CryoSegNet: accurate cryo-EM protein particle picking by integrating the foundational AI image segmentation model and attention-gated U-Net.

Picking protein particles in cryo-electron microscopy (cryo-EM) micrographs is a crucial step in the cryo-EM-based structure determination. However, existing methods trained on a limited amount of cryo-EM data still cannot accurately pick protein particles from noisy cryo-EM images. The general foundational artificial intelligence-based image segmentation model such as Meta's Segment Anything Model (SAM) cannot segment protein particles well because their training data do not include cryo-EM images.

CryoTransformer: a transformer model for picking protein particles from cryo-EM micrographs.

Motivation: Cryo-electron microscopy (cryo-EM) is a powerful technique for determining the structures of large protein complexes. Picking single protein particles from cryo-EM micrographs (images) is a crucial step in reconstructing protein structures from them. However, the widely used template-based particle picking process requires some manual particle picking and is labor-intensive and time-consuming.

CryoVirusDB: A Labeled Cryo-EM Image Dataset for AI-Driven Virus Particle Picking.

With the advancements in instrumentation, image processing algorithms, and computational capabilities, single-particle electron cryo-microscopy (cryo-EM) has achieved nearly atomic resolution in determining the 3D structures of viruses. The virus structures play a crucial role in studying their biological function and advancing the development of antiviral vaccines and treatments. Despite the effectiveness of artificial intelligence (AI) in general image processing, its development for identifying and extracting virus particles from cryo-EM micrographs (images) has been hindered by the lack of manually labelled high-quality datasets.

CryoTransformer: A Transformer Model for Picking Protein Particles from Cryo-EM Micrographs.

Cryo-electron microscopy (cryo-EM) is a powerful technique for determining the structures of large protein complexes. Picking single protein particles from cryo-EM micrographs (images) is a crucial step in reconstructing protein structures from them. However, the widely used template-based particle picking process requires some manual particle picking and is labor-intensive and time-consuming.

Accurate cryo-EM protein particle picking by integrating the foundational AI image segmentation model and specialized U-Net.

Picking protein particles in cryo-electron microscopy (cryo-EM) micrographs is a crucial step in the cryo-EM-based structure determination. However, existing methods trained on a limited amount of cryo-EM data still cannot accurately pick protein particles from noisy cryo-EM images. The general foundational artificial intelligence (AI)-based image segmentation model such as Meta's Segment Anything Model (SAM) cannot segment protein particles well because their training data do not include cryo-EM images.

A large expert-curated cryo-EM image dataset for machine learning protein particle picking.

Cryo-electron microscopy (cryo-EM) is a powerful technique for determining the structures of biological macromolecular complexes. Picking single-protein particles from cryo-EM micrographs is a crucial step in reconstructing protein structures. However, the widely used template-based particle picking process is labor-intensive and time-consuming.

CryoPPP: A Large Expert-Labelled Cryo-EM Image Dataset for Machine Learning Protein Particle Picking.

Cryo-electron microscopy (cryo-EM) is currently the most powerful technique for determining the structures of large protein complexes and assemblies. Picking single-protein particles from cryo-EM micrographs (images) is a key step in reconstructing protein structures. However, the widely used template-based particle picking process is labor-intensive and time-consuming.

Novel report on congenital talipes equinovarus (CTEV) following olanzapine exposure during pregnancy: case report and short review.

Olanzapine is widely used during pregnancy to manage mood and psychotic disorders with overall beneficial effects. There have been past reports of olanzapine exposure during early pregnancy and clubfoot in two newborns from India and Israel. We report a woman in Nepal diagnosed with schizophrenia and treated with olanzapine throughout the pregnancy delivering a baby boy with congenital talipes equinovarus deformity.

Acute Disseminated Encephalomyelitis: Psychiatric Presentation of a Rare Diagnosis.

Acute disseminated encephalomyelitis (ADEM) is an autoimmune inflammatory disease of the central nervous system that is characterized by widespread demyelination, predominantly involving the white matter of the brain and spinal cord. Often caused by a viral infection or vaccination, its clinical features include an acute encephalopathy with multifocal neurologic signs and deficits in children. It can present with psychosis, depression, or abnormal behavior, and it might mimic a dissociative disorder.