Association of a Novel Hsp70 Species with Brain Aging and Proteasome Dysfunction
Most neurological diseases are characterized by the presence of protein aggregates,\r suggesting that aberrations in protein homeostasis are associated with neuronal demise. In eukaryotic cells, protein homeostasis is maintained by the chaperone, ubiquitin proteasome (UPS) and autophagy systems. As age is a risk factor for several types of neurodegenerative diseases, the function of these various protein homeostatic systems could become compromised with age. To understand the events that occur during normal aging, we examined the expression of key markers associated with the aforementioned systems in mice aged 1, 3, and >18 months. We found that proteasome activity and the amount of proteasome-related structures remained unaffected with age. Interestingly though, an agerelated increase of a novel Hsp70 chaperone protein species (herein designated Hsp70*) was observed. The expression of Hsp70* is also increased markedly in cells treated with pharmacological agents that promote proteasome inhibition, suggesting a functional interaction between the chaperone system and the UPS. Taken together, our results suggest that there is some form of crosstalk between the chaperone system and the UPS involving the observed HSP70 species.
ORGANIC AND NON ORGANIC CEREALS The experimental pattern that marks the difference
1. Purpose of the research The purpose of this research is to make a suitable experimental pattern to distinguish, by scientific method, organic cereals from non organic cereals. The reference ideas consider cereals (rice, barley and maize) as a complex system that possesses its own chemical–physical properties. These cereals are able to maintain traces of the cultivation process. In non organic cereal grains foreign molecules, from synthesis substances used during their cultivation and/or in their final processing, can be found. These kinds of molecules would be absent in organic cereals. The effect of these foreign molecules traces on the principal components (glucides, proteins, lipids) of cereals is investigated by Infrared Spectroscopy (IR). 2. Procedures The spectra of a small quantity of cereal meal are recorded by the ATR (Attenuated Total Reflectance) sampling method. The meal is obtained from selected grains of rice and barley, that are grated near the germ. On the contrary, the maize grains, are cut lengthwise and the two halves are grated on the interior surface. This procedure of preparing samples, withdraws that part of the non organic cereal grains where foreign molecules are more abundant. The meal mass amounts to only a few milligrams; so in this way the dilution effect caused by starchy and proteinic parts onto the lipid part, is reduced. The cereal packaging has to be intact, well preserved and the expiry date has to be far–off. The organic packaging has the European Certification symbol and that of the authorizing agency. The cereals used in this research, have been labelled with symbols. The experimental data are processed by the NMC (Nearest Means Classification: J.Chem. Educ. 2003, 80, 542) method, adapted to cereals. 3. Data The NMC method is based on the individuation of suitable absorption bands of the IR spectrum and, for each of them, the calculation of the following quantities: the average value of the wave number (); the (Σ) value; the |diff.|=|(ῡ–)| value and the Σ|diff.| value. At the end the sum of the Σ|diff.| for all selected bands is computed in order to obtain the Σ(Σ|diff.|). Then a graph is plotted using (Σ) and Σ(Σ|diff.|) variables. The graph has a gap between the organic cereals and the non organic ones; in other words the organic cereals are found in a particular area, whilst the non organic cereals are found in another area. The boundary between the two areas is a particular value of the Σ(Σ|diff.|). This is the pattern that distinguishes organic cereals from non organic ones. 4. Conclusions For some cereals, the gap is bigger than others; but in any case the position of the cereals on one side of the boundary line or on the other, is clear. An experimental scientific pattern that marks the difference between organic cereals and non organic ones, can be useful to organic farms, authorizing agencies and consumers. This research has planned a route to find such a pattern.
Hourglass 2011
Over the past year Conor has been developing an electronic time keeping device named Hourglass. Hourglass has a three-fold focus on functionality, intuitive design and simplicity. To simplify the device he has limited the hardware to a bare minimum. Just three buttons and an LCD screen comprise the user-interface. Although this interface is simple, the user can access many features. These include intuitive scrolling menus, countdown, lap and alarm functions, accessed through button combinations as well as multiple ways to use single buttons, such as holding or short pressing. Many functions have been integrated into the device, such as a stopwatch with lap times, a countdown, up to 99 Custom Alarms with an individual active/inactive state and a lock/unlock feature. The stopwatch is accurate to 1 second and can be started, stopped, reset and used to record lap times. When laps have been recorded, the user can then take the time value of a lap and turn it into a countdown. A countdown of up to 99 hours can be set, and will run until deactivated or until it reaches zero. Upon reaching zero the alarm is activated. The home screen displays the time, any active countdown and notifies the user if an alarm is active. It can be locked or unlocked by holding the blue button a set period of time, helping to reduce any inadvertent change in setting. All of the functions available can be operated easily with the intuitive 3 button interface method. The menu system is simple, but has been set up through clever coding. An arrow indicated which option is selected, by pressing the top button on the clock the option above the current selection is selected/the menu scrolls up. Pressing the bottom button selects the next option in the downward direction/scrolls down. The button in the centre positioned off to the left is used to activate an option. When a Yes or No prompt appears on the screen, the action corresponds with the button position. Therefore the triangle layout of the buttons is simple and intuitive. Thus Conor’s device relies on complicated, yet elegantly formulated and annotated code and simple hardware interfaces to interact with the user in a way which is intuitive and provides great functionality. It does this while being simple and easy to understand. Here these principles are applied to a clock project, but there are implications for good design that go way beyond this context.
New Screening Method for Early Pediatric Cancer Detection Through Automated Handwriting Analysis
Pediatric cancer has an incidence rate of more than 175,000 per year with a mortality rate of approximately 96,000 per year. One major cause of this problem is late diagnosis. A novel promising way of pediatric cancer screening is handwriting analysis. This method surpasses other methods by detecting pediatric cancer in a very early stage. However, studies are still limited to manual analysis which needs an expert and a long period of time. The aim of this project is to design a computer program to extract handwriting features and build a classification model to classify the user as patient or as control. Dataset was collected from schools and hospitals where all participants could read and write in English. After data cleansing, number of samples was 440 samples. MATLAB (Matrix Laboratory) program was used for extracting geometric features in handwriting. Program was validated using a subset of 50 samples of the dataset. WEKA Package was used to test and build the classifier. Experiments were done using classifiers: Logistic, Multilayer Perceptron, J48, LibSVM, AdaBoostM1 and Naïve Bayes. Best subset of attributes was evaluated and used for each classifier and all calculations were done as the average of cross validation operations of several folds assignments. Best performance was achieved by Logistic classifier with average accuracy of 80.15%, standard deviation of 0.43% and Matthews's correlation coefficient of 0.59. Finally, this project presents a new fast, free, ready, easy and psychologically comfortable method for pediatric cancer detection while keeping suitable accuracy for mass screening.