Physical Analysis of Heat for Formation and Entropy of Ceria Oxide Using Topological Indices.

BACKGROUND: Cerium oxide nanoparticles (CeO2 NPs) have gained their importance as engineered nanomaterials (ENMs) that have wide applications as catalysts in industry, which direct to their prominent occurrence in natural and engineered water systems. Cerium oxide nanoparticles (CeO2 NPs) have gained their importance as engineered nanomaterials (ENMs) that have wide applications as catalysts in industry, which direct to their prominent occurrence in natural and engineered water systems. In wastewater treatment plants, CeO2 NPs can stay colloidally stable and be unconstrained in the secondary effluents. As they entered into tertiary treatment, such as advanced oxidation processes (AOPs), it is noteworthy that how the generated reactive oxygen species will change the colloidal stability, aggregation, and the surface chemistry of CeO2 NPs. AIM AND OBJECTIVE: The study was aimed to analyze the chemical graph of the crystal structure of Ceria Oxide(cuprite) CeO2. Also, our main objective is to compute the Heat of Formation and Entropy using degree based topological indices. MATERIALS AND METHODS: Chemical graph theory plays an important role in modeling and designing any chemical structure. The topological indices are the numerical invariants of a molecular graph and are very useful for predicting their physical properties. For calculation, we have utilized the combinatorial processing strategy, edge partition technique, vertex partition strategy, analytic procedures, graph hypothetical tools, degree counting technique and entirety of degrees of neighbor technique. Moreover, Matlab programming has been utilized for numerical computations and checks. We likewise utilized the maple for plotting these numerical outcomes. RESULTS: We have computed Heat of Formation and Entropy using degree based topological indices. Our main results are based on some degree based topological indices, namely, the atom bond connectivity index ABC, geometric arithmetic index GA, general Randi index, Forgotten index, Augmented zagreb index and Balban index for the chemical graph of the crystal structure of cuprite CeO2[p, q, t] We also provide a detailed application of the computed results. CONCLUSION: We discuss these indices exhibited difference with the reported heat of formation and entropy of cuprite CeO2[p, q, t] In almost all the cases, an exponential increase of aforementioned indices is observed with the increase in the number of cells or other words size of cuprite CeO2[p, q, t] nanocrystal. On the other hand, a linear relationship of indices with respect to the number of formula units suggests a slight modification of these indices for an appropriate explanation of the physical properties of cuprite CeO2[p, q, t] nanocrystal of varying size and hence its prospective application in nanoceria engineering.

Catalytic cracking of polystyrene pyrolysis oil: Effect of Nb2O5 and NiO/Nb2O5 catalyst on the liquid product composition.

The catalytic cracking of polystyrene pyrolysis oil was investigated over a Nb2O5 and a NiO/Nb2O5 catalyst in a fixed bed reactor. First, the pyrolysis of two different polystyrene feedstock (polystyrene foam and polystyrene pellet) was carried out in a semi-batch reactor, and the resulting polystyrene pellets pyrolysis oil was selected for catalytic cracking reaction because of its high liquid yield (85%). Catalytic cracking experiments were then performed at different temperatures (350-500 °C) using Nb2O5 or NiO/Nb2O5 catalyst. Gas chromatography-mass spectrometry analysis of liquid product obtained from the catalytic cracking process showed that the dimers in the pyrolysis oil were converted to monomers during the catalytic cracking process. The catalytic cracking results also showed that the NiO/Nb2O5 catalyst (having slightly higher acidic sites) had slightly higher activity for monomer conversion than the Nb2O5 catalyst (having less acidic sites). X-ray diffraction, transmission electron microscopy, pyridine Fourier transform infrared spectroscopy, NH3 Temperature Programmed Desorption and X-ray photoelectron spectroscopy were used to characterize the catalyst. The highest catalytic cracking activity was observed at 400 °C with the Nb2O5 catalyst with 4% toluene, 6% ethylbenzene, approximately 50% styrene, 13% α-methyl styrene, and only 6% of dimers in the liquid oil. The increase in temperature positively affected the yield of gases during catalytic cracking process.

Time-dependent AI-Modeling of the anticancer efficacy of synthesized gallic acid analogues.

