High-throughput technologies have become essential in many fields of pharmaceutical and biological development and production. Such technologies were initially developed with compatibility with liquid handling-based cell culture techniques to produce large-scale 2D cell culture experiments for the compound analysis of candidate drug compounds. Over the past two decades, tools for creating 3D cell cultures, organoids, and other 3D models, such as cell supportive biomaterials and 3D bioprinting, have rapidly advanced. Concurrently, a significant body of evidence has accumulated which speaks to the many benefits that 3D model systems have over traditional 2D cell cultures. Specifically, 3D cellular models better mimic aspects such as diffusion kinetics, cell-cell interactions, cell-matrix interactions, inclusion of stroma, and other features native to tissue and as such have become an integral part of academic research. However, most high throughput assays were not developed to specifically support 3D systems. Here, we describe the need for improved compatibility and relevant advances toward deployment and adoption of high throughput 3D models to improve disease modeling, drug efficacy testing, and precision medicine applications.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7968875 | PMC |
http://dx.doi.org/10.1063/1.5056188 | DOI Listing |
Am J Drug Alcohol Abuse
January 2025
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Kratom is a plant with alkaloids acting at opioid, serotonergic, adrenergic, and other receptors. Consumers report numerous use motivations. To distinguish subgroups of kratom consumers by kratom-use motivations using latent-class analysis.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Gastroenterology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Background: Gastrointestinal bleeding (GIB) is a severe and potentially life-threatening complication in patients with acute myocardial infarction (AMI), significantly affecting prognosis during hospitalization. Early identification of high-risk patients is essential to reduce complications, improve outcomes, and guide clinical decision-making.
Objective: This study aimed to develop and validate a machine learning (ML)-based model for predicting in-hospital GIB in patients with AMI, identify key risk factors, and evaluate the clinical applicability of the model for risk stratification and decision support.
Neurology
February 2025
From the Temple University College of Public Health (I.L.H.); Thomas Jefferson University (G.G.); and Department of Neurology (T.D.H.-P.), Lewis Katz School of Medicine at Temple University, Philadelphia, PA.
Background And Objectives: Clinical care for people living with amyotrophic lateral sclerosis (PLWALS) is directed at slowing disease progression and symptom management. The American Academy of Neurology recommends a multidisciplinary approach to providing ALS health care because observational studies show that multidisciplinary clinics (MDCs) extend survival and improve quality of life. However, providing multidisciplinary care is a challenging financial proposition.
View Article and Find Full Text PDFAm J Public Health
January 2025
Alexia Couture, A. Danielle Iuliano, Ryan Threlkel, Matthew Gilmer, Alissa O'Halloran, Dawud Ujamaa, Matthew Biggerstaff, and Carrie Reed are with the National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA. Howard H. Chang is with the Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA.
To develop a method leveraging hospital-based surveillance to estimate influenza-related hospitalizations by state, age, and month as a means of enhancing current US influenza burden estimation efforts. Using data from the Influenza Hospitalization Surveillance Network (FluSurv-NET), we extrapolated monthly FluSurv-NET hospitalization rates after adjusting for testing practices and diagnostic test sensitivities to non-FluSurv-NET states. We used a Poisson zero-inflated model with an overdispersion parameter within the Bayesian hierarchical framework and accounted for uncertainty and variability between states and across time.
View Article and Find Full Text PDFJ Clin Oncol
January 2025
German Breast Group, Neu-Isenburg, Germany.
Purpose: To assess trial-level surrogacy value for overall survival (OS) of the pathologic complete response (pCR) and invasive disease-free survival (iDFS) in randomized clinical trials (RCTs) for early breast cancer (BC).
Methods: Individual patient data of neoadjuvant RCTs with available data on pCR, iDFS, and OS were included in the analysis. We used the coefficient of determination from weighted linear regression models to quantify the association between treatment effects on OS and on the surrogate end points.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!