Galilee: an Internet Web Based Distance Learning Support System

This paper presents a project of Web-based Distance Learning support system. The system has been built based on the Internet and World Wide Web facility. The system could be accessed with a web browser which is directed to a certain web server address so that students can do learning process just like in the real situation, such as student admissions, taking course materials, syllabus, assignments, students grades, class discussions through web, and doing online quizzes. Students could also join collaboration works by giving opinions, feedback and student produced paper/web which can be shared to the entire learning community. Therefore, it will build a collaborative learning environment where lectures together with students make constructive knowledge databases for entire learning community. This system has been developed based on Active Server Pages (ASP) technology from Microsoft which is embedded in a web server. Web pages reside in a web server which is connected to an SQL Database Server. Database server is used to store structured data such as lectures/students personal information, course lists, syllabus and its descriptions, announcement texts from lecturers, commentaries for discussion forum, student's study evaluations, scores for each assignment, quizzes for each course, assignments text from lectures, assignments which are collected by students and students contribution/materials. This system has been maintained by an administrator for maintaining and developing web pages using HTML. The administrator also does ASP scripts programming to convert web pages into active server pages. Lectures and students could contribute some course materials and share their ideas through their web browser. This web-based collaborative learning system gives the students more active role in the information gathering and learning process, making the distance students feel part of a learning community, therefore increasing motivation, comprehension and interaction with other students

Evolutionary minority game with heterogeneous strategy distribution

We present detailed numerical results for a modified form of the so-called Minority Game, which provides a simplified model of a competitive market. Each agent has a limited set of strategies, and competes to be in a minority. An evolutionary rule for strategy modification is included to mimic simple learning. The results can be understood by considering crowd formation within the population.Comment: Revtex file + 4 figure

Neuroevolution is a Competitive Alternative to Reinforcement Learning for Skill Discovery

Deep Reinforcement Learning (RL) has emerged as a powerful paradigm for training neural policies to solve complex control tasks. However, these policies tend to be overfit to the exact specifications of the task and environment they were trained on, and thus do not perform well when conditions deviate slightly or when composed hierarchically to solve even more complex tasks. Recent work has shown that training a mixture of policies, as opposed to a single one, that are driven to explore different regions of the state-action space can address this shortcoming by generating a diverse set of behaviors, referred to as skills, that can be collectively used to great effect in adaptation tasks or for hierarchical planning. This is typically realized by including a diversity term - often derived from information theory - in the objective function optimized by RL. However these approaches often require careful hyperparameter tuning to be effective. In this work, we demonstrate that less widely-used neuroevolution methods, specifically Quality Diversity (QD), are a competitive alternative to information-theory-augmented RL for skill discovery. Through an extensive empirical evaluation comparing eight state-of-the-art methods on the basis of (i) metrics directly evaluating the skills' diversity, (ii) the skills' performance on adaptation tasks, and (iii) the skills' performance when used as primitives for hierarchical planning; QD methods are found to provide equal, and sometimes improved, performance whilst being less sensitive to hyperparameters and more scalable. As no single method is found to provide near-optimal performance across all environments, there is a rich scope for further research which we support by proposing future directions and providing optimized open-source implementations

Mitochondria-derived reactive oxygen species drive GANT61-induced mesothelioma cell apoptosis

Gli transcription factors of the Hedgehog (Hh) pathway have been reported to be drivers of malignant mesothelioma (MMe) cell survival. The Gli inhibitor GANT61 induces apoptosis in various cancer cell models, and has been associated directly with Gli inhibition. However various chemotherapeutics can induce cell death through generation of reactive oxygen species (ROS) but whether ROS mediates GANT61-induced apoptosis is unknown. In this study human MMe cells were treated with GANT61 and the mechanisms regulating cell death investigated. Exposure of MMe cells to GANT61 led to G1 phase arrest and apoptosis, which involved ROS but not its purported targets, GLI1 or GLI2. GANT61 triggered ROS generation and quenching of ROS protected MMe cells from GANT61-induced apoptosis. Furthermore, we demonstrated that mitochondria are important in mediating GANT61 effects: (1) ROS production and apoptosis were blocked by mitochondrial inhibitor rotenone; (2) GANT61 promoted superoxide formation in mitochondria; and (3) mitochondrial DNA-deficient LO68 cells failed to induce superoxide, and were more resistant to apoptosis induced by GANT61 than wild-type cells. Our data demonstrate for the first time that GANT61 induces apoptosis by promoting mitochondrial superoxide generation independent of Gli inhibition, and highlights the therapeutic potential of mitochondrial ROS-mediated anticancer drugs in MMe

