The Fuzziness in Molecular, Supramolecular, and Systems Chemistry

Fuzzy Logic is a good model for the human ability to compute words. It is based on the theory of fuzzy set. A fuzzy set is different from a classical set because it breaks the Law of the Excluded Middle. In fact, an item may belong to a fuzzy set and its complement at the same time and with the same or different degree of membership. The degree of membership of an item in a fuzzy set can be any real number included between 0 and 1. This property enables us to deal with all those statements of which truths are a matter of degree. Fuzzy logic plays a relevant role in the field of Artificial Intelligence because it enables decision-making in complex situations, where there are many intertwined variables involved. Traditionally, fuzzy logic is implemented through software on a computer or, even better, through analog electronic circuits. Recently, the idea of using molecules and chemical reactions to process fuzzy logic has been promoted. In fact, the molecular word is fuzzy in its essence. The overlapping of quantum states, on the one hand, and the conformational heterogeneity of large molecules, on the other, enable context-specific functions to emerge in response to changing environmental conditions. Moreover, analog input–output relationships, involving not only electrical but also other physical and chemical variables can be exploited to build fuzzy logic systems. The development of “fuzzy chemical systems” is tracing a new path in the field of artificial intelligence. This new path shows that artificially intelligent systems can be implemented not only through software and electronic circuits but also through solutions of properly chosen chemical compounds. The design of chemical artificial intelligent systems and chemical robots promises to have a significant impact on science, medicine, economy, security, and wellbeing. Therefore, it is my great pleasure to announce a Special Issue of Molecules entitled “The Fuzziness in Molecular, Supramolecular, and Systems Chemistry.” All researchers who experience the Fuzziness of the molecular world or use Fuzzy logic to understand Chemical Complex Systems will be interested in this book

In-Vitro Biological Tissue State Monitoring based on Impedance Spectroscopy

The relationship between post-mortem state and changes of biological tissue impedance has been investigated to serve as a basis for developing an in-vitro measurement method for monitoring the freshness of meat. The main challenges thereby are the reproducible measurement of the impedance of biological tissues and the classification method of their type and state. In order to realize reproducible tissue bio-impedance measurements, a suitable sensor taking into account the anisotropy of the biological tissue has been developed. It consists of cylindrical penetrating multi electrodes realizing good contacts between electrodes and the tissue. Experimental measurements have been carried out with different tissues and for a long period of time in order to monitor the state degradation with time. Measured results have been evaluated by means of the modified Fricke-Cole-Cole model. Results are reproducible and correspond to the expected behavior due to aging. An appropriate method for feature extraction and classification has been proposed using model parameters as features as input for classification using neural networks and fuzzy logic. A Multilayer Perceptron neural network (MLP) has been proposed for muscle type computing and the age computing and respectively freshness state of the meat. The designed neural network is able to generalize and to correctly classify new testing data with a high performance index of recognition. It reaches successful results of test equal to 100% for 972 created inputs for each muscle. An investigation of the influence of noise on the classification algorithm shows, that the MLP neural network has the ability to correctly classify the noisy testing inputs especially when the parameter noise is less than 0.6%. The success of classification is 100% for the muscles Longissimus Dorsi (LD) of beef, Semi-Membraneous (SM) of beef and Longissimus Dorsi (LD) of veal and 92.3% for the muscle Rectus Abdominis (RA) of veal. Fuzzy logic provides a successful alternative for easy classification. Using the Gaussian membership functions for the muscle type detection and trapezoidal member function for the classifiers related to the freshness detection, fuzzy logic realized an easy method of classification and generalizes correctly the inputs to the corresponding classes with a high level of recognition equal to 100% for meat type detection and with high accuracy for freshness computing equal to 84.62% for the muscle LD beef, 92.31 % for the muscle RA beef, 100 % for the muscle SM veal and 61.54% for the muscle LD veal.  Auf der Basis von Impedanzspektroskopie wurde ein neuartiges in-vitro-Messverfahren zur Überwachung der Frische von biologischem Gewebe entwickelt. Die wichtigsten Herausforderungen stellen dabei die Reproduzierbarkeit der Impedanzmessung und die Klassifizierung der Gewebeart sowie dessen Zustands dar. Für die Reproduzierbarkeit von Impedanzmessungen an biologischen Geweben, wurde ein zylindrischer Multielektrodensensor realisiert, der die 2D-Anisotropie des Gewebes berücksichtigt und einen guten Kontakt zum Gewebe realisiert. Experimentelle Untersuchungen wurden an verschiedenen Geweben über einen längeren Zeitraum durchgeführt und mittels eines modifizierten Fricke-Cole-Cole-Modells analysiert. Die Ergebnisse sind reproduzierbar und entsprechen dem physikalisch-basierten erwarteten Verhalten. Als Merkmale für die Klassifikation wurden die Modellparameter genutzt

