Involvement of RBP-J interacting and tubulin-associated protein in the distribution of protein regulator of cytokinesis 1 in mitotic spindles.

The protein regulator of cytokinesis 1 (PRC1) is a key regulator of microtubule crosslinking and bundling, which is crucial for spindle formation and cytokinesis. RITA, the BP-J nteracting and ubulin-ssociated protein, is a microtubule associated protein. We have reported that RITA localizes to mitotic spindles modulating microtubule dynamics and stability as well as to spindle poles affecting the activity of Aurora A.

Deep-Learning-based Automated Identification of Ventriculoperitoneal-Shunt Valve Models from Skull X-rays.

Introduction: Ventriculoperitoneal shunts (VPS) are an essential part of the treatment of hydrocephalus, with numerous valve models available with different ways of indicating pressure levels. The model types often need to be identified on X‑rays to assess pressure levels using a matching template. Artificial intelligence (AI), in particular deep learning, is ideally suited to automate repetitive tasks such as identifying different VPS valve models.

The role of carotid elongation for intervention time and outcome in mechanical thrombectomy for anterior circulation acute ischemic stroke.

Introduction: This study investigates the influence of carotid artery elongation on neurovascular intervention and outcome in acute stroke treatments proposing an easily assessable imaging marker for carotid elongation.

Methods: 118 patients who underwent mechanical thrombectomy for middle cerebral artery occlusions were included. The carotid elongation ratio (CER), center-line artery length to scan's Z-axis, was measured on the affected side in CT-angiographies.

Simulated brain networks reflecting progression of Parkinson's disease.

The neurodegenerative progression of Parkinson's disease affects brain structure and function and, concomitantly, alters the topological properties of brain networks. The network alteration accompanied by motor impairment and the duration of the disease has not yet been clearly demonstrated in the disease progression. In this study, we aim to resolve this problem with a modeling approach using the reduced Jansen-Rit model applied to large-scale brain networks derived from cross-sectional MRI data.

Language aptitude is related to the anatomy of the transverse temporal gyri.

Why is it that some people seem to learn new languages faster and more easily than others? The present study investigates the neuroanatomical basis of language learning aptitude, with a focus on the multiplication pattern of the transverse temporal gyrus/gyri (TTG/TTGs) of the auditory cortex. The size and multiplication pattern of the first TTG (i.e.

Prehospital telemedicine support for urban stroke care: Analysis of current state of care and conceptualization.

Background: The reduction of processing times in the treatment of acute ischemic stroke is of outstanding importance. Our objective is to analyze the acute stroke care chain from onset to treatment in a city in Germany comprising three stroke units. Additionally, we discuss solutions for detected treatment delays.

Nonlinear Langevin functionals for a driven probe.

When a probe particle immersed in a fluid with nonlinear interactions is subject to strong driving, the cumulants of the stochastic force acting on the probe are nonlinear functionals of the driving protocol. We present a Volterra series for these nonlinear functionals by applying nonlinear response theory in a path integral formalism, where the emerging kernels are shown to be expressed in terms of connected equilibrium correlation functions. The first cumulant is the mean force, the second cumulant characterizes the non-equilibrium force fluctuations (noise), and higher order cumulants quantify non-Gaussian fluctuations.

Reproducibility and across-site transferability of an improved deep learning approach for aneurysm detection and segmentation in time-of-flight MR-angiograms.

This study aimed to (1) replicate a deep-learning-based model for cerebral aneurysm segmentation in TOF-MRAs, (2) improve the approach by testing various fully automatic pre-processing pipelines, and (3) rigorously validate the model's transferability on independent, external test-datasets. A convolutional neural network was trained on 235 TOF-MRAs acquired on local scanners from a single vendor to segment intracranial aneurysms. Different pre-processing pipelines including bias field correction, resampling, cropping and intensity-normalization were compared regarding their effect on model performance.

Surgical and endovascular cerebral revascularization for cerebral vasculitis with inflammatory vessel stenosis: a case series.

Autoimmune vasculitides affect the cerebral vasculature significantly in a considerable number of cases. When immunosuppressive treatments fail to prevent stenosis in cerebral vessels, treatment options for affected patients become limited. In this case series, we present four cases of pharmacoresistant vasculitis with recurrent transient ischemic attacks (TIAs) or stroke successfully treated with either extracranial-intracranial (EC-IC) bypass surgery or endovascular stenting.

Normal cohorts in automated brain atrophy estimation: how many healthy subjects to include?

Objectives: This study investigates the influence of normal cohort (NC) size and the impact of different NCs on automated MRI-based brain atrophy estimation.

Methods: A pooled NC of 3945 subjects (NC) was retrospectively created from five publicly available cohorts. Voxel-wise gray matter volume atrophy maps were calculated for 48 Alzheimer's disease (AD) patients (55-82 years) using veganbagel and dynamic normal templates with an increasing number of healthy subjects randomly drawn from NC (initially three, and finally 100 subjects).

Prediction of therapy response of breast cancer patients with machine learning based on clinical data and imaging data derived from breast [F]FDG-PET/MRI.

Purpose: To evaluate if a machine learning prediction model based on clinical and easily assessable imaging features derived from baseline breast [F]FDG-PET/MRI staging can predict pathologic complete response (pCR) in patients with newly diagnosed breast cancer prior to neoadjuvant system therapy (NAST).

