Pregnancy

Emerging innovations in ophthalmic drug delivery for diabetic retinopathy: a translational perspective.

Diabetic retinopathy (DR) is a progressive microvascular complication of diabetes and a leading cause of vision impairment worldwide. Despite advancements in pharmacotherapy, challenges such as poor intraocular bioavailability, rapid drug clearance, and the restrictive blood-retinal barrier hinder effective treatment. Recent innovations in ophthalmic drug delivery systems offer promising solutions...

Intestinal therapeutic agent delivery microrobot with magnetic targeting and pH-triggered degradation abilities.

Oral drug delivery remains a clinically preferred route for colorectal cancer therapy due to its noninvasive nature and patient compliance. However, conventional formulations suffer from premature degradation in the gastric environment and poor site-specific targeting in the intestine, significantly reducing therapeutic efficacy. Here, we introduce an intestinal therapeutic agent delivery microrob...

Prediction of spontaneous preterm birth in pregnant women using machine learning.

PURPOSE: Spontaneous preterm birth (sPTB) is a significant global health concern, contributing to adverse outcomes for both pregnant women and newborn...

Picoeukaryote-based biohybrid microrobots for active delivery in the kidney.

Confined spaces in the human body pose substantial challenges for biomedical procedures. Navigating these ultrasmall environments is essential for pre...

Multiparametric ultrasound techniques are superior to AI-assisted ultrasound for assessment of solid thyroid nodules: a prospective study.

OBJECTIVES: To evaluate the diagnostic performance of multiparametric ultrasound (mpUS) and AI-assisted B-mode ultrasound (AI-US), and their potential...

A formulation dataset of poly(lactide-co-glycolide) nanoparticles for small molecule delivery.

Poly(lactide-co-glycolide) (PLGA) nanoparticles are promising drug delivery systems, widely recognized for their ability to overcome various limitatio...

Deformable detection transformers for domain adaptable ultrasound localization microscopy with robustness to point spread function variations.

Super-resolution imaging has emerged as a rapidly advancing field in diagnostic ultrasound. Ultrasound Localization Microscopy (ULM) achieves sub-wave...

Intratumoral and peritumoral radiomics based on 2D ultrasound imaging in breast cancer was used to determine the optimal peritumoral range for predicting KI-67 expression.

OBJECTIVES: Currently, radiomics focuses on intratumoral regions and fixed peritumoral regions, and lacks an optimal peritumoral region taken to predi...

Intelligent quality assessment of ultrasound images for fetal nuchal translucency measurement during the first trimester of pregnancy based on deep learning models.

OBJECTIVE: As increased nuchal translucency (NT) thickness is notably associated with fetal chromosomal abnormalities, structural defects, and genetic...

BIScreener: enhancing breast cancer ultrasound diagnosis through integrated deep learning with interpretability.

Breast cancer is the leading cause of death among women worldwide, and early detection through the standardized BI-RADS framework helps physicians ass...

A novel machine-learning algorithm to screen for trisomy 21 in first-trimester singleton pregnancies.

BACKGROUND: Antenatal screening for Trisomy 21 (T21) in the UK is performed primarily in the first trimester. Nuchal Translucency (NT), gestational ag...

Predicting the sonication energy for focused ultrasound surgery treatment of breast fibroadenomas using machine learning algorithms.

PURPOSE: To establish a predictive model for the sonication energy required for focused ultrasound surgery (FUS) of breast fibroadenomas.

Recent developments with pH-responsive lyotropic liquid crystalline lipid nanoparticles for targeted bioactive agent delivery.

INTRODUCTION: Lyotropic liquid crystalline lipid nanoparticles (LNPs) are a platform technology with broad-ranging potential in bioactive agent delive...

Association Between COVID-19 During Pregnancy and Preterm Birth by Trimester of Infection: Retrospective Cohort Study Using Large-Scale Social Media Data.

BACKGROUND: Preterm birth, defined as birth at <37 weeks of gestation, is the leading cause of neonatal death globally and the second leading cause of...

Integrative multimodal ultrasound and radiomics for early prediction of neoadjuvant therapy response in breast cancer: a clinical study.

PURPOSE: This study aimed to develop an early predictive model for neoadjuvant therapy (NAT) response in breast cancer by integrating multimodal ultra...

A novel UNet-SegNet and vision transformer architectures for efficient segmentation and classification in medical imaging.

Medical imaging has become an essential tool in the diagnosis and treatment of various diseases, and provides critical insights through ultrasound, MR...

Development of a deep learning model for predicting skeletal muscle density from ultrasound data: a proof-of-concept study.

Reduced muscle mass and function are associated with increased morbidity, and mortality. Ultrasound, despite being cost-effective and portable, is sti...

Machine learning models using non-invasive tests & B-mode ultrasound to predict liver-related outcomes in metabolic dysfunction-associated steatotic liver disease.

Advanced metabolic-dysfunction-associated steatotic liver disease (MASLD) fibrosis (F3-4) predicts liver-related outcomes. Serum and elastography-base...

Recent advances of engineering cell membranes for nanomedicine delivery across the blood-brain barrier.

The blood-brain barrier (BBB) poses a major challenge to the effective delivery of therapeutic agents for the treatment of central nervous system (CNS...

Efficient Ultrasound Breast Cancer Detection with DMFormer: A Dynamic Multiscale Fusion Transformer.

OBJECTIVE: To develop an advanced deep learning model for accurate differentiation between benign and malignant masses in ultrasound breast cancer scr...