AIMC Topic: Mice

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Bubble-Based Microrobots with Rapid Circular Motions for Epithelial Pinning and Drug Delivery.

Small (Weinheim an der Bergstrasse, Germany)
Remotely powered microrobots are proposed as next-generation vehicles for drug delivery. However, most microrobots swim with linear trajectories and lack the capacity to robustly adhere to soft tissues. This limits their ability to navigate complex b...

Identification of thrombopoiesis inducer based on a hybrid deep neural network model.

Thrombosis research
Thrombocytopenia is a common haematological problem worldwide. Currently, there are no relatively safe and effective agents for the treatment of thrombocytopenia. To address this challenge, we propose a computational method that enables the discovery...

Science fact vs science fiction: A ChatGPT immunological review experiment gone awry.

Immunology letters
Artificial intelligence (AI) has made great progress in recent years. The latest chatbot to make a splash is ChatGPT. To see if this type of AI could also be helpful in creating an immunological review article, I put a planned review on different cla...

A pharmacokinetic-pharmacodynamic model based on the SSA-1DCNN-Attention network and the semicompartment method.

Biotechnology & genetic engineering reviews
To solve the problem of inaccurate prediction caused by the lack of representativeness of samples due to the small sample size of the collected clinical data when using machine learning methods to predict drug concentration in plasma and describe the...

Dose reduction and image enhancement in micro-CT using deep learning.

Medical physics
BACKGROUND: In preclinical settings, micro-computed tomography (CT) provides a powerful tool to acquire high resolution anatomical images of rodents and offers the advantage to in vivo non-invasively assess disease progression and therapy efficacy. M...

The emerging role of artificial intelligence and digital twins in pre-clinical molecular imaging.

Nuclear medicine and biology
INTRODUCTION: Pre-clinical molecular imaging, particularly with mice, is an essential part of drug and radiopharmaceutical development. There remain ethical challenges to reduce, refine and replace animal imaging where possible.

An end-to-end pipeline based on open source deep learning tools for reliable analysis of complex 3D images of ovaries.

Development (Cambridge, England)
Computational analysis of bio-images by deep learning (DL) algorithms has made exceptional progress in recent years and has become much more accessible to non-specialists with the development of ready-to-use tools. The study of oogenesis mechanisms a...

Machine learning-assisted data filtering and QSAR models for prediction of chemical acute toxicity on rat and mouse.

Journal of hazardous materials
Machine learning (ML) methods provide a new opportunity to build quantitative structure-activity relationship (QSAR) models for predicting chemicals' toxicity based on large toxicity data sets, but they are limited in insufficient model robustness du...

Tough, Recyclable, and Degradable Elastomers for Potential Biomedical Applications.

Advanced materials (Deerfield Beach, Fla.)
Elastomers have many industrial, medical and commercial applications, however, their huge demand raises an important question of how to dispose of the out-of-service elastomers. Ideal elastomers that are concurrently tough, recyclable, and degradable...

Active mesh and neural network pipeline for cell aggregate segmentation.

Biophysical journal
Segmenting cells within cellular aggregates in 3D is a growing challenge in cell biology due to improvements in capacity and accuracy of microscopy techniques. Here, we describe a pipeline to segment images of cell aggregates in 3D. The pipeline comb...