Monitoring the Early Signs of Cognitive Decline in Elderly by Computer Games: An MRI Study

BackgroundIt is anticipated that current and future preventive therapies will likely be more effective in the early stages of dementia, when everyday functioning is not affected. Accordingly the early identification of people at risk is particularly important. In most cases, when subjects visit an expert and are examined using neuropsychological tests, the disease has already been developed. Contrary to this cognitive games are played by healthy, well functioning elderly people, subjects who should be monitored for early signs. Further advantages of cognitive games are their accessibility and their cost-effectiveness.PurposeThe aim of the investigation was to show that computer games can help to identify those who are at risk. In order to validate games analysis was completed which measured the correlations between results of the ''Find the Pairs'' memory game and the volumes of the temporal brain regions previously found to be good predictors of later cognitive decline.ResultsThere was a correlation between the number of attempts and the time required to complete the memory game and the volume of the entorhinal cortex, the temporal pole, and the hippocampus. There was also a correlation between the results of the Paired Associates Learning (PAL) test and the memory game.ConclusionsThe results gathered support the initial hypothesis that healthy elderly subjects achieving lower scores in the memory game have increased level of atrophy in the temporal brain structures and showed a decreased performance in the PAL test. Based on these results it can be concluded that memory games may be useful in early screening for cognitive decline.     

Computational Modeling of Seizure Dynamics Using Coupled Neuronal Networks: Factors Shaping Epileptiform Activity

Epileptic seizure dynamics span multiple scales in space and time. Understanding seizure mechanisms requires identifying the relations between seizure components within and across these scales, together with the analysis of their dynamical repertoire. Mathematical models have been developed to reproduce seizure dynamics across scales ranging from the single neuron to the neural population. In this study, we develop a network model of spiking neurons and systematically investigate the conditions, under which the network displays the emergent dynamic behaviors known from the Epileptor, which is a well-investigated abstract model of epileptic neural activity. This approach allows us to study the biophysical parameters and variables leading to epileptiform discharges at cellular and network levels. Our network model is composed of two neuronal populations, characterized by fast excitatory bursting neurons and regular spiking inhibitory neurons, embedded in a common extracellular environment represented by a slow variable. By systematically analyzing the parameter landscape offered by the simulation framework, we reproduce typical sequences of neural activity observed during status epilepticus. We find that exogenous fluctuations from extracellular environment and electro-tonic couplings play a major role in the progression of the seizure, which supports previous studies and further validates our model. We also investigate the influence of chemical synaptic coupling in the generation of spontaneous seizure-like events. Our results argue towards a temporal shift of typical spike waves with fast discharges as synaptic strengths are varied. We demonstrate that spike waves, including interictal spikes, are generated primarily by inhibitory neurons, whereas fast discharges during the wave part are due to excitatory neurons. Simulated traces are compared with in vivo experimental data from rodents at different stages of the disorder. We draw the conclusion that slow variations of global excitability, due to exogenous fluctuations from extracellular environment, and gap junction communication push the system into paroxysmal regimes. We discuss potential mechanisms underlying such machinery and the relevance of our approach, supporting previous detailed modeling studies and reflecting on the limitations of our methodology.     

Predictors of Symptomatic Change and Adherence in Internet-Based Cognitive Behaviour Therapy for Social Anxiety Disorder in Routine Psychiatric Care

Objective

A central goal of health care is to improve patient outcomes. Although several studies have demonstrated the effectiveness of therapist guided internet-based cognitive behaviour therapy (ICBT) for social anxiety disorder (SAD), a significant proportion of patients do not respond to treatment. Consequently, the aim of this study was to identify individual characteristics and treatment program related factors that could help clinicians predict treatment outcomes and adherence for individuals with SAD.

Method

The sample comprised longitudinal data collected during a 4-year period of adult individuals (N = 764) treated for SAD at a public service psychiatric clinic. Weekly self-rated Liebowitz Social Anxiety Scale (LSAS-SR) scores were provided. Rates of symptomatic change during treatment and adherence levels were analysed using multilevel modelling. The following domains of prognostic variables were examined: (a) socio-demographic variables; (b) clinical characteristics; (c) family history of mental illness; and (d) treatment-related factors.

Results

Higher treatment credibility and adherence predicted a faster rate of improvement during treatment, whereas higher overall functioning level evidenced a slower rate of improvement. Treatment credibility was the strongest predictor of greater adherence. Having a family history of SAD-like symptoms was also associated with greater adherence, whereas Attention-Deficit/Hyperactivity Disorder (ADHD)-like symptoms, male gender, and family history of minor depression predicted lower adherence. Also, the amount of therapist time spent per treatment module was negatively associated with adherence.

