study, improving the accuracy of regression coefficients.
- Simulations show that the constrained CEMI method outperforms other methods by producing regression coefficients with reduced bias and better confidence intervals, and it has been applied to analyze asthma-related data in children in New York City.
Article Synopsis
- The rise of electronic cigarettes ("vaping") among teens poses serious health risks, particularly due to links with harmful substances and possible connections to cannabis and alcohol use.
- Research using data from over 51,000 US adolescents highlights that various patterns of nicotine use—like smoking-only, vaping-only, or a combination of both—are strongly correlated with increased cannabis use and binge drinking.
- Findings suggest that teens who engage in both smoking and vaping are significantly more likely to binge drink, indicating a pressing need for targeted prevention strategies and public education campaigns to address these overlapping substance use behaviors.
Article Synopsis
- Adolescents commonly exhibit psychiatric symptoms that fall into two main categories: internalizing (like anxiety) and externalizing (like aggression), both of which are related to self-esteem levels.
- A study analyzed data from nearly 339,000 US adolescents between 1991 and 2020 to explore changes in self-esteem and externalizing symptoms, looking closely at how different activities influenced these aspects by sex.
- The findings showed a notable rise in poor self-esteem, particularly among girls with low socialization, while externalizing symptoms decreased; however, those with both issues remained consistent across various activity groups, indicating a need for focused interventions.
Self-Report Survey Measures of Alcohol-Impaired Driving: A Systematic Review.
J Stud Alcohol Drugs
September 2023
Article Synopsis
- The study aimed to identify and evaluate self-report measures used for assessing alcohol-impaired driving, a significant cause of vehicle-related injuries and deaths.
- Researchers reviewed literature from various databases, extracting measures and their reliability or validity to compile a list and categorize them into codes for comparison.
- Findings indicated that self-report measures with multiple items, covering different aspects of alcohol impairment, demonstrated higher reliability, but no studies reported on their validity, highlighting a need for future research in this area.
Article Synopsis
- The COVID-19 pandemic led to changes in alcohol consumption and traffic crashes in the US, with alcohol-related incidents increasing in California post-stay-at-home order.
- A study analyzed crash data from 2016 to 2021, revealing a drop in overall crash rates by 4.6 per 100,000 population after the order, but a rise in the proportion of alcohol-involved crashes from 10.3% to 12.7%.
- Although crash rates have returned to pre-pandemic figures, alcohol-involved crashes remain higher than before the pandemic, highlighting ongoing public safety concerns.
Article Synopsis
- Sobriety checkpoints help catch drunk drivers, but they aren’t used much in the USA. This study tested a new way to do checkpoints with fewer officers for shorter times, hoping to save money but still keep people safe.
- The study took place in Apex, NC, where police conducted 5 out of 6 planned checkpoints, comparing the new method to the regular way of doing things.
- Most drivers (over 90%) said they support these checkpoints, and drivers felt stress when passing through, but the new way worked just as well as the old way.