Tailored risk assessment and forecasting in intermittent claudication

BackgroundGuidelines recommend cardiovascular risk reduction and supervised exercise therapy as the first line of treatment in intermittent claudication, but implementation challenges and poor patient compliance lead to significant variation in management and therefore outcomes. The development of a precise risk stratification tool is proposed through a machine-learning algorithm that aims to provide personalized outcome predictions for different management strategies.MethodsFeature selection was performed using the least absolute shrinkage and selection operator method. The model was developed using a bootstrapped sample based on patients with intermittent claudication from a vascular centre to predict chronic limb-threatening ischaemia, two or more revascularization procedures, major adverse cardiovascular events, and major adverse limb events. Algorithm performance was evaluated using the area under the receiver operating characteristic curve. Calibration curves were generated to assess the consistency between predicted and actual outcomes. Decision curve analysis was employed to evaluate the clinical utility. Validation was performed using a similar dataset.ResultsThe bootstrapped sample of 10 000 patients was based on 255 patients. The model was validated using a similar sample of 254 patients. The area under the receiver operating characteristic curves for risk of progression to chronic limb-threatening ischaemia at 2 years (0.892), risk of progression to chronic limb-threatening ischaemia at 5 years (0.866), likelihood of major adverse cardiovascular events within 5 years (0.836), likelihood of major adverse limb events within 5 years (0.891), and likelihood of two or more revascularization procedures within 5 years (0.896) demonstrated excellent discrimination. Calibration curves demonstrated good consistency between predicted and actual outcomes and decision curve analysis confirmed clinical utility. Logistic regression yielded slightly lower area under the receiver operating characteristic curves for these outcomes compared with the least absolute shrinkage and selection operator algorithm (0.728, 0.717, 0.746, 0.756, and 0.733 respectively). External calibration curve and decision curve analysis confirmed the reliability and clinical utility of the model, surpassing traditional logistic regression.ConclusionThe machine-learning algorithm successfully predicts outcomes for patients with intermittent claudication across various initial treatment strategies, offering potential for improved risk stratification and patient outcomes

Pipecolic Acid Confers Systemic Immunity by Regulating Free Radicals

Pipecolic acid (Pip), a non-proteinaceous product of lysine catabolism, is an important regulator of immunity in plants and humans alike. In plants, Pip accumulates upon pathogen infection and has been associated with systemic acquired resistance (SAR). However, the molecular mechanisms underlying Pip-mediated signaling and its relationship to other known SAR inducers remain unknown. We show that in plants, Pip confers SAR by increasing levels of the free radicals, nitric oxide (NO), and reactive oxygen species (ROS), which act upstream of glycerol-3-phosphate (G3P). Plants defective in NO, ROS, G3P, or salicylic acid (SA) biosynthesis accumulate reduced Pip in their distal uninfected tissues although they contain wild-type-like levels of Pip in their infected leaves. These data indicate that de novo synthesis of Pip in distal tissues is dependent on both SA and G3P and that distal levels of SA and G3P play an important role in SAR. These results also suggest a unique scenario whereby metabolites in a signaling cascade can stimulate each other\u27s biosynthesis depending on their relative levels and their site of action

Novel fused arylpyrimidinone based allosteric modulators of the M1 muscarinic acetylcholine receptor

Benzoquinazolinone 1 is a positive allosteric modulator (PAM) of the M1 muscarinic acetylcholine receptor (mAChR), which is significantly more potent than the prototypical PAM, 1-(4-methoxybenzyl)-4-oxo-1,4-dihydroquinoline- 3-carboxylic acid (BQCA). In this study, we explored the structural determinants that underlie the activity of 1 as a PAM of the M1 mAChR. We paid particular attention to the importance of the tricyclic scaffold of compound 1, for the activity of the molecule. Complete deletion of the peripheral fused benzene ring caused a significant decrease in affinity and binding cooperativity with acetylcholine (ACh). This loss of affinity was rescued with the addition of either one or two methyl groups in the 7- and/or 8-position of the quinazolin-4(3H)-one core. These results demonstrate that the tricyclic benzo[h]quinazolin-4(3H)-one core could be replaced with a quinazolin-4(3H)-one core and maintain functional affinity. As such, the quinazolin-4(3H)-one core represents a novel scaffold to further explore M1 mAChR PAMs with improved physicochemical properties