Conclusions

Results from a large clinical sample indicate that the credibility of ICBT is the strongest prognostic factor explaining individual differences in both adherence level and symptomatic improvement. Early screening of ADHD-like symptoms may help clinicians identify patients who might need extra support or an adjusted treatment. Therapist behaviours that promote adherence may be important for treatment response, although more research is needed in order to determine what type of support would be most beneficial.     

Communicable Diseases Prioritized According to Their Public Health Relevance,Sweden, 2013

To establish strategic priorities for the Public Health Agency of Sweden we prioritized pathogens according to their public health relevance in Sweden in order to guide resource allocation. We then compared the outcome to ongoing surveillance. We used a modified prioritization method developed at the Robert Koch Institute in Germany. In a Delphi process experts scored pathogens according to ten variables. We ranked the pathogens according to the total score and divided them into four priority groups. We then compared the priority groups to self-reported time spent on surveillance by epidemiologists and ongoing programmes for surveillance through mandatory and/or voluntary notifications and for surveillance of typing results. 106 pathogens were scored. The result of the prioritization process was similar to the outcome of the prioritization in Germany. Common pathogens such as calicivirus and Influenza virus as well as blood-borne pathogens such as human immunodeficiency virus, hepatitis B and C virus, gastro-intestinal infections such as Campylobacter and Salmonella and vector-borne pathogens such as Borrelia were all in the highest priority group. 63% of time spent by epidemiologists on surveillance was spent on pathogens in the highest priority group and all pathogens in the highest priority group, except for Borrelia and varicella-zoster virus, were under surveillance through notifications. Ten pathogens in the highest priority group (Borrelia, calicivirus, Campylobacter, Echinococcus multilocularis, hepatitis C virus, HIV, respiratory syncytial virus, SARS- and MERS coronavirus, tick-borne encephalitis virus and varicella-zoster virus) did not have any surveillance of typing results. We will evaluate the possibilities of surveillance for the pathogens in the highest priority group where we currently do not have any ongoing surveillance and evaluate the need of surveillance for the pathogens from the low priority group where there is ongoing surveillance in order to focus our work on the pathogens with the highest relevance.     

Natural and synthetic inhibitors of kallikrein-related peptidases (KLKs)

Including the true tissue kallikrein KLK1, kallikrein-related peptidases (KLKs) represent a family of fifteen mammalian serine proteases. While the physiological roles of several KLKs have been at least partially elucidated, their activation and regulation remain largely unclear. This obscurity may be related to the fact that a given KLK fulfills many different tasks in diverse fetal and adult tissues, and consequently, the timescale of some of their physiological actions varies significantly. To date, a variety of endogenous inhibitors that target distinct KLKs have been identified. Among them are the attenuating Zn²⁺ ions, active site-directed proteinaceous inhibitors, such as serpins and the Kazal-type inhibitors, or the huge, unspecific compartment forming α₂-macroglobulin. Failure of these inhibitory systems can lead to certain pathophysiological conditions. One of the most prominent examples is the Netherton syndrome, which is caused by dysfunctional domains of the Kazal-type inhibitor LEKTI-1 which fail to appropriately regulate KLKs in the skin. Small synthetic inhibitory compounds and natural polypeptidic exogenous inhibitors have been widely employed to characterize the activity and substrate specificity of KLKs and to further investigate their structures and biophysical properties. Overall, this knowledge leads not only to a better understanding of the physiological tasks of KLKs, but is also a strong fundament for the synthesis of small compound drugs and engineered biomolecules for pharmaceutical approaches. In several types of cancer, KLKs have been found to be overexpressed, which makes them clinically relevant biomarkers for prognosis and monitoring. Thus, down regulation of excessive KLK activity in cancer and in skin diseases by small inhibitor compounds may represent attractive therapeutical approaches.     

Synthesis and in vitro antitumor effect of vinblastine derivative-oligoarginine conjugates

Vinblastine is a widely used anticancer drug with undesired side effects. Its conjugation with carrier molecules could be an efficient strategy to reduce these side effects. Besides this, the conjugate could exhibit increased efficiency against resistant cells, e.g., due to the altered internalization pathway. Oligoarginines, as cell-penetrating peptides, can transport covalently attached compounds into different kinds of cells and enhance the efficiency of those compounds. We report here the coupling of vinblastine through its carboxyl group at position 16 with the N-terminal amino function of L-Trp methyl ester. After hydrolysis of the ester group, 17-desacetylvinblastineTrp was conjugated to the N-terminal amino group of oligoarginine via the C-terminal carboxyl group of the Trp moiety in solution. The antitumor effect of conjugates was studied on sensitive and resistant human leukemia (HL-60) cells in vitro. Our data suggest that all conjugates investigated possess an antiproliferative effect against the studied cells. However, the effect was dependent on the number of Arg residues in the conjugates: Arg? > Arg? ? Arg?. The conjugate with Arg? exhibited similar efficicacy as compared with free 17-desacetylvinblastineTrp. The in vitro studies also showed that the tubulin binding ability of vinblastine was essentially preserved even in the octaarginine conjugate. We also observed that two isomers were formed during conjugation. These isomers showed different levels of activity against tubulin polymerization in vitro and in vivo. The 17-desacetylvinblastineTrp-Arg?-1 isomer conjugate possessed high selectivity against the mitotic spindles. HRMS and NMR data suggest that 17-desacetylvinblastineTrp-Arg?-1 and 17-desacetylvinblastineTrp-Arg?-2 are epimers at the tryptophan α carbon atom.     

