PICALM Rescues Endocytic Defects Caused by the Alzheimer's Disease Risk Factor APOE4.

The ε4 allele of apolipoprotein E (APOE4) is a genetic risk factor for many diseases, including late-onset Alzheimer's disease (AD). We investigate the cellular consequences of APOE4 in human iPSC-derived astrocytes, observing an endocytic defect in APOE4 astrocytes compared with their isogenic APOE3 counterparts. Given the evolutionarily conserved nature of endocytosis, we built a yeast model to identify genetic modifiers of the endocytic defect associated with APOE4.

Translocon Declogger Ste24 Protects against IAPP Oligomer-Induced Proteotoxicity.

Aggregates of human islet amyloid polypeptide (IAPP) in the pancreas of patients with type 2 diabetes (T2D) are thought to contribute to β cell dysfunction and death. To understand how IAPP harms cells and how this might be overcome, we created a yeast model of IAPP toxicity. Ste24, an evolutionarily conserved protease that was recently reported to degrade peptides stuck within the translocon between the cytoplasm and the endoplasmic reticulum, was the strongest suppressor of IAPP toxicity.

A Genetic Tool to Track Protein Aggregates and Control Prion Inheritance.

Protein aggregation is a hallmark of many diseases but also underlies a wide range of positive cellular functions. This phenomenon has been difficult to study because of a lack of quantitative and high-throughput cellular tools. Here, we develop a synthetic genetic tool to sense and control protein aggregation.

Prion-like proteins sequester and suppress the toxicity of huntingtin exon 1.

Expansions of preexisting polyglutamine (polyQ) tracts in at least nine different proteins cause devastating neurodegenerative diseases. There are many unique features to these pathologies, but there must also be unifying mechanisms underlying polyQ toxicity. Using a polyQ-expanded fragment of huntingtin exon-1 (Htt103Q), the causal protein in Huntington disease, we and others have created tractable models for investigating polyQ toxicity in yeast cells.

Modular aspects of kinesin force generation machinery.

The motor head of kinesin carries out microtubule binding, ATP hydrolysis, and force generation. Despite a high level of sequence and structural conservation, subtle variations in subdomains of the motor head determine family-specific properties. In particular, both Kinesin-1 (Kin-1) and Kinesin-5 (Kin-5) walk processively to the microtubule plus-end, yet show distinct motility characteristics suitable for their functions.

From two-dimensional colloidal self-assembly to three-dimensional nanolithography.

A number of "top-down" lithographic and "bottom-up" self-assembly methods have been developed to fabricate three-dimensional (3D) nanostructures to support the recent advances in nanotechnology. But they are limited by a number of factors such as fabrication cost, pattern resolution, and/or flexibility of geometry. Here we present a 3D nanolithography process that utilizes self-assembled nanospheres to create a periodic array of focal spots, which are then replicated across multiple depth in a transparent medium according to the Talbot effect.

Bacterial nanofluidic structures for medicine and engineering.

Bacteria are microscopic, single-celled organisms that utilize a variety of nanofluidic structures. One of the best known and widely used nanofluidic structures that are derived from bacteria is the alpha-hemolysin pore. This pore, which self-assembles in lipid bilayers, has been used for a wide variety of sensing applications, most notably, DNA sensing.

Modelling and analysis of time-variant directed interrelations between brain regions based on BOLD-signals.

Time-variant Granger Causality Index (tvGCI) was applied to simulated and measured BOLD signals to investigate the reliability of time-variant analysis approaches for the identification of directed interrelations between brain areas on the basis of fMRI data. Single-shot fMRI data of a single image slice with short repetition times (200 ms, 16000 frames/subject, 64x64 voxels) were acquired from 5 healthy subjects during an externally-driven, self-paced finger-tapping paradigm (57-59 single taps for each subject). BOLD signals were derived from the pre-supplementary motor area (preSMA), the supplementary motor area (SMA), and the primary motor cortex (M1).

Visualization of flagellar interactions on bacterial carpets.

Methods for the in-depth study of the physics of microscale actuation of microfluidics environments by flagellated bacteria 'teamsters' have been developed. These methods, which include single and multi-colour fluorescent labelling and electron microscopy allow for the analysis of the effect that individual flagellar filaments have on bacterially driven microstructures, and allow for the investigation of the interaction and coordination of flagellar filaments of neighbouring bacteria on densely packed monolayers of bacteria, 'bacterial carpets'. We show that the flagella of bacteria that are immobilized on a surface often interact with each other, and that the flagella of these bacteria do not often form multi-flagella bundles that are aligned with the cell body.

How do brain areas communicate during the processing of noxious stimuli? An analysis of laser-evoked event-related potentials using the Granger causality index.

Several imaging techniques have identified different brain areas involved in the processing of noxious stimulation and thus in the constitution of pain. However, only little is known how these brain areas communicate with one another after activation by stimulus processing and which areas directionally affect or modulate the activity of succeeding areas. One measure for the analysis of such interactions is represented by the Granger Causality Index (GCI).

Tracking the time-varying cortical connectivity patterns by adaptive multivariate estimators.

The directed transfer function (DTF) and the partial directed coherence (PDC) are frequency-domain estimators that are able to describe interactions between cortical areas in terms of the concept of Granger causality. However, the classical estimation of these methods is based on the multivariate autoregressive modelling (MVAR) of time series, which requires the stationarity of the signals. In this way, transient pathways of information transfer remains hidden.

Cortical network dynamics during foot movements.

