Nano-Immunodetection and Quantification of Mycobacteria in Metalworking Fluids

The accurate detection and enumeration of mycobacteria in metalworking fluids (MWFs) is imperative from an environmental protection and occupational health perspective. We report here on a comparison of the labeling efficiency of nano-immunomagnetic particles (NIMP) and free antibody (FAb) to detect mycobacteria in semisynthetic MWF by using both traditional visualization analysis and cluster analysis aided visualization analysis (CAAVA). The NIMP labeling method involved coating nanometer-scale magnetic particles with Protein A, and oriented conjugation of polyclonal antibodies specific to Mycobacterium spp. The FAb labeling method is modified from the traditional immunofluorescence (IF) method for more efficient detection of mycobacteria in a model MWF. The labeling efficiency of NIMP and FAb were 7.2 ± 4.6 and 16.3 ± 5.5%, and the specificity 85.0 ± 6.1 and 88.1 ± 10.5%, respectively, based on traditional visualization analysis. Based on CAAVA analysis, the labeling efficiency of NIMP and FAb increased to 12.4 ± 1.6 and 20.5 ± 3.9%, and the specificity to 97.8 ± 3.2 and 98.5 ± 2.5%, respectively. A linear relationship of FCM counts and seeded concentrations was observed over four orders of magnitude (R 2 ≤ 0.99) in pure and ternary cultures. The results strongly support the applicability of either FAb or NIMP coupled with CAAVA and flow cytometry for rapid detection and enumeration of mycobacteria in complex matrices.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63114/1/ees.2007.24.58.pd

Synthesis, structure, magnetic behavior and dielectric relaxation of the La<inf>x</inf>Sr<inf>2-x</inf>Fe<inf>х</inf>Ti<inf>1-х</inf>O<inf>4</inf> (х ​= ​0.5, 0.7) oxide ceramic

© 2020 Elsevier Inc. This study is devoted to the investigation of the high dielectric constant causes in complex oxides with a structure of the K2NiF4 type. А new thermobaric treated ceramics on the basis conjugate LaxSr2-xFeхTi1-хO4 (х ​= ​0.5, 0.7) solid solutions was synthesized and the study their structure, microstructure, magnetic and dielectric properties was performed. It is shown that antiferromagnetic interactions coexist with ferromagnetic, which become dominant towards to low temperatures; the appearance of two types of magnetic interactions may be related to the presence of magnetic ions of different valences. Different values of the dielectric constants ε are observed in wide region of frequencies 10–107 ​Hz. In obtained at ambient pressure LaxSr2-xFeхTi1-хO4 (х ​= ​0.5, 0.7) ceramics the highest permittivity ε value is only 30–50 in the frequency range from 1 ​kHz to 1 ​MHz. After the samples treatment at 1273 ​K and P ​= ​4 ​GPa during 5 ​min ε increases to 5–102–103 ​at 293 ​К and independent of frequency in the range (102–106) Hz. At the temperature increase the permittivity as well increases and the ε value becomes ~106 at, approximately, f ​= ​100 ​Hz and T ​= ​750 ​K. An obvious change of samples microstructure and polyhedra structure anisotropy in LaxSr2-xFeхTi1-хO4 (х ​= ​0.5, 0.7) was observed after the thermobaric treatment. Described in this article performed dielectric properties investigations indicate that possible reasons of the high-permittivity origin are specifics of layered structure, microstructure and charge polarization associated with it, Maxwell-Wagner polarization at the grain boundaries and inhomogeneities and small polaron hopping conduction mechanism

Evolutionary algorithm for automated formation of decision-making models for predicting the safety of opioid therapy

In this paper, an evolutionary algorithm for solving the problem of predicting the safety of opioid therapy for patients with pancreatic cancer is proposed. Opioid analgesics such as fentanyl and morphine are used as a therapy for pain syndromes. Using the patient database, based on the results of the therapy applied to them, it is determined whether there is a correlation between the outcome and the combination of input data taken into account. To find a set of informative features, it is proposed to use the genetic algorithm for multi-criterion optimization, in which two criteria are reduced to one generalized criterion using the method of "additive convolution". The formed combination of the selected input features, which affects the outcome, is used to build a decision support model and to evaluate it afterwards. © Published under licence by IOP Publishing Ltd

Predicting of fentanyl-associated neurotoxicity in pancreatic cancer with clical, genetic model [Прогнозирование фентанил-ассоциированной нейротоксичности у больных с раком поджелудочной железы с помощью клинико-генетической модели]

Aim. To develop a model for the implementation of opioid - associated neurotoxicity in patients with pancreatic cancer based on an analysis of the relationship of clinical and genetic factors. Materials and methods. In 45 patients with pancreatic cancer, 54 clinical and genetic factors were studied for predicting the implementation of opioid-associated neurotoxicity, receiving a transdermal form of fentanyl. Results. A clinical genetic model of the implementation of opioid - associated neurotoxicity in patients with pancreatic cancer was developed using the example of a transdermal form of fentanyl Conclusion. The clinical genetic model for predicting the risk of opioid-associated neurotoxicity in patients with pancreatic cancer is important from the perspective of personalized medicine. © 2021 Global Media Tekhnologii. All rights reserved