Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases

Neurodegenerative diseases (NDs) including Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, and Huntington’s disease are incurable and affect millions of people worldwide. The development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.     

Molecular Mechanisms of Fetal Tendon Regeneration Versus Adult Fibrous Repair

Tendinopathies are painful, disabling conditions that afflict 25% of the adult human population. Filling an unmet need for realistic large-animal models, we here present an ovine model of tendon injury for the comparative study of adult scarring repair and fetal regeneration. Complete regeneration of the fetal tendon within 28 days is demonstrated, while adult tendon defects remained macroscopically and histologically evident five months post-injury. In addition to a comprehensive histological assessment, proteome analyses of secretomes were performed. Confirming histological data, a specific and pronounced inflammation accompanied by activation of neutrophils in adult tendon defects was observed, corroborated by the significant up-regulation of pro-inflammatory factors, neutrophil attracting chemokines, the release of potentially tissue-damaging antimicrobial and extracellular matrix-degrading enzymes, and a response to oxidative stress. In contrast, secreted proteins of injured fetal tendons included proteins initiating the resolution of inflammation or promoting functional extracellular matrix production. These results demonstrate the power and relevance of our novel ovine fetal tendon regeneration model, which thus promises to accelerate research in the field. First insights from the model already support our molecular understanding of successful fetal tendon healing processes and may guide improved therapeutic strategies.     

Functionalized oligopolysiloxanes by heterogeneously catalyzed equilibration polymerization reactions

Summary A new general procedure for preparation of functionalized oligopolysiloxanes of predetermined molecular weight is described. It utilizes heterogeneously catalyzed siloxane equilibration polymerization reactions which do not require troublesome and sometimes difficult post-preparative work-up procedures usually encountered with the well known homogeneously catalyzed corresponding reactions. The method is described using as example the preparation of , -telechelic vinyldimethylsiloxy-oligopolydimethylsiloxanes from octamethylcyclotetrasiloxane and 1,3-divinyltetramethyldisiloxane, but reference to the preparations of trimethylsiloxy-, dimethylsiloxy-and carboxypropyldimethylsiloxyoligopolydimethylsiloxanes, oligopolymethylhydridosiloxanes or their copolymers is also made.     

An e-Learning tool considering similarity measures for manufacturing cell formation

Manufacturing cell formation is the first step in the design of cellular manufacturing system. The primary objective of this step is to cluster machines into machine cells and parts into part families so that the minimum of intercell trips will be achieved. This paper will be focused on the configuration of machine cells considering three types of initial machine-part matrix: binary (zero-one) matrix, production volume matrix, and operation time matrix. The similarity measure uses only information from these types of matrix. A pure combinatorial programming formulation will be developed to maximize the sum of similarity coefficients between machine/part pairs. An e-Learning tool/application to help industrial students and engineers for enhancing their cell formation capability is proposed. This tool is designed to include a novel similarity coefficient-based heuristic algorithm for solving the cell formation problem. To determine the performance of the proposed tool, comparison is made with a well-known tool along a case study.     

Selective Complexation and Membrane Transport of Guanidinium Salts by Calix[6]arene Amides

The p-tert-butylcalix[6]arene hexamide 2 and syn-1,3,5–trimethoxy-2,4,6-triamide 4 were synthesized by reaction of α-chloro-N,N-diethylacetamide and the corresponding calix[6]arenes 1 and 3 , respectively. ¹H NMR spectroscopy shows that 2 is a mixture of different conformations whereas 4 is fixed in a cone conformation. Extraction experiments, (S-L) and (H₂O–CDCl₃) with picrate salts, indicate that 2 complexes both alkali metal (1:2 complex) and guanidinium salts (1:1 complex) but 4 complexes only guanidinium (1:1 complex). Incorporated in supported liquid membranes (Accurel^® / o-nitrophenyl n-octyl ether) the calixarenes 2 and 4 transport guanidinium salts. The hexamide 2 is a more efficient carrier of guanidinium but the syn-1,3,5-trimethoxy-2,4,6-triamide 4 is much more selective. Both 2 and 4 are sufficiently lipophilic to give membranes that are stable over longer periods (weeks).     

A low-cost real time virtual system for postural stability assessment at home

Background and objective

The degeneration of the balance control system in the elderly and in many pathologies requires measuring the equilibrium conditions very often. In clinical practice, equilibrium control is commonly evaluated by using a force platform (stabilometric platform) in a clinical environment.In this paper, we demonstrate how a simple movement analysis system, based on a 3D video camera and a 3D real time model reconstruction of the human body, can be used to collect information usually recorded by a physical stabilometric platform.

Methods

The algorithm used to reconstruct the human body model as a set of spheres is described and discussed. Moreover, experimental measurements and comparisons with data collected by a physical stabilometric platform are also reported. The measurements were collected on a set of 6 healthy subjects to whom a change in equilibrium condition was stimulated by performing an equilibrium task.

Results

The experimental results showed that more than 95% of data collected by the proposed method were not significantly different from those collected by the classic platform, thus confirming the usefulness of the proposed system.

Conclusions

The proposed virtual balance assessment system can be implemented at low cost (about 500$) and, for this reason, can be considered a home use medical device. On the contrary, astabilometric platform has a cost of about 10,000$ and requires periodical calibration. The proposed system does not require periodical calibration, as is necessary for stabilometric force platforms, and it is easy to use. In future, the proposed system with little integration can be used, besides being an emulator of a stabilometric platform, also to recognize and track, in real time, head, legs, arms and trunk, that is to collect information actually obtained by sophisticated optoelectronic systems.     

Support vector regression methodology for prediction of input displacement of adaptive compliant robotic gripper

The prerequisite for new versatile grippers is the capability to locate and perceive protests in their surroundings. It is realized that automated controllers are profoundly nonlinear frameworks, and a faultless numerical model is hard to get, in this way making it troublesome to control utilizing tried and true procedure. Here, a design of an adaptive compliant gripper is presented. This design of the gripper has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize specific shapes of the grasping objects. Since the conventional control strategy is a very challenging task, soft computing based controllers are considered as potential candidates for such an application. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) to estimate and predict optimal inputs displacement of the gripper according to experimental tests and shapes of grasping objects. Instead of minimizing the observed training error, SVR _poly and SVR _rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR approach compared to other soft computing methodology.     

Electrochemical study of the chromium electrode behaviour in borate buffer solution

The electrochemical behaviour of the chromium electrode in borate buffer solution (pH 9.3) was studied by cyclic voltammetry and electrochemical impedance spectroscopy. Chromium passivity was observed over a broad potential region, from –1.0 to 0.5 V vs SCE. The passivation process took place in two steps: formation of a chromium oxide monolayer and transition of chromium to a higher valence state. The anodic film exhibited the properties of a p-type semiconductor. Transpassive dissolution of chromium occurred at 0.5 V vs SCE, with two reaction intermediates present, Cr_Cr ^III and Cr_ad ⁴⁺.     

Abnormal behavior detection using dominant sets

Smart surveillance systems are increasingly being used to detect potentially dangerous situations. To do so, the common and easier way is to model normal human behaviors and consider as abnormal any new strange behavior in the scene. In this article, Dominant Sets is adapted to model most frequent behaviors and to detect any unknown event to trigger an alarm. It is proved that after an unsupervised training, Dominant Sets can robustly detect abnormal behaviors. The method is tested in several different cases and compared to other usual clusterization methods such as KNN, mixture of Gaussians or Fuzzy \(K\) -Means to confirm its robustness and performance. The overall performance of abnormal behavior detection based on Dominant Sets is better, being the error ratio at least \(1.5\) points lower than the others.