Intrinsically Disordered Proteins and Chronic Diseases

This book is an embodiment of a series of articles that were published as part of a Special Issue of Biomolecules. It is dedicated to exploring the role of intrinsically disordered proteins (IDPs) in various chronic diseases. The main goal of the articles is to describe recent progress in elucidating the mechanisms by which IDPs cause various human diseases, such as cancer, cardiovascular disease, amyloidosis, neurodegenerative diseases, diabetes, and genetic diseases, to name a few. Contributed by leading investigators in the field, this compendium serves as a valuable resource for researchers, clinicians as well as postdoctoral fellows and graduate student

Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data

Abstract Managing, processing and understanding big healthcare data is challenging, costly and demanding. Without a robust fundamental theory for representation, analysis and inference, a roadmap for uniform handling and analyzing of such complex data remains elusive. In this article, we outline various big data challenges, opportunities, modeling methods and software techniques for blending complex healthcare data, advanced analytic tools, and distributed scientific computing. Using imaging, genetic and healthcare data we provide examples of processing heterogeneous datasets using distributed cloud services, automated and semi-automated classification techniques, and open-science protocols. Despite substantial advances, new innovative technologies need to be developed that enhance, scale and optimize the management and processing of large, complex and heterogeneous data. Stakeholder investments in data acquisition, research and development, computational infrastructure and education will be critical to realize the huge potential of big data, to reap the expected information benefits and to build lasting knowledge assets. Multi-faceted proprietary, open-source, and community developments will be essential to enable broad, reliable, sustainable and efficient data-driven discovery and analytics. Big data will affect every sector of the economy and their hallmark will be ‘team science’.http://deepblue.lib.umich.edu/bitstream/2027.42/134522/1/13742_2016_Article_117.pd

Ultrasonication assisted Layer-by-Layer technology for the preparation of multi-functional anticancer drugs paclitaxel and lapatinib

