Behavioral and psychological symptoms and cognitive decline in patients with amnestic MCI and mild AD: a two-year follow-up study.

BACKGROUND: Mild cognitive impairment (MCI) has been defined as a transitional state between normal aging and dementia. In many cases, MCI represents an early stage of developing cognitive impairment. Patients diagnosed with MCI do not meet the criteria for dementia as their general intellect and everyday activities are preserved, although minor changes in instrumental activities of daily living (ADL) may occur. However, they may exhibit significant behavioral and psychological signs and symptoms (BPS), also frequently observed in patients with Alzheimer's disease (AD). Hence, we wondered to what extent specific BPS are associated with cognitive decline in participants with MCI or AD. METHODS: Our sample consisted of 164 participants, including 46 patients with amnestic (single or multi-domain) MCI and 54 patients with AD, as well as 64 control participants without cognitive disorders. Global cognitive performance, BPS, and ADL were assessed using validated clinical methods at baseline and at two-year follow-up. RESULTS: The BPS variability over the follow-up period was more pronounced in the MCI group than in patients with AD: some BPS improve, others occur newly or worsen, while others still remain unchanged. Moreover, specific changes in BPS were associated with a rapid deterioration of the global cognitive level in MCI patients. In particular, an increase of euphoria, eating disorders, and aberrant motor behavior, as well as worsened sleep quality, predicted a decline in cognitive functioning. CONCLUSIONS: Our findings confirm a higher variability of BPS over time in the MCI group than in AD patients. Moreover, our results provide evidence of associations between specific BPS and cognitive decline in the MCI group that might suggest a risk of conversion of individuals with amnestic MCI to AD.

In cortical neurons HDAC3 suppresses RD4-dependent SMRT export

The transcriptional corepressor SMRT controls neuronal responsiveness of several transcription factors and can regulate neuroprotective and neurogenic pathways. SMRT is a multi-domain protein that complexes with HDAC3 as well as being capable of interactions with HDACs 1, 4, 5 and 7. We previously showed that in rat cortical neurons, nuclear localisation of SMRT requires histone deacetylase activity: Inhibition of class I/II HDACs by treatment with trichostatin A (TSA) causes redistribution of SMRT to the cytoplasm, and potentiates the activation of SMRT-repressed nuclear receptors. Here we have sought to identify the HDAC(s) and region(s) of SMRT responsible for anchoring it in the nucleus under normal circumstances and for mediating nuclear export following HDAC inhibition. We show that in rat cortical neurons SMRT export can be triggered by treatment with the class I-preferring HDAC inhibitor valproate and the HDAC2/3-selective inhibitor apicidin, and by HDAC3 knockdown, implicating HDAC3 activity as being required to maintain SMRT in the nucleus. HDAC3 interaction with SMRT's deacetylation activation domain (DAD) is known to be important for activation of HDAC3 deacetylase function. Consistent with a role for HDAC3 activity in promoting SMRT nuclear localization, we found that inactivation of SMRT's DAD by deletion or point mutation triggered partial redistribution of SMRT to the cytoplasm. We also investigated whether other regions of SMRT were involved in mediating nuclear export following HDAC inhibition. TSA- and valproate-induced SMRT export was strongly impaired by deletion of its repression domain-4 (RD4). Furthermore, over-expression of a region of SMRT containing the RD4 region suppressed TSA-induced export of full-length SMRT. Collectively these data support a model whereby SMRT's RD4 region can recruit factors capable of mediating nuclear export of SMRT, but whose function and/or recruitment is suppressed by HDAC3 activity. Furthermore, they underline the fact that HDAC inhibitors can cause reorganization and redistribution of corepressor complexes.

