AIMC Topic: Mice

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3D electron microscopy for analyzing nanoparticles in the tumor endothelium.

Proceedings of the National Academy of Sciences of the United States of America
Delivering medical agents to diseased tissues has been challenging, leading researchers to study the in vivo transport process in the body for improving delivery. Many imaging techniques exist for mapping the distribution of medical agent-carrying na...

Cross-disease transcriptomic analysis reveals DOK3 and PAPOLA as therapeutic targets for neuroinflammatory and tumorigenic processes.

Frontiers in immunology
OBJECTIVE: Subarachnoid hemorrhage (SAH) and tumorigenesis share numerous biological complexities; nevertheless, the specific gene expression profiles and underlying mechanisms remain poorly understood. This study aims to identify differentially expr...

Cyto-Safe: A Machine Learning Tool for Early Identification of Cytotoxic Compounds in Drug Discovery.

Journal of chemical information and modeling
Cytotoxicity is essential in drug discovery, enabling early evaluation of toxic compounds during screenings to minimize toxicological risks. assays support high-throughput screening, allowing for efficient detection of toxic substances while conside...

Imaging-guided bioresorbable acoustic hydrogel microrobots.

Science robotics
Micro- and nanorobots excel in navigating the intricate and often inaccessible areas of the human body, offering immense potential for applications such as disease diagnosis, precision drug delivery, detoxification, and minimally invasive surgery. De...

Integration of bulk/scRNA-seq and multiple machine learning algorithms identifies PIM1 as a biomarker associated with cuproptosis and ferroptosis in abdominal aortic aneurysm.

Frontiers in immunology
BACKGROUND: Abdominal aortic aneurysm (AAA) is a serious life-threatening vascular disease, and its ferroptosis/cuproptosis markers have not yet been characterized. This study was aiming to identify markers associated with ferroptosis/cuproptosis in ...

Enhancing automatic sleep stage classification with cerebellar EEG and machine learning techniques.

Computers in biology and medicine
Sleep disorders have become a significant health concern in modern society. To investigate and diagnose sleep disorders, sleep analysis has emerged as the primary research method. Conventional polysomnography primarily relies on cerebral electroencep...

Machine learning models for quantitatively prediction of toxicity in macrophages induced by metal oxide nanoparticles.

Chemosphere
As nanotechnology advances, metal oxide nanoparticles (MeONPs) increasingly come into contact with humans. The inhaled MeONPs cannot be effectively cleared by cilia or lung mucus. In the last decade, potential immune toxicity arising from exposure to...

Integrating microbial profiling and machine learning for inference of drowning sites: a forensic investigation in the Northwest River.

Microbiology spectrum
Drowning incidents present significant challenges for forensic investigators in determining the exact site of occurrence. Traditional forensic methods often rely on physical evidence and circumstantial clues, but the emerging field of forensic microb...

Multiomics identification of programmed cell death-related characteristics for nonobstructive azoospermia based on a 675-combination machine learning computational framework.

Genomics
BACKGROUND: Abnormal programmed cell death (PCD) plays a central role in spermatogenic dysfunction. However, the molecular mechanisms and biomarkers of PCD in patients with nonobstructive azoospermia (NOA) remain unclear.

A programmable, open-source robot that scratches cultured tissues to investigate cell migration, healing, and tissue sculpting.

Cell reports methods
Despite the widespread popularity of the "scratch assay," where a pipette is dragged manually through cultured tissue to create a gap to study cell migration and healing, it carries significant drawbacks. Its heavy reliance on manual technique can co...