In this dissertation, ultrasonication assisted Layer-by-Layer (LbL) technology for the preparation of multifunctional poorly water-soluble anticancer drug nanoparticles, paclitaxel and lapatinib, has been developed. Many FDA approved drugs are very low soluble in water; therefore, it is very difficult to load and control their release and targeting efficiently, which greatly confines their application. The development of this method will pave the way for the development and application of those low soluble anticancer drugs. In the first part of this dissertation, the first approach for powerful ultrasonication, the top-down approach (sonicating bulk drug crystals in polyelectrolyte solution), was successfully applied for the preparation of the nanoparticles of paclitaxel. For this approach, a 200 nm diameter was a kind of magic barrier for colloidal particles prepared. This diameter barrier may be related to the nucleation size of the solvent vapor microbubbles. Consequently, agents enhancing bubbling formation (such as NH4HCO3) were applied to decrease paclitaxel colloid particles to 100-120 nm. Those paclitaxel nanoparticles were Layer-by-Layer coated with a 10-20 nm polycation/polyanion shell to provide aqueous colloidal stability and slower particle dissolution. However, a large obstacle of these powerful ultrasonication methods was a necessity of long ca 45 minutes high power ultrasonication which resulted in TiO2contamination from titanium electrode. The small amount of TiO2 contamination from ultrasonication did negatively affect the in vivotesting of this system in mice, and had to be removed before low toxicity of the Layer-by-Layer coated paclitaxel nanoparticles were observed. In the second part of the dissertation, the second approach for sonication, the bottom-up approach (sonicating drug in a water-miscible organic solvent followed by slow water add-in) was successfully applied for the preparation of the nanoparticles of lapatinib and paclitaxel with less powerful sonication. By using polymeric excipients combined with non-ionic and anionic surfactants along with regular sonication, the prepared particle sizes was uniform at around 140-150 nm. Less sonication time (ca 15 minutes) and lower sonication power avoided TiO2 contamination. The amphiphiles attached to the hydrophobic nanoparticles and served as anchors for LbL shell. The inner LbL layers and surfactants minimized the surface free energy, thereby preventing crystal form changes and nanoparticles coalescence, while the outermost layers enhanced colloidal stability. In the third part of the dissertation, LbL shells with PEGylation (using a block copolymer of poly-L-lysine (PLL) and PEG) for lapatinib were developed for enhanced colloidal stability in high molarity PBS buffer. In the above proposed paclitaxel and lapatinib formulation, we obtained 150-200 nm with high drug content of 80-90% due to very thin capsule walls (ca 10 nm). The drug release time from the LbL capsules was found to be between 10 and 20 hours depending on the shell thickness. Washless Layer-by-Layer assembly was used: 1) addition of polycation in the amount that is enough to reverse surface charge of the dispersion to a high positive (+30 mV) value; 2) addition of polyanion in the amount that is enough to reverse surface charge of the dispersion to a high negative (-30 mV) value. No intermediate washing of nanoparticles was done until the shell was complete. The washless method had the advantage of time and energy saving, preservation of the sample structure and no losses of sample. In the last part of the dissertation, we elaborated nanoformulation of two drugs in one nanocapsule locating paclitaxel in the core and lapatinib on the shell periphery. With this formulation, combining in one nanoparticle dual drugs, we reached the drugs\u27 efficiency synergy. In a multidrug-resistant (MDR) ovarian cancer cell line, OVCAR-3, LbL lapatinib/paclitaxel nanocolloids mediated an enhanced cell growth inhibition in comparison with the LbL paclitaxel-only and LbL lapatinib-only treatment, not to say the free one drug treatment

Development of advanced monitoring and control tools for rAAV production in the insect cell system

"Since the first publication introducing the concept in 1972, gene therapy has had a series of success stories and setbacks. However, the recent rise of awareness, public interest, promising results in clinical trials and recent market approvals indicate that gene therapy has come to stay. Currently there is a growing interest from the biopharmaceutical industry in gene and cell therapy, mostly using viral vectors. (...)

A novel diffusion tensor imaging-based computer-aided diagnostic system for early diagnosis of autism.

Autism spectrum disorders (ASDs) denote a significant growing public health concern. Currently, one in 68 children has been diagnosed with ASDs in the United States, and most children are diagnosed after the age of four, despite the fact that ASDs can be identified as early as age two. The ultimate goal of this thesis is to develop a computer-aided diagnosis (CAD) system for the accurate and early diagnosis of ASDs using diffusion tensor imaging (DTI). This CAD system consists of three main steps. First, the brain tissues are segmented based on three image descriptors: a visual appearance model that has the ability to model a large dimensional feature space, a shape model that is adapted during the segmentation process using first- and second-order visual appearance features, and a spatially invariant second-order homogeneity descriptor. Secondly, discriminatory features are extracted from the segmented brains. Cortex shape variability is assessed using shape construction methods, and white matter integrity is further examined through connectivity analysis. Finally, the diagnostic capabilities of these extracted features are investigated. The accuracy of the presented CAD system has been tested on 25 infants with a high risk of developing ASDs. The preliminary diagnostic results are promising in identifying autistic from control patients