The Ligand and Membrane-binding Behaviour of the Phosphatidylinositol Transfer Proteins (PITPa & PITPb)

Human Class I phosphatidylinositol transfer proteins (PITPs) exists in two forms: PITPα and PITPβ. PITPs are believed to be lipid transfer proteins based on their capacity to transfer either phosphatidylinositol (PI) or phosphatidylcholine (PC) between membrane compartments in vitro. In Drosophila, the PITP domain is found to be part of a multi-domain protein named retinal degeneration B (RdgBα). The PITP domain of RdgBα shares 40 % sequence identity with PITPα and has been shown to possess PI and PC binding and transfer activity. The detailed molecular mechanism of ligand transfer by the human PITPs and the Drosophila PITP domain remains to be fully established. Here, we investigated the membrane interactions of these proteins using dual polarization interferometry (DPI). DPI is a technique that measures protein binding affinity to a flat immobilized lipid bilayer. In addition, we also measured how quickly these proteins transfer their ligands to lipid vesicles using a fluorescence resonance energy transfer (FRET)-based assay. DPI investigations suggest that PITPβ had a two-fold higher affinity for membranes compared to PITPα. This was reflected by a four-fold faster ligand transfer rate for PITPβ in comparison to PITPα as determined by the FRET assay. Interestingly, DPI analysis also demonstrated that PI-bound human PITPs have lower membrane affinity compared to PC-bound PITPs. In addition, the FRET studies demonstrated the significance of membrane curvature in the ligand transfer rate of PITPs. The ligand transfer rate was higher when the accepting vesicles were highly curved. Furthermore, when the accepting vesicles contained phosphatidic acid (PA) which have smaller head groups, the transfer rate increased. In contrast, when the accepting vesicles contained phosphoinositides which have larger head groups, the transfer rate was diminished. However, PI, the favorite ligand of PITPs, or the presence of anionic lipids did not appear to influence the ligand transfer rate of PITPs. Both DPI and FRET examinations revealed that the PITP domain of RdgBα was able to bind to membranes. However, the RdgBα PITP domain appears to be a poor binder and transporter of PC.

Structural, magnetic and electrical properties of the sol-gel prepared Li0.5Fe2.5O4 fine particles

Fine particles of lithium ferrite were synthesized by the sol-gel method. By subsequent heat treatment at different temperatures, lithium ferrites of different grain sizes were prepared. A structural characterization of all the samples was conducted by the x-ray diffraction technique. A grain size of around 12 nm was observed for Li0.5Fe2.5O4 obtained through the sol-gel method. Magnetic properties of lithium ferrite nanoparticles with grain size ranging from 12 to 32 nm were studied. Magnetization measurements showed that Li0.5Fe2.5O4 fine particles exhibit a deviation from the predicted magnetic behaviour. The as-prepared sample of lithium ferrite showed a maximum saturation magnetization of 75 emu g−1. Variation of coercivity is attributed to the transition from multi-domain to single domain nature. Dielectric permittivity and ac conductivity of all the samples were evaluated as a function of frequency, temperature and grain size. Variation of permittivity and ac conductivity with frequency reveals that the dispersion is due to the Maxwell–Wagner type interfacial polarization

The prediction of seasonal and inter-annual climate variations and their impacts on the water resources in the eastern seaboard of Thailand

