Demographic disparities, temporal trends, and geographic patterns of HPV vaccination on Long Island, New York: A comprehensive analysis of immunization registry data (2012-2023).

The Advisory Committee on Immunization Practices (ACIP) advised vaccinating children, adolescents and young adults against Human Papillomavirus (HPV) in 2006, aiming to prevent HPV-related cancers and genital warts. As HPV vaccination rates remained low even 10 years after it was introduced, understanding vaccination patterns is essential for informing targeted public health interventions. This study explores the demographic disparities (age, gender, race and ethnicity), temporal trends, and geographical patterns of HPV vaccine administration by analyzing large-scale immunization registry data for Long Island (LI) (Nassau and Suffolk Counties), New York (NY).

A systematic study of key elements underlying molecular property prediction.

Artificial intelligence (AI) has been widely applied in drug discovery with a major task as molecular property prediction. Despite booming techniques in molecular representation learning, key elements underlying molecular property prediction remain largely unexplored, which impedes further advancements in this field. Herein, we conduct an extensive evaluation of representative models using various representations on the MoleculeNet datasets, a suite of opioids-related datasets and two additional activity datasets from the literature.

An integrated LSTM-HeteroRGNN model for interpretable opioid overdose risk prediction.

Opioid overdose (OD) has become a leading cause of accidental death in the United States, and overdose deaths reached a record high during the COVID-19 pandemic. Combating the opioid crisis requires targeting high-need populations by identifying individuals at risk of OD. While deep learning emerges as a powerful method for building predictive models using large scale electronic health records (EHR), it is challenged by the complex intrinsic relationships among EHR data.

Artificial intelligence in drug discovery: applications and techniques.

Artificial intelligence (AI) has been transforming the practice of drug discovery in the past decade. Various AI techniques have been used in many drug discovery applications, such as virtual screening and drug design. In this survey, we first give an overview on drug discovery and discuss related applications, which can be reduced to two major tasks, i.

A Large-Scale Observational Study on the Temporal Trends and Risk Factors of Opioid Overdose: Real-World Evidence for Better Opioids.

Background: The USA is in the midst of an opioid overdose epidemic. To address the epidemic, we conducted a large-scale population study on opioid overdose.

Objectives: The primary objective of this study was to evaluate the temporal trends and risk factors of inpatient opioid overdose.

Predicting opioid overdose risk of patients with opioid prescriptions using electronic health records based on temporal deep learning.

The US is experiencing an opioid epidemic, and opioid overdose is causing more than 100 deaths per day. Early identification of patients at high risk of Opioid Overdose (OD) can help to make targeted preventative interventions. We aim to build a deep learning model that can predict the patients at high risk for opioid overdose and identify most relevant features.

Detecting Miscoded Diabetes Diagnosis Codes in Electronic Health Records for Quality Improvement: Temporal Deep Learning Approach.

Background: Diabetes affects more than 30 million patients across the United States. With such a large disease burden, even a small error in classification can be significant. Currently billing codes, assigned at the time of a medical encounter, are the "gold standard" reflecting the actual diseases present in an individual, and thus in aggregate reflect disease prevalence in the population.

An Informatics-based Approach to Identify Key Pharmacological Components in Drug-Drug Interactions.

Drug-drug interactions (DDI) can cause severe adverse drug reactions and pose a major challenge to medication therapy. Recently, informatics-based approaches are emerging for DDI studies. In this paper, we aim to identify key pharmacological components in DDI based on large-scale data from DrugBank, a comprehensive DDI database.

Self-Stabilized Precipitation Polymerization and Its Application.

An effective, value-added use of the large amounts of olefinic compounds produced in the processing of petroleum, aside from ethylene and propylene, has been a long outstanding challenge. Here, we developed a novel heterogeneous polymerization method, beyond emulsion/dispersion/suspension, termed self-stabilized precipitation (2SP) polymerization, which involves the nucleation and growth of nanoparticles (NPs) of a well-defined size without the use of any stabilizers and multifunctional monomers (crosslinker). This technique leads to two revolutionary advances: (1) the generation of functional copolymer particles from single olefinic monomer or complex olefinic mixtures (including C4/C5/C9 fractions) in large quantities, which open a new way to transform huge amount of unused olefinic compounds in C4/C5/C9 fractions into valuable copolymers, and (2) the resultant polymeric NPs possess a self-limiting size and narrow size distribution, therefore being one of the most simple, efficient, and green strategies to produce uniform, size-tunable, and functional polymeric nanoparticles.

In silico drug absorption tract: An agent-based biomimetic model for human oral drug absorption.

Background: An agent-based modeling approach has been suggested as an alternative to traditional, equation-based modeling methods for describing oral drug absorption. It enables researchers to gain a better understanding of the pharmacokinetic (PK) mechanisms of a drug. This project demonstrates that a biomimetic agent-based model can adequately describe the absorption and disposition kinetics both of midazolam and clonazepam.

Robust and Fast Decoding of High-Capacity Color QR Codes for Mobile Applications.

The use of color in QR codes brings extra data capacity, but also inflicts tremendous challenges on the decoding process due to chromatic distortion-cross-channel color interference and illumination variation. Particularly, we further discover a new type of chromatic distortion in high-density color QR codes-cross-module color interference-caused by the high density which also makes the geometric distortion correction more challenging. To address these problems, we propose two approaches, LSVM-CMI and QDA-CMI, which jointly model these different types of chromatic distortion.

A Review of Food-Drug Interactions on Oral Drug Absorption.

Food effect, also known as food-drug interactions, is a common phenomenon associated with orally administered medications and can be defined as changes in absorption rate or absorption extent. The mechanisms of food effect and their consequences can involve multiple factors, including human post-prandial physiology, properties of the drug, and how the drug is administered. Therefore, it is essential to have a thorough understanding of these mechanisms when recommending whether a specific drug should be taken with or without food.

An Agent-Based Approach to Dynamically Represent the Pharmacokinetic Properties of Baicalein.

Baicalein, a typical flavonoid presented in Scutellariae radix, exhibits a unique metabolic profile during first-pass metabolism: parallel glucuronidation and sulfation pathways, with possible substrate inhibition in both pathways. In this project, we aimed to construct an agent-based model to dynamically represent baicalein pharmacokinetics and to verify the substrate inhibition hypothesis. The model consisted of three 3D spaces and two membranes: apical space (S1), intracellular space (S2), basolateral space (S3), apical membrane (M1), and basolateral membrane (M2).

An extremely simple and effective strategy to tailor the surface performance of inorganic substrates by two new photochemical reactions.

This article reports on a new sequential strategy to fabricate monolayer functional organosilane films on inorganic substrate surfaces, and subsequently, to pattern them by two new photochemical reactions. (1) By using UV light (254 nm) plus dimethylformamide (DMF), a functional silane monolayer film could be fabricated quickly (within minutes) under ambient temperature. (2) The organic groups of the formed films became decomposed in a few minutes with UV irradiation coupled with a water solution of ammonium persulfate (APS).