AIMC Topic: Humans

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Meta-Analysis and Machine Learning Prediction of Protein Corona Composition across Nanoparticle Systems in Biological Media.

ACS nano
A comprehensive understanding of protein corona (PC) composition is critical for engineering nanoparticles (NPs) with optimal safety and therapeutic performance, because the PC governs NP pharmacokinetics, biodistribution, and cellular interactions. ...

Machine Learning-Assisted 3D SERS Chip with Acoustic Enrichment for High-Accuracy Diagnosis of Respiratory Viruses and Emerging Pathogens.

ACS sensors
Outbreaks of SARS-CoV-2, first investigated as an unknown pathogen, have reflected the severe threat that pathogen X poses to public health and social security. Early and precise diagnosis and classification of infectious respiratory diseases with si...

The Identification of Biological Stains at Crime Scenes: A Promising Role for Proteomics and Machine Learning.

Analytical chemistry
Forensic body fluid identification is crucial for reconstructing crime scene events. While DNA analysis provides individualization, it lacks information about the fluid's origin. We developed and evaluated three complementary proteomic approaches usi...

Machine learning-assisted triboelectric nanogenerator technology for intelligent sports.

Science advances
The rapid development of internet of things, big data, and artificial intelligence is propelling sports science into a data-driven era, demanding real-time, multidimensional athletic performance monitoring. Triboelectric nanogenerators (TENGs) have d...

AI-directed gene fusing prolongs the evolutionary half-life of synthetic gene circuits.

Science advances
Evolutionary instability is a persistent challenge in synthetic biology, often leading to the loss of heterologous gene expression over time. Here, we present STABLES, a gene fusion strategy that links a gene of interest (GOI) to an essential endogen...

Differential Diagnosis Assessment in Ambulatory Care With a Digital Health History Device: Pseudorandomized Study.

JMIR formative research
BACKGROUND: Digital health history devices represent a promising wave of digital tools with the potential to enhance the quality and efficiency of medical consultations. They achieve this by providing physicians with standardized, high-quality patien...

Fast and Robust Single-Shot Cine Cardiac MRI Using Deep Learning Super-Resolution Reconstruction.

Investigative radiology
OBJECTIVE: The aim of the study was to compare the diagnostic quality of deep learning (DL) reconstructed balanced steady-state free precession (bSSFP) single-shot (SSH) cine images with standard, multishot (also: segmented) bSSFP cine (standard cine...

PixelPrint 4D : A 3D Printing Method of Fabricating Patient-Specific Deformable CT Phantoms for Respiratory Motion Applications.

Investigative radiology
OBJECTIVES: Respiratory motion poses a significant challenge for clinical workflows in diagnostic imaging and radiation therapy. Many technologies such as motion artifact reduction and tumor tracking have been developed to compensate for its effect. ...

Deep Learning Predicts Cardiac Output from Seismocardiographic Signals in Heart Failure.

The American journal of cardiology
Determination of cardiac output (CO) is essential to the clinical management of cardiovascular compromise. However, the invasiveness, procedural risks, and reliance on specialized infrastructure limit accessibility and scalability of standard-of-care...

Breaking barriers: Medicinal chemistry strategies and advanced in-silico approaches for overcoming the BBB and enhancing CNS penetration.

European journal of medicinal chemistry
Delivering small molecules to the brain and central nervous system (CNS) is greatly hindered by the restrictive blood-brain barrier (BBB), which selectively permits essential molecules while excluding toxic molecules. This selective permeability feat...