4-Phenylpyridin-2-one derivatives: a novel class of positive allosteric modulator of the M1 muscarinic acetylcholine receptor

Positive allosteric modulators (PAMs) of the M1 muscarinic acetylcholine receptor (M1 mAChR) are a promising strategy for the treatment of the cognitive deficits associated with diseases including Alzheimer’s and schizophrenia. Herein, we report the design, synthesis, and characterization of a novel family of M1 mAChR PAMs. The most active compounds of the 4-phenylpyridin-2-one series exhibited comparable binding affinity to the reference compound, 1-(4-methoxybenzyl)-4-oxo-1,4-dihydroquinoline-3-carboxylic acid (BQCA) (1), but markedly improved positive cooperativity with acetylcholine, and retained exquisite selectivity for the M1 mAChR. Furthermore, our pharmacological characterization revealed ligands with a diverse range of activities, including modulators that displayed both high intrinsic efficacy and PAM activity, those that showed no detectable agonism but robust PAM activity and ligands that displayed robust allosteric agonism but little modulatory activity. Thus, the 4-phenylpyridin-2-one scaffold offers an attractive starting point for further lead optimization

Stimulation of the D5 Dopamine Receptor Acidifies the Lysosomal pH of Retinal Pigmented Epithelial Cells and Decreases Accumulation of Autofluorescent Photoreceptor Debris

Optimal neuronal activity requires that supporting cells provide both efficient nutrient delivery and waste disposal. The incomplete processing of engulfed waste by their lysosomes can lead to accumulation of residual material and compromise their support of neurons. As most degradative lysosomal enzymes function best at an acidic pH, lysosomal alkalinization can impede enzyme activity and increase lipofuscin accumulation. We hypothesize that treatment to reacidify compromised lysosomes can enhance degradation. Here, we demonstrate that degradation of ingested photoreceptor outer segments by retinal pigmented epithelial (RPE) cells is increased by stimulation of D5 dopamine receptors. D1/D5 receptor agonists reacidified lysosomes in cells alkalinized by chloroquine or tamoxifen, with acidification dependent on protein kinase A. Knockdown with siRNA confirmed acidification was mediated by the D5 receptor. Exposure of cells to outer segments increased lipofuscin-like autofluorescence, but SKF 81297 reduced autofluorescence. Likewise, SKF 81297 increased the activity of lysosomal protease cathepsin D in situ. D5DR stimulation also acidified lysosomes of RPE cells from elderly ABCA4−/− mice, a model of recessive Stargardt’s retinal degeneration. In conclusion, D5 receptor stimulation lowers compromised lysosomal pH, enhancing degradation. The reduced accumulation of lipofuscin-like autofluorescence implies the D5 receptor stimulation may enable cells to better support adjacent neurons

Stimulation of the D5 Dopamine Receptor Acidifies the Lysosomal pH of Retinal Pigmented Epithelial Cells and Decreases Accumulation of Autofluorescent Photoreceptor Debris

Optimal neuronal activity requires that supporting cells provide both efficient nutrient delivery and waste disposal. The incomplete processing of engulfed waste by their lysosomes can lead to accumulation of residual material and compromise their support of neurons. As most degradative lysosomal enzymes function best at an acidic pH, lysosomal alkalinization can impede enzyme activity and increase lipofuscin accumulation. We hypothesize that treatment to reacidify compromised lysosomes can enhance degradation. Here, we demonstrate that degradation of ingested photoreceptor outer segments by retinal pigmented epithelial cells is increased by stimulation of D5 dopamine receptors. D1/D5 receptor agonists reacidified lysosomes in cells alkalinized by chloroquine or tamoxifen, with acidification dependent on protein kinase A. Knockdown with siRNA confirmed acidification was mediated by the D5 receptor. Exposure of cells to outer segments increased lipofuscin-like autofluorescence, but SKF 81297 reduced autofluorescence. Likewise, SKF 81297 increased the activity of lysosomal protease cathepsin D in situ. D5DR stimulation also acidified lysosomes of retinal pigmented epithelial cells from elderly ABCA4-/- mice, a model of recessive Stargardt\u27s retinal degeneration. In conclusion, D5 receptor stimulation lowers compromised lysosomal pH, enhancing degradation. The reduced accumulation of lipofuscin-like autofluorescence implies the D5 receptor stimulation may enable cells to better support adjacent neurons. © 2012 The Authors. Journal of Neurochemistry © 2012 International Society for Neurochemistry