The present work intends to evaluate the dynamics of the cerebral networks during the preparation and the execution of the foot movement. In order to achieve this objective, we have used mathematical tools capable of estimating the cortical activity via high-resolution EEG techniques. Afterwards we estimated, the instantaneous relationships occurring among the time-series of sixteen regions of interest (ROIs) in the Alpha (7-12 Hz) and Beta (13-29 Hz) band through the adaptive multivariate autoregressive models.

Features extraction from time-varying cortical networks adopting a theoretical graph approach.

In this work, a novel approach is proposed in order to capture relevant features related to the structure and organization of the functional brain networks estimated in the time-frequency domain. To achieve this, we used a cascade of computational tools able to estimate first the electrical activity of the cortical surface by using high resolution EEG techniques. Then, on the cortical signals from different regions of interests we estimated the time-varying functional connectivity patterns by means of the adaptive Partial Directed Coherence.

Time-varying cortical connectivity by adaptive multivariate estimators applied to a combined foot-lips movement.

In this paper we propose the use of an adaptive multivariate approach to define time-varying multivariate estimators based on the Directed Transfer Function (DTF) and the Partial Directed Coherence (PDC). DTF and PDC are frequency-domain estimators that are able to describe interactions between cortical areas in terms of the concept of Granger causality. Time-varying DTF and PDC were obtained by the adaptive recursive fit of an MVAR model with time-dependent parameters, by means of a generalized recursive least-square (RLS) algorithm, taking into consideration a set of EEG epochs.

Estimation of the time-varying cortical connectivity patterns by the adaptive multivariate estimators in high resolution EEG studies.

The Directed Transfer Function (DTF) and the Partial Directed Coherence (PDC) are frequency-domain estimators, based on the multivariate autoregressive modelling (MVAR) of time series, that are able to describe interactions between cortical areas in terms of the concept of Granger causality. However, the classical estimation of these methods requires the stationary of the signals. In this way, transient pathways of information transfer remains hidden.

Coupled oscillators for modeling and analysis of EEG/MEG oscillations.

This study presents three EEG/MEG applications in which the modeling of oscillatory signal components offers complementary analysis and an improved explanation of the underlying generator structures. Coupled oscillator networks were used for modeling. Parameters of the corresponding ordinary coupled differential equation (ODE) system are identified using EEG/MEG data and the resulting solution yields the modeled signals.

Detection of directed information flow in biosignals.

Several analysis techniques have been developed for time series to detect interactions in multidimensional dynamic systems. When analyzing biosignals generated by unknown dynamic systems, awareness of the different concepts upon which these analysis techniques are based, as well as the particular aspects the methods focus on, is a basic requirement for drawing reliable conclusions. For this purpose, we compare four different techniques for linear time series analysis.

Time-variant analysis of fast-fMRI and dynamic contrast agent MRI sequences as examples of 4-dimensional image analysis.

Objectives: Image sequences with time-varying information content need appropriate analysis strategies. The exploration of directed information transfer (interactions) between neuronal assemblies is one of the most important aims of current functional MRI (fMRI) analysis. Additionally, we examined perfusion maps in dynamic contrast agent MRI sequences of stroke patients.

Development of interaction measures based on adaptive non-linear time series analysis of biomedical signals.

An important feature of interaction between two signal components is the direction of the interaction. Recently, different methods have been developed and applied for detecting the direction of interactions. Besides frequency-dependent methods, Granger causality is a well-known frequency-independent approach.

The use of time-variant EEG Granger causality for inspecting directed interdependencies of neural assemblies.

Understanding of brain functioning requires the investigation of activated cortical networks, in particular the detection of interactions between different cortical sites. Commonly, coherence and correlation are used to describe interrelations between EEG signals. However, on this basis, no statements on causality or the direction of their interrelations are possible.

[Brief causal relations in EEG based on adaptive Granger causality].

Commonly, coherence and correlation are used to describe interrelations between EEG signals. But, on this basis, the investigation of causality or direction of interrelations is not possible. The general idea of causality between two signals may be expressed in terms of upgrading the predictability of one signal bye the knowledge of the past of the other signal.

[Personality and personality disorders II. The Specificity of the DAPP-model as a diagnostic system for personality disorders].

The 'Dimensional Assessment of Personality Pathology - Basic Questionnaire' (DAPP) measures 18 traits to provide a systematic representation of the overall domain of personality disorders (PD). The present study investigated the relationships between DAPP personality profiles and dimensional assessments of DSM-IV PD in general population subjects (n = 156), and a sample of 220 nonpsychotic psychiatric patients (including n = 67 PD patients). Using nonmetric multidimensional scaling models the similarities between the 18 DAPP-factors and the dimensional scores of the 12 DSM-IV PD (inclusive appendix) were graphically represented in a 2-dimensional similarity-system.

[Personality and personality disorders I. Universality and sensitivity of dimensional personality models as diagnostic systems for personality disorders].

Objective: A dimensional diagnostic system for personality disorders (PD) postulates continuous transitions from normal to disordered personalities (continuity hypothesis) and universal validity of basic personality dimensions (universal hypothesis). In the present study three dimensional personality models that claim to provide a systematic representation of the overall domain of personality disorders were compared: the Big-Five model proposed by Costa and McCrae, the psychobiological model proposed by Cloninger and colleagues, and the "Dimensional Assessment of Personal Pathology (DAPP)" model proposed by Livesley and colleagues.

Method: The "Six Factor Test" (SFT) measuring the Big-Five factors of personality, the "Temperament and Character Inventory (TCI)" measuring 4 temperament and 3 character dimensions, and the DAPP measuring 18 basic traits and 4 second ordered factors were administered to general population subjects (n = 156), and a clinical sample (n = 220) including a subsample of 69 patients with at least one diagnosis of DSM-IV PD.