The research of this thesis dissertation covers developments and applications of short-and long-term climate predictions. The short-term prediction emphasizes monthly and seasonal climate, i.e. forecasting from up to the next month over a season to up to a year or so. The long-term predictions pertain to the analysis of inter-annual- and decadal climate variations over the whole 21st century. These two climate prediction methods are validated and applied in the study area, namely, Khlong Yai (KY) water basin located in the eastern seaboard of Thailand which is a major industrial zone of the country and which has been suffering from severe drought and water shortage in recent years. Since water resources are essential for the further industrial development in this region, a thorough analysis of the potential climate change with its subsequent impact on the water supply in the area is at the heart of this thesis research. The short-term forecast of the next-season climate, such as temperatures and rainfall, offers a potential general guideline for water management and reservoir operation. To that avail, statistical models based on autoregressive techniques, i.e., AR-, ARIMA- and ARIMAex-, which includes additional external regressors, and multiple linear regression- (MLR) models, are developed and applied in the study region. Teleconnections between ocean states and the local climate are investigated and used as extra external predictors in the ARIMAex- and the MLR-model and shown to enhance the accuracy of the short-term predictions significantly. However, as the ocean state – local climate teleconnective relationships provide only a one- to four-month ahead lead time, the ocean state indices can support only a one-season-ahead forecast. Hence, GCM- climate predictors are also suggested as an additional predictor-set for a more reliable and somewhat longer short-term forecast. For the preparation of “pre-warning” information for up-coming possible future climate change with potential adverse hydrological impacts in the study region, the long-term climate prediction methodology is applied. The latter is based on the downscaling of climate predictions from several single- and multi-domain GCMs, using the two well-known downscaling methods SDSM and LARS-WG and a newly developed MLR-downscaling technique that allows the incorporation of a multitude of monthly or daily climate predictors from one- or several (multi-domain) parent GCMs. The numerous downscaling experiments indicate that the MLR- method is more accurate than SDSM and LARS-WG in predicting the recent past 20th-century (1971-2000) long-term monthly climate in the region. The MLR-model is, consequently, then employed to downscale 21st-century GCM- climate predictions under SRES-scenarios A1B, A2 and B1. However, since the hydrological watershed model requires daily-scale climate input data, a new stochastic daily climate generator is developed to rescale monthly observed or predicted climate series to daily series, while adhering to the statistical and geospatial distributional attributes of observed (past) daily climate series in the calibration phase. Employing this daily climate generator, 30 realizations of future daily climate series from downscaled monthly GCM-climate predictor sets are produced and used as input in the SWAT- distributed watershed model, to simulate future streamflow and other hydrological water budget components in the study region in a multi-realization manner. In addition to a general examination of the future changes of the hydrological regime in the KY-basin, potential future changes of the water budgets of three main reservoirs in the basin are analysed, as these are a major source of water supply in the study region. The results of the long-term 21st-century downscaled climate predictions provide evidence that, compared with the past 20th-reference period, the future climate in the study area will be more extreme, particularly, for SRES A1B. Thus, the temperatures will be higher and exhibit larger fluctuations. Although the future intensity of the rainfall is nearly constant, its spatial distribution across the region is partially changing. There is further evidence that the sequential rainfall occurrence will be decreased, so that short periods of high intensities will be followed by longer dry spells. This change in the sequential rainfall pattern will also lead to seasonal reductions of the streamflow and seasonal changes (decreases) of the water storage in the reservoirs. In any case, these predicted future climate changes with their hydrological impacts should encourage water planner and policy makers to develop adaptation strategies to properly handle the future water supply in this area, following the guidelines suggested in this study.

Poder e influencia en el liderazgo transformacional

Como proyecto de grado, el presente trabajo consiste en una revisión teórica de los conceptos de liderazgo, poder e influencia, junto con las posibles relaciones que entre ellos se pueden presentar. Para ello, cada concepto es definido de manera individual, y con base en ello, se identifica la dependencia que tienen estos conceptos entre sí y la importancia dentro del desarrollo del liderazgo transformacional actual. Para lograr lo propuesto, se llevó a cabo la revisión de una parte de la literatura académica presente en libros, revistas académicas, bases de datos y documentos relacionados con los temas y conceptos tratados. A partir de ello, se entendió la evolución del concepto del liderazgo y los enfoques presentados desde la década de los 1920´s hasta la actualidad, junto con el modelo de rango total y el tipo transaccional y transformacional del liderazgo, para luego definir el papel y la importancia de los conceptos de poder, los tipos de poder, la influencia y las tácticas de influencia, y así, identificar las posibles relaciones que se presentan entre los conceptos y la importancia de estos en el entorno organizacional actual.

