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Magnetically Responsive Nanomedicine
Published in Lin Zhu, Stimuli-Responsive Nanomedicine, 2021
Meng Zhang, Ergang Liu, Yongzhuo Huang
SAR is a crucial parameter of magnetic nanoparticles for clinical trials; higher SAR values imply lower dose. The factors governing SAR include the composition, size, and shape of the magnetic nanoparticles, as well as the external magnetic field. Guardia et al. prepared the magnetic nanocubes between 13 and 40 nm via a one-pot synthesis [178]. When the size was 19 nm, the magnetic nanocubes had the highest SAR and showed the hyperthermia effect in KB cells. The oleic acid-based magnetic nanocubes with an average size of 30 nm, coated with chitosan-DOPA, had higher specific loss power (SLP) than the commercial product, Feridex, and exhibited superior magnetic heating ability. The chitosan-DOPA conjugated magnetic nanocubes offered higher in vitro cell apoptosis and in vivo anti-cancer activity on the A549 tumor xenografted mice than Feridex (Figure 7.12) [179].
Biological Correlates of Microwave
Published in Jitendra Behari, Radio Frequency and Microwave Effects on Biological Tissues, 2019
The concept of SAR is not sufficient when one is looking for biological effects based, depending on parameters other than absorption. This raises question about using these parameters for evaluating effects that may be of some other type. The possibility of nonthermal effects is thus a controversial one and therefore the problem of dosimetry becomes more pronounced. SAR may be a valid quantitative measure of interaction other than absorptive ones when the mechanism is dependent on the intensity of E field, except however when direction of the E field is of importance with respect to the biological structure (L/λ value). Similarly, the SAR concept may not be sufficient for the interactions directly through the E field. Further it is always a matter of uncertainty between perceived field strength and the actual RF exposure with respect to the biological object over a period of time. SAR may also depend upon the mobile phone used: i.e., GSM 900 or GSM 1800 MHz type (Panagopoulous et al. (2007)).
Dosimetry in Bioelectromagnetics
Published in Marko Markov, Dosimetry in Bioelectromagnetics, 2017
The irrelevance of SAR as a measure of biological response is also apparent when comparing the stress response stimulated by extremely low-frequency and RF fields. Although both fields use the same nonthermal biochemical pathway, the SARs for the responses in the two frequency ranges differ by many orders of magnitude, as shown earlier. Since the same biochemical reactions are stimulated in different frequency ranges at very different SAR levels, SAR cannot be the basis for a biological standard.
A review on machine learning methods for in silico toxicity prediction
Published in Journal of Environmental Science and Health, Part C, 2018
Gabriel Idakwo, Joseph Luttrell, Minjun Chen, Huixiao Hong, Zhaoxian Zhou, Ping Gong, Chaoyang Zhang
An SAR model is a statistical/mathematical model used to establish an approximate relationship between a biological property of a compound and its structure-derived physicochemical and structural features3,9,10 in order to predict the activities of unknown molecules. The basic assumptions in SAR modeling are that molecules with similar structures exhibit similar biological activity, and that the physicochemical properties and/or structural properties of a molecule can be encoded as molecular descriptors to predict the biological activity of structurally related compounds. The independent variable is referred to as molecular descriptors generated from the structure of the molecule, while the dependent variable could be a numeric value of toxicity, such as LD50 in the case of quantitative SAR, or the classification of a compound as toxic versus nontoxic in a binary qualitative SAR model. Generally, the steps for developing a toxicity prediction model involve (see Figure 1): (1) data curation (gathering and cleaning data that relates chemicals to toxicity endpoints), (2) molecular descriptors generation, (3) prediction model development, and (4) model evaluation and validation.
Review on Chemistry of Oxazole derivatives: Current to Future Therapeutic Prospective
Published in Egyptian Journal of Basic and Applied Sciences, 2023
Sweta Joshi, Meenakshi Mehra, Ramandeep Singh, Satinder Kakar
The SAR studies presented in Table 1 show versatility of oxazole moiety. SAR shows the chemical relationship between 3D structure of the molecule and their biological activities. Oxazole is a versatile moiety, so it gained a huge popularity among the researchers and medicinal chemists [9]. The SAR studies revealed the pharmacophore present in the compounds which are essential for the pharmacological activity. Figures 3-16 indicate the important pharmacophores with and their therapeutic activity.