Methods: Altogether 143 women with newly diagnosed breast cancer (54 ± 12 years) were retrospectively enrolled. All women underwent a breast [F]FDG-PET/MRI, a histopathological workup of their breast cancer lesions and evaluation of clinical data.

Diagnostic Value of Perfusion Parameters for Differentiation of Underlying Etiology in Internal Carotid Artery Occlusions.

Purpose: Occlusions of the internal carotid artery (ICA) may be caused by dissection, embolic or macroangiopathic pathogenesis, which partially influences the treatment; however, inferring the underlying etiology in computed tomography angiography can be challenging. In this study, we investigated whether computed tomography perfusion (CT-P) parameters could be used to distinguish between etiologies.

Methods: Patients who received CT‑P in acute ischemic stroke due to ICA occlusion between 2012 and 2019 were retrospectively analyzed.

Memory-induced alignment of colloidal dumbbells.

When a colloidal probe is forced through a viscoelastic fluid which is characterized by a long stress-relaxation time, the fluid is excited out of equilibrium. This is leading to a number of interesting effects including a non-trivial recoil of the probe when the driving force is removed. Here, we experimentally and theoretically investigate the transient recoil dynamics of non-spherical particles, i.

Prediction of cognitive performance differences in older age from multimodal neuroimaging data.

Differences in brain structure and functional and structural network architecture have been found to partly explain cognitive performance differences in older ages. Thus, they may serve as potential markers for these differences. Initial unimodal studies, however, have reported mixed prediction results of selective cognitive variables based on these brain features using machine learning (ML).

Serotonergic modulation of normal and abnormal brain dynamics: The genetic influence of the TPH2 G-703T genotype and DNA methylation on wavelet variance in children and adolescents with and without ADHD.

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that often persists into adulthood. Core symptoms of ADHD, such as impulsivity, are caused by an interaction of genetic and environmental factors. Epigenetic modifications of DNA, such as DNA methylation, are thought to mediate the interplay of these factors.

Brain-age prediction: A systematic comparison of machine learning workflows.

The difference between age predicted using anatomical brain scans and chronological age, i.e., the brain-age delta, provides a proxy for atypical aging.

How are mobility and friction related in viscoelastic fluids?

The motion of a colloidal probe in a viscoelastic fluid is described by friction or mobility, depending on whether the probe is moving with a velocity or feeling a force. While the Einstein relation describes an inverse relationship valid for Newtonian solvents, both concepts are generalized to time-dependent memory kernels in viscoelastic fluids. We theoretically and experimentally investigate their relation by considering two observables: the recoil after releasing a probe that was moved through the fluid and the equilibrium mean squared displacement (MSD).

Whole-brain dynamical modelling for classification of Parkinson's disease.

Simulated whole-brain connectomes demonstrate enhanced inter-individual variability depending on the data processing and modelling approach. By considering the human brain connectome as an individualized attribute, we investigate how empirical and simulated whole-brain connectome-derived features can be utilized to classify patients with Parkinson's disease against healthy controls in light of varying data processing and model validation. To this end, we applied simulated blood oxygenation level-dependent signals derived by a whole-brain dynamical model simulating electrical signals of neuronal populations to reveal differences between patients and controls.

Clinical Decision Support for Axillary Lymph Node Staging in Newly Diagnosed Breast Cancer Patients Based on F-FDG PET/MRI and Machine Learning.

In addition to its high prognostic value, the involvement of axillary lymph nodes in breast cancer patients also plays an important role in therapy planning. Therefore, an imaging modality that can determine nodal status with high accuracy in patients with primary breast cancer is desirable. Our purpose was to investigate whether, in newly diagnosed breast cancer patients, machine-learning prediction models based on simple assessable imaging features on MRI or PET/MRI are able to determine nodal status with performance comparable to that of experienced radiologists; whether such models can be adjusted to achieve low rates of false-negatives such that invasive procedures might potentially be omitted; and whether a clinical framework for decision support based on simple imaging features can be derived from these models.

Perception of Different Tone Contrasts at Sub-Lexical and Lexical Levels by Dutch Learners of Mandarin Chinese.

This study explores the difficulties in distinguishing different lexical tone contrasts at both sub-lexical and lexical levels for beginning and advanced Dutch learners of Mandarin, using a sequence-recall task and an auditory lexical decision task. In both tasks, the Tone 2-Tone 3 contrast is most prone to errors for both groups of learners. A significant improvement in the advanced group was found for this tone contrast in the sub-lexical sequence recall task, but not in the lexical decision task.

Impact of defacing on automated brain atrophy estimation.

Background: Defacing has become mandatory for anonymization of brain MRI scans; however, concerns regarding data integrity were raised. Thus, we systematically evaluated the effect of different defacing procedures on automated brain atrophy estimation.

Methods: In total, 268 Alzheimer's disease patients were included from ADNI, which included unaccelerated (n = 154), within-session unaccelerated repeat (n = 67) and accelerated 3D T1 imaging (n = 114).

Barrier Crossing in a Viscoelastic Bath.

We investigate the hopping dynamics of a colloidal particle across a potential barrier and within a viscoelastic, i.e., non-Markovian, bath and report two clearly separated timescales in the corresponding waiting time distributions.