Dynamic load balancing for the distributed mining of molecular structures

In molecular biology, it is often desirable to find common properties in large numbers of drug candidates. One family of methods stems from the data mining community, where algorithms to find frequent graphs have received increasing attention over the past years. However, the computational complexity of the underlying problem and the large amount of data to be explored essentially render sequential algorithms useless. In this paper, we present a distributed approach to the frequent subgraph mining problem to discover interesting patterns in molecular compounds. This problem is characterized by a highly irregular search tree, whereby no reliable workload prediction is available. We describe the three main aspects of the proposed distributed algorithm, namely, a dynamic partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiverinitiated load balancing algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer Institute’s HIV-screening data set, where we were able to show close-to linear speedup in a network of workstations. The proposed approach also allows for dynamic resource aggregation in a non dedicated computational environment. These features make it suitable for large-scale, multi-domain, heterogeneous environments, such as computational grids.

Decentralized load balancing for highly irregular search problems

In this paper, we present a distributed computing framework for problems characterized by a highly irregular search tree, whereby no reliable workload prediction is available. The framework is based on a peer-to-peer computing environment and dynamic load balancing. The system allows for dynamic resource aggregation, does not depend on any specific meta-computing middleware and is suitable for large-scale, multi-domain, heterogeneous environments, such as computational Grids. Dynamic load balancing policies based on global statistics are known to provide optimal load balancing performance, while randomized techniques provide high scalability. The proposed method combines both advantages and adopts distributed job-pools and a randomized polling technique. The framework has been successfully adopted in a parallel search algorithm for subgraph mining and evaluated on a molecular compounds dataset. The parallel application has shown good calability and close-to linear speedup in a distributed network of workstations.

A hierarchical distributed approach for mining molecular fragments

Recently, two approaches have been introduced that distribute the molecular fragment mining problem. The first approach applies a master/worker topology, the second approach, a completely distributed peer-to-peer system, solves the scalability problem due to the bottleneck at the master node. However, in many real world scenarios the participating computing nodes cannot communicate directly due to administrative policies such as security restrictions. Thus, potential computing power is not accessible to accelerate the mining run. To solve this shortcoming, this work introduces a hierarchical topology of computing resources, which distributes the management over several levels and adapts to the natural structure of those multi-domain architectures. The most important aspect is the load balancing scheme, which has been designed and optimized for the hierarchical structure. The approach allows dynamic aggregation of heterogenous computing resources and is applied to wide area network scenarios.

Efficient mining of discriminative molecular fragments

Frequent pattern discovery in structured data is receiving an increasing attention in many application areas of sciences. However, the computational complexity and the large amount of data to be explored often make the sequential algorithms unsuitable. In this context high performance distributed computing becomes a very interesting and promising approach. In this paper we present a parallel formulation of the frequent subgraph mining problem to discover interesting patterns in molecular compounds. The application is characterized by a highly irregular tree-structured computation. No estimation is available for task workloads, which show a power-law distribution in a wide range. The proposed approach allows dynamic resource aggregation and provides fault and latency tolerance. These features make the distributed application suitable for multi-domain heterogeneous environments, such as computational Grids. The distributed application has been evaluated on the well known National Cancer Institute’s HIV-screening dataset.