BACKGROUND/AIM: Main objective of this study is mapping of the anticancer efficacy of synthesized gallic acid analogues using modeling and artificial intelligence (AI) over a large range of concentrations and exposure times to explore the underline mechanisms of drug action and draw careful inferences regarding drug response heterogeneity. METHODS: Two series of gallic acid derivatives i.e. esters and amides have been synthesized and characterized by FTIR, NMR and mass spectrometry. The compounds have been tested in vitro for their anticancer activity against wild type human ovarian cancer cell line A2780, prostate cancer cell line PC3 and normal human fibroblast cells 3T3. To completely characterize optimal anticancer activity, a comprehensive model using piecewise recursive Hill model is used to quantitatively assess the in vitro anticancer effect of the tested compounds as a function of concentration and exposure time for periods ranging from 24 to 72 h. A robust artificial intelligence approach i.e. the "Support Vector Machine (SVM) Learning Algorithm" is adopted to utilize the data obtained at different temporal values, to identify compounds that trail forecasting algorithm. RESULTS: All the synthesized analogues were found biocompatible. Significantly low EC50 values indicated that tested compounds have potent anticancer activity against A2780 cell line in comparison to PC3 cells where only few compounds generated same impact at almost 200 times high dose. On the basis of EC50 values, compounds 7 h, 7 m, 9c, 9b, 7c, 7b and 7 g were identified as the most active anticancer agent against A2780. Three major patterns of drug response heterogeneity were observed for different compounds in the form of multiple Hill graphs and shallow slopes. The anticancer efficiency of the compounds was verified using Machine learning SVM regression learner algorithm. For compounds 7a, 7b, 7e, 7 g, 7o, 7 r, 9b, 9e-9 g higher accuracy was found in predicted and experimentally obtained end point potency in terms of % viability. CONCLUSIONS: Pharmacodynamics modeling of anticancer potential of the synthesized compounds revealed that drug efficacy and response heterogeneity could be modulated by changing the exposure time to optimize therapeutic impact. Combining experimental results with AI based drug action forecasting, compounds 7b, 7 g, and 9b may be tested further as potent anticancer agent for in vivo studies. This approach may serve a useful tool for extrapolation of in vitro results for generating lead compounds in in vivo and preclinical studies.

Cancer drug therapy and stochastic modeling of "nano-motors".

BACKGROUND: Controlled inhibition of kinesin motor proteins is highly desired in the field of oncology. Among other interventions, there exists "targeted chemotherapeutic regime/options" of selective Eg5 competitive and allosteric inhibitors, inducing cancer cell apoptosis and tumor regression with improved safety profiles. RESEARCH QUESTION: Though promising, such studies are still under clinical trials, for the discovery of efficient and least harmful Eg5 inhibitors. The aim of this research was to bridge the computational modeling approach with drug design and therapy of cancer cells. METHODS: A computational model, interfaced with the clinical data of "Eg5 dynamics" and "inhibitors" via special functions, is presented in this article. Comparisons are made for the drug efficacy, and the threshold values are predicted through numerical simulations. RESULTS: Results are obtained to depict the dynamics induced by ispinesib, when used as an inhibitor of kinesin Eg5, on cancer cell lines.

Role of key players in paradigm shifts of prostate cancer bone metastasis.

The decreased bone mineral density and compromised bone strength predispose individuals to skeletal osteoporosis. Both prostate cancer and bone metastasis caused by cancer invasion have remained a great challenge to researchers. With the advancement in the fields of biochemistry and biomechanics, the molecular mechanisms that make prostate cancer metastasize to bone have recently been identified, and they provide new molecular targets for drug development. Many biochemical by-products have been identified to help in understanding the interaction between the bone and the tumor. Enhanced clinical management of patients with bone metastases was reported during the past decade; however, the anticipated risk and the response to the therapy are still challenging to assess. In this review, the key players that play a dominant role in secondary osteoporosis are addressed. An attempt is made to provide the readers with a clear understanding of the communication pathways between each of the cell types involved in this vicious cycle. Furthermore, the role of Wnts, sclerostin, RANKL, PTHrP, and their respective clinical studies are addressed in this study.

A review on hyperthermia via nanoparticle-mediated therapy.

Hyperthermia treatment, generated by magnetic nanoparticles (MNPs) is promising since it is tumour-focused, minimally invasive and uniform. The most unique feature of magnetic nanoparticles is its reaction and modulation by a magnetic force basically responsible for enabling its potential as heating mediators for cancer therapy. In magnetic nanoparticle hyperthermia, a tumour is preferentially loaded with systemically administered nanoparticles with high-absorption cross-section for transduction of an extrinsic energy source to heat. To maximize the energy deposited in the tumour while limiting the exposure to healthy tissues, the heating is achieved by exposing the region of tissue containing magnetic nanoparticles to an alternating magnetic field. The magnetic nanoparticles dissipate heat from relaxation losses thereby heating localized tissue above normal physiological ranges. Besides thermal efficiency, the biocompatibility of magnetite nanoparticles assisted its deployment as efficient drug carrier for targeted therapeutic regimes. In the present article, we provide a state-of-the-art review focused on progress in nanoparticle induced hyperthermia treatments that have several potential advantages over both global and local hyperthermia treatments achieved without nanoparticles. Green bio-nanotechnology has attracted substantial attention and has demonstrable abilities to improve cancer therapy. Furthermore, we have listed the challenges associated with this treatment along with future prospective that could attract the interest of biomedical engineers, biomaterials scientists, medical researchers and pharmacological research groups.