An Interesting Class of Monotonic Functions

1909 ◽  
Vol 16 (1) ◽  
pp. 4
Author(s):  
Arthur R. Schweitzer
2020 ◽  
Vol 21 (4) ◽  
pp. 429-438 ◽  
Author(s):  
Bruno Casciaro ◽  
Francesca Ghirga ◽  
Deborah Quaglio ◽  
Maria Luisa Mangoni

Cationic antimicrobial peptides (AMPs) are an interesting class of gene-encoded molecules endowed with a broad-spectrum of anti-infective activity and immunomodulatory properties. They represent promising candidates for the development of new antibiotics, mainly due to their membraneperturbing mechanism of action that very rarely induces microbial resistance. However, bringing AMPs into the clinical field is hampered by some intrinsic limitations, encompassing low peptide bioavailability at the target site and high peptide susceptibility to proteolytic degradation. In this regard, nanotechnologies represent an innovative strategy to circumvent these issues. According to the literature, a large variety of nanoparticulate systems have been employed for drug-delivery, bioimaging, biosensors or nanoantibiotics. The possibility of conjugating different types of molecules, including AMPs, to these systems, allows the production of nanoformulations able to enhance the biological profile of the compound while reducing its cytotoxicity and prolonging its residence time. In this minireview, inorganic gold nanoparticles (NPs) and biodegradable polymeric NPs made of poly(lactide-coglycolide) are described with particular emphasis on examples of the conjugation of AMPs to them, to highlight the great potential of such nanoformulations as alternative antimicrobials.


2021 ◽  
Author(s):  
Nicole Ziegenbalg ◽  
Ruth Lohwasser ◽  
Giovanni D’Andola ◽  
Torben Adermann ◽  
Johannes Christopher Brendel

Polyethersulfones are an interesting class of polymers for industrial applications due to their unusual properties such as a high refractive index, flame-retardant properties, high temperature and chemical resistance. The common...


Polymers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1729
Author(s):  
Patrizio Raffa

The study of interactions between polyelectrolytes (PE) and surfactants is of great interest for both fundamental and applied research. These mixtures can represent, for example, models of self-assembly and molecular organization in biological systems, but they are also relevant in industrial applications. Amphiphilic block polyelectrolytes represent an interesting class of PE, but their interactions with surfactants have not been extensively explored so far, most studies being restricted to non-associating PE. In this work, interactions between an anionic amphiphilic triblock polyelectrolyte and different types of surfactants bearing respectively negative, positive and no charge, are investigated via surface tension and solution rheology measurements for the first time. It is evidenced that the surfactants have different effects on viscosity and surface tension, depending on their charge type. Micellization of the surfactant is affected by the presence of the polymer in all cases; shear viscosity of polymer solutions decreases in presence of the same charge or nonionic surfactants, while the opposite charge surfactant causes precipitation. This study highlights the importance of the charge type, and the role of the associating hydrophobic block in the PE structure, on the solution behavior of the mixtures. Moreover, a possible interaction model is proposed, based on the obtained data.


2021 ◽  
Vol 11 (9) ◽  
pp. 3836
Author(s):  
Valeri Gitis ◽  
Alexander Derendyaev ◽  
Konstantin Petrov ◽  
Eugene Yurkov ◽  
Sergey Pirogov ◽  
...  

Prostate cancer is the second most frequent malignancy (after lung cancer). Preoperative staging of PCa is the basis for the selection of adequate treatment tactics. In particular, an urgent problem is the classification of indolent and aggressive forms of PCa in patients with the initial stages of the tumor process. To solve this problem, we propose to use a new binary classification machine-learning method. The proposed method of monotonic functions uses a model in which the disease’s form is determined by the severity of the patient’s condition. It is assumed that the patient’s condition is the easier, the less the deviation of the indicators from the normal values inherent in healthy people. This assumption means that the severity (form) of the disease can be represented by monotonic functions from the values of the deviation of the patient’s indicators beyond the normal range. The method is used to solve the problem of classifying patients with indolent and aggressive forms of prostate cancer according to pretreatment data. The learning algorithm is nonparametric. At the same time, it allows an explanation of the classification results in the form of a logical function. To do this, you should indicate to the algorithm either the threshold value of the probability of successful classification of patients with an indolent form of PCa, or the threshold value of the probability of misclassification of patients with an aggressive form of PCa disease. The examples of logical rules given in the article show that they are quite simple and can be easily interpreted in terms of preoperative indicators of the form of the disease.


1967 ◽  
Vol 74 (3) ◽  
pp. 314 ◽  
Author(s):  
A. F. Beardon
Keyword(s):  

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