PDM 2006: Proceedings of the International Workshop on Data Mining

Recently major processor manufacturers have announced a dramatic shift in their paradigm to increase computing power over the coming years. Instead of focusing on faster clock speeds and more powerful single core CPUs, the trend clearly goes towards multi core systems. This will also result in a paradigm shift for the development of algorithms for computationally expensive tasks, such as data mining applications. Obviously, work on parallel algorithms is not new per se but concentrated efforts in the many application domains are still missing. Multi-core systems, but also clusters of workstations and even large-scale distributed computing infrastructures provide new opportunities and pose new challenges for the design of parallel and distributed algorithms. Since data mining and machine learning systems rely on high performance computing systems, research on the corresponding algorithms must be on the forefront of parallel algorithm research in order to keep pushing data mining and machine learning applications to be more powerful and, especially for the former, interactive. To bring together researchers and practitioners working in this exciting field, a workshop on parallel data mining was organized as part of PKDD/ECML 2006 (Berlin, Germany). The six contributions selected for the program describe various aspects of data mining and machine learning approaches featuring low to high degrees of parallelism: The first contribution focuses the classic problem of distributed association rule mining and focuses on communication efficiency to improve the state of the art. After this a parallelization technique for speeding up decision tree construction by means of thread-level parallelism for shared memory systems is presented. The next paper discusses the design of a parallel approach for dis- tributed memory systems of the frequent subgraphs mining problem. This approach is based on a hierarchical communication topology to solve issues related to multi-domain computational envi- ronments. The forth paper describes the combined use and the customization of software packages to facilitate a top down parallelism in the tuning of Support Vector Machines (SVM) and the next contribution presents an interesting idea concerning parallel training of Conditional Random Fields (CRFs) and motivates their use in labeling sequential data. The last contribution finally focuses on very efficient feature selection. It describes a parallel algorithm for feature selection from random subsets. Selecting the papers included in this volume would not have been possible without the help of an international Program Committee that has provided detailed reviews for each paper. We would like to also thank Matthew Otey who helped with publicity for the workshop.

Optimisation of recombinant production of active human cardiac SERCA2a ATPase

Methods for recombinant production of eukaryotic membrane proteins, yielding sufficient quantity and quality of protein for structural biology, remain a challenge. We describe here, expression and purification optimisation of the human SERCA2a cardiac isoform of Ca2+ translocating ATPase, using Saccharomyces cerevisiae as the heterologous expression system of choice. Two different expression vectors were utilised, allowing expression of C-terminal fusion proteins with a biotinylation domain or a GFP- His8 tag. Solubilised membrane fractions containing the protein of interest were purified onto Streptavidin-Sepharose, Ni-NTA or Talon resin, depending on the fusion tag present. Biotinylated protein was detected using specific antibody directed against SERCA2 and, advantageously, GFP-His8 fusion protein was easily traced during the purification steps using in-gel fluorescence. Importantly, talon resin affinity purification proved more specific than Ni-NTA resin for the GFP-His8 tagged protein, providing better separation of oligomers present, during size exclusion chromatography. The optimised method for expression and purification of human cardiac SERCA2a reported herein, yields purified protein (> 90%) that displays a calcium-dependent thapsigargin-sensitive activity and is suitable for further biophysical, structural and physiological studies. This work provides support for the use of Saccharomyces cerevisiae as a suitable expression system for recombinant production of multi-domain eukaryotic membrane proteins.

GTP binding controls complex formation by the human ROCO protein MASL1

The human ROCO proteins are a family of multi-domain proteins sharing a conserved ROC-COR supra-domain. The family has four members: leu- cine-rich repeat kinase 1 (LRRK1), leucine-rich repeat kinase 2 (LRRK2), death-associated protein kinase 1 (DAPK1) and malignant fibrous histiocy- toma amplified sequences with leucine-rich tandem repeats 1 (MASL1). Previous studies of LRRK1/2 and DAPK1 have shown that the ROC (Ras of complex proteins) domain can bind and hydrolyse GTP, but the cellular consequences of this activity are still unclear. Here, the first biochemical characterization of MASL1 and the impact of GTP binding on MASL1 complex formation are reported. The results demonstrate that MASL1, similar to other ROCO proteins, can bind guanosine nucleotides via its ROC domain. Furthermore, MASL1 exists in two distinct cellular com- plexes associated with heat shock protein 60, and the formation of a low molecular weight pool of MASL1 is modulated by GTP binding. Finally, loss of GTP enhances MASL1 toxicity in cells. Taken together, these data point to a central role for the ROC/GTPase domain of MASL1 in the reg- ulation of its cellular function.

