EMPIAR-13184 - Cryo-EM structure of alpha-synuclein fibrils formed in artificial cerebrospinal fluid (aCSF) [3510 multi-frame micrographs composed of 317 frames each in EER format]

EMPIAR-13184

Cryo-EM structure of alpha-synuclein fibrils formed in artificial cerebrospinal fluid (aCSF) [3510 multi-frame micrographs composed of 317 frames each in EER format]

Publication:

Formation of Condition-Dependent Alpha-Synuclein Fibril Strain in Artificial Cerebrospinal Fluid

Sniečkutė R, Šulskis D, Jocytė A, Venclovaitė U, Tamulytė R, Žiaunys M, Smirnovas V, Sakalauskas A

Advanced science (Weinheim, Baden-Wurttemberg, Germany) (2025)

PMID: 41262012

DOI: 10.1002/advs.202505228

Related EMDB entry:

EMD-52833

Deposited:

2024-11-11

Released:

2026-01-20

Last modified:

2026-01-20

Imageset size:

2.72 TB

Imageset DOI:

10.6019/EMPIAR-13184

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe

Image Sets

1. Unalligned multiframe micrographs of alpha-synuclein fibrils formed in aCSF

Category:

micrographs - multiframe

Image format:

EER

No. of images or tilt series:

3510

Image size:

(4096, 4096)

Pixel type:

UNSIGNED 16 BIT INTEGER

Pixel spacing:

(0.754, 0.754)

Details:

EER files from a Falcon 4i detector. Raw micrographs, not motion corrected and picked particles.

Files:

このエントリはPDBjからダウンロードすることはできません。

選択したファイルを無圧縮zipファイルにアーカイブ化してダウンロードします。

ダウンロードするファイル数やサイズによっては、膨大な時間がかかります。また、この機能は不安定で正常に動作しない可能性があり、ダウンロードされたファイルのチェックサムは検証されません。

rsync、aspera、globus 等の利用をおすすめします。

選択したファイルのリストをダウンロードします。

rsyncコマンド等でファイルリストを指定してダウンロードすることが可能です。

rsync -av --files-from=(path-to-filelist) rsync://empiar.pdbj.org/empiar/archive (path-to-destination)

Browse All Files

Quick Links

Browse EMPIAR

Sample Preparation Widget

Volume Browser

Tomo Viewer Prototype

Claim entries to your ORCiD

Talks and Tutorials

EMPIAR Quick tour

Publications

Re-use study

Statistics

EMPIAR in the news

COVID-19 Data Portal

EMDB

BioImage Archive

PDBe

EMNavigator@PDBj

PDBj

Citations

AlignPCA-2D: PCA-reduced Euclidean vector alignment for 2D classification in cryo-EM.

Ramírez-Aportela E, Zarrabeitia OL, Fonseca YC, Ceska T, Subramaniam S, Carazo JM, Sorzano COS. (2026)

A variational framework with composite sparse regularization for cryo-electron tomography reconstruction.

Yu C, Xu Z, Zeng Q, Wan X, El-Messiry H, Zhang F, Han R. (2026)

Helical reconstruction of amyloids in cryoSPARC.

Schaefer JH, O'Neill RT, Donnelly JP, Powers ET, Kelly JW, Lander GC. (2026)

An unattended image-processing pipeline for on-the-fly quality assessment and 3D exploration in cryo-EM.

Marchán Torres D, Conesa P, Garcia A, Iceta M, Broche L, Gragera M, Linares R, Kwong HS, Chichón FJ, Svensson O, Arranz R, Effantin G, Kandiah E, Carazo JM, Sorzano COS. (2026)

CryoFSL: an annotation-efficient, few-shot learning framework for robust protein particle picking in cryo-electron microscopy micrographs.

Poudel B, Gyawali R, Dhakal A, Cheng J, Xu D. (2026)

prismPYP: Power-spectrum and image domain learning for self-supervised micrograph evaluation.

He L, Bartesaghi A. (2026)

CryoSIP: unleashing protein high-resolution Cryo-EM via semantic-instance collaborative picking.

Deng Y, Wang S, Xiang M, Li Y, Zhuo L, Cao D, Fu X, Zou Q. (2026)

Unbend, correction of local beam-induced sample motion in cryo-EM images using a 3D spline model.

Kong L, Zottig X, Elferich J, Grigorieff N. (2026)

CryoVirusDB: An Annotated Dataset for AI-Based Virus Particle Identification in Cryo-EM Micrographs.

Gyawali R, Dhakal A, Wang L, Cheng J. (2026)

CryoWriter: a robotic solution for improved Cryo-EM grid preparation.

Kv C, Ekundayo B, Di Fabrizio M, Mohammed I, Radecke J, Stahlberg H, Kube M. (2026)