Impaired autophagy in Lafora disease

Lafora disease (LD) is a progressive, lethal, autosomal recessive, neurodegenerative disorder that manifests with myoclonus epilepsy. LD is characterized by the presence of intracellular inclusion bodies called Lafora bodies (LB), in brain, spinal cord and other tissues. More than 50 percent of LD is caused by mutations in EPM2A that encodes laforin. Here we review our recent findings that revealed that laforin regulates autophagy. We consider how autophagy compromise may predispose to LB formation and neurodegeneration in LD, and discuss future investigations suggested by our data.Key words: autophagy, glycogen metabolism, Lafora disease, laforin, malin, neurodegeneration     

Identifying functional relationships within sets of co-expressed genes by combining upstream regulatory motif analysis and gene expression information

Background

Existing clustering approaches for microarray data do not adequately differentiate between subsets of co-expressed genes. We devised a novel approach that integrates expression and sequence data in order to generate functionally coherent and biologically meaningful subclusters of genes. Specifically, the approach clusters co-expressed genes on the basis of similar content and distributions of predicted statistically significant sequence motifs in their upstream regions.

Results

We applied our method to several sets of co-expressed genes and were able to define subsets with enrichment in particular biological processes and specific upstream regulatory motifs.

Conclusions

These results show the potential of our technique for functional prediction and regulatory motif identification from microarray data.

     

Phylogenetic approach reveals that virus genotype largely determines HIV set-point viral load

HIV virulence, i.e. the time of progression to AIDS, varies greatly among patients. As for other rapidly evolving pathogens of humans, it is difficult to know if this variance is controlled by the genotype of the host or that of the virus because the transmission chain is usually unknown. We apply the phylogenetic comparative approach (PCA) to estimate the heritability of a trait from one infection to the next, which indicates the control of the virus genotype over this trait. The idea is to use viral RNA sequences obtained from patients infected by HIV-1 subtype B to build a phylogeny, which approximately reflects the transmission chain. Heritability is measured statistically as the propensity for patients close in the phylogeny to exhibit similar infection trait values. The approach reveals that up to half of the variance in set-point viral load, a trait associated with virulence, can be heritable. Our estimate is significant and robust to noise in the phylogeny. We also check for the consistency of our approach by showing that a trait related to drug resistance is almost entirely heritable. Finally, we show the importance of taking into account the transmission chain when estimating correlations between infection traits. The fact that HIV virulence is, at least partially, heritable from one infection to the next has clinical and epidemiological implications. The difference between earlier studies and ours comes from the quality of our dataset and from the power of the PCA, which can be applied to large datasets and accounts for within-host evolution. The PCA opens new perspectives for approaches linking clinical data and evolutionary biology because it can be extended to study other traits or other infectious diseases.     

Protective effects of polyphenolics in red wine on diabetes associated oxidative/nitrative stress in streptozotocin‐diabetic rats

Increased accumulation of NT (3‐nitrotyrosine) and PARylated [poly(ADP‐ribosyl)ated] proteins in the tissues of diabetics are associated with diabetes complications (diabetes neuropathy, nephropathy and retinopathy). Red wine (its polyphenols are considered to be the main active components) can act as ROS (reactive oxygen species) scavengers, iron chelators and enzyme modulators. This study is novel in investigating the effect of red wine in preventing the accumulation of NT and PARylated proteins in the sciatic nerve, DRG (dorsal root ganglia), spinal cord, kidney and retina of diabetic animals. We have shown that during the experiment the body weight of control and diabetic groups of rats with consumption of red wine was significantly increased, by 52% and 19% accordingly. The significant increase in the content of NT in the sciatic nerve, DRG, spinal cord, kidney and retina, and PARylated proteins in the sciatic nerve, renal glomeruli and retinae of diabetic rats was partly or completely prevented by treatment with red wine. Red wine and its polyphenol preparations might be a promising option in the prevention and treatment of diabetic complications.