Estudo das características magnéticas e absorvedoras das ferritas de nizn, niznmn, mnzn, nimg, nicuzn e nicuznmg obtidas via método do citrato precursor

Were synthesized systems Ni0,5Zn0,5Fe2O4, i0,2Zn0,5Mn0,3Fe2O4, Mn0,5Zn0,5Fe2O4, Ni0,5Mg0,5Fe2O4, Ni0,2Cu0,3Zn0,5Fe2O4 and Ni0,2Cu0,3Zn0,5Mg0,08Fe2O4, the precursors citrate method. The decomposition of the precursors was studied by thermogravimetric analysis and spectroscopy in the infrared region, the temperature of 350°C/3h. The evolution of the phases formed after calcinations at 350, 500, 900 and 1100ºC/3h was accompanied by X-ray diffraction using the Rietveld refinement to better identify the structures formed. The materials were also analyzed by scanning electron microscopy, magnetic measurements and analysis of the reflectivity of the material. The samples calcined at different temperatures showed an increase of crystallinity with increasing calcination temperature, verifying that for some compositions at temperatures above 500°C precipitates of second phase such as hematite and CuO. The compositions of manganese present in the structure diffusion processes slower due to the ionic radius of manganese is greater than for other ions substitutes, a fact that delays the stabilization of spinel structure and promotes the precipitation of second phase. The compositions presented with copper precipitation CuO phase at a temperature of 900 and 1100ºC/3h This occurs according to the literature because the concentration of copper in the structure is greater than 0.25 mol%. The magnetic measurements revealed features of a soft ferrimagnetic material, resulting in better magnetic properties for the NiZn ferrite and NiCuZnMg at high temperatures. The reflectivity measurements showed greater absorption of electromagnetic radiation in the microwave band for the samples calcined at 1100ºC/3h, which has higher crystallite size and consequently the formation of multi-domain, increasing the magnetization of the material. The results of absorption agreed with the magnetic measurements, indicating among the ferrites studied, those of NiZn and NiCuZnMg as better absorbing the incident radiation.

Giant magnetofossils and hyperthermal events

Magnetotactic bacteria biomineralize magnetic minerals with precisely controlled size, morphology, and stoichiometry. These cosmopolitan bacteria are widely observed in aquatic environments. If preserved after burial, the inorganic remains of magnetotactic bacteria act as magnetofossils that record ancient geomagnetic field variations. They also have potential to provide paleoenvironmental information. In contrast to conventional magnetofossils, giant magnetofossils (most likely produced by eukaryotic organisms) have only been reported once before from Paleocene-Eocene Thermal Maximum (PETM; 55.8 Ma) sediments on the New Jersey coastal plain. Here, using transmission electron microscopic observations, we present evidence for abundant giant magnetofossils, including previously reported elongated prisms and spindles, and new giant bullet-shaped magnetite crystals, in the Southern Ocean near Antarctica, not only during the PETM, but also shortly before and after the PETM. Moreover, we have discovered giant bullet-shaped magnetite crystals from the equatorial Indian Ocean during the Mid-Eocene Climatic Optimum (similar to 40 Ma). Our results indicate a more widespread geographic, environmental, and temporal distribution of giant magnetofossils in the geological record with a link to "hyperthermal" events. Enhanced global weathering during hyperthermals, and expanded suboxic diagenetic environments, probably provided more bioavailable iron that enabled biomineralization of giant magnetofossils. Our micromagnetic modelling indicates the presence of magnetic multi-domain (i.e., not ideal for navigation) and single domain (i.e., ideal for navigation) structures in the giant magnetite particles depending on their size, morphology and spatial arrangement. Different giant magnetite crystal morphologies appear to have had different biological functions, including magnetotaxis and other non-navigational purposes. Our observations suggest that hyperthermals provided ideal conditions for giant magnetofossils, and that these organisms were globally distributed. Much more work is needed to understand the interplay between magnetofossil morphology, climate, nutrient availability, and environmental variability.