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Cody P Coyne,1 Lakshmi Narayanan2 1Department of Basic Sciences, 2Department of Clinical Sciences, College of Veterinary Medicine, Mississippi State University, Starkville, MS, USA Purpose: Corticosteroids are effective in the management of a variety of disease states, such as several forms of neoplasia (leukemia and lymphoma), autoimmune conditions, and severe inflammatory responses. Molecular strategies that selectively “target” delivery of corticosteroids minimize or prevents large amounts of the pharmaceutical moiety from passively diffusing into normal healthy cell populations residing within tissues and organ systems. Materials and methods: The covalent immunopharmaceutical, dexamethasone-(C21-phosphoramide)-[anti-EGFR] was synthesized by reacting dexamethasone-21-monophosphate with a carbodiimide reagent to form a dexamethasone phosphate carbodiimide ester that was subsequently reacted with imidazole to create an amine-reactive dexamethasone-(C21-phosphorylimidazolide) intermediate. Monoclonal anti-EGFR immunoglobulin was combined with the amine-reactive dexamethasone-(C21-phosphorylimidazolide) intermediate, resulting in the synthesis of the covalent immunopharmaceutical, dexamethasone-(C21-phosphoramide)-[anti-EGFR]. Following spectrophotometric analysis and validation of retained epidermal growth factor receptor type 1 (EGFR)-binding avidity by cell-ELISA, the selective anti-neoplasic cytotoxic potency of dexamethasone-(C21-phosphoramide)-[anti-EGFR] was established by MTT-based vitality stain methodology using adherent monolayer populations of human pulmonary adenocarcinoma (A549) known to overexpress the tropic membrane receptors EGFR and insulin-like growth factor receptor type 1. Results: The dexamethasone:IgG molar-incorporation-index for dexamethasone-(C21-phosphoramide)-[anti-EGFR] was 6.95:1 following exhaustive serial microfiltration. Cytotoxicity analysis: covalent bonding of dexamethasone to monoclonal anti-EGFR immunoglobulin did not significantly modify the ex vivo antineoplastic cytotoxicity of dexamethasone against pulmonary adenocarcinoma at and between the standardized dexamethasone equivalent concentrations of 10-9 M and 10-5 M. Rapid increases in antineoplastic cytotoxicity were observed at and between the dexamethasone equivalent concentrations of 10-9 M and 10-7 M where cancer cell death increased from 7.7% to a maximum of 64.9% (92.3%–35.1% residual survival), respectively, which closely paralleled values for “free” noncovalently bound dexamethasone. Discussion: Organic chemistry reaction regimens were optimized to develop a multiphase synthesis regimen for dexamethasone-(C21-phosphoramide)-[anti-EGFR]. Attributes of dexamethasone-(C21-phosphoramide)-[anti-EGFR] include a high dexamethasone molar incorporation-index, lack of extraneous chemical group introduction, retained EGFR-binding avidity (“targeted” delivery properties), and potential to enhance long-term pharmaceutical moiety effectiveness. Keywords: dexamethasone, anti-EGFR, organic chemistry reactions, synthesis, selective “targeted” delivery, covalent immunopharmaceuticals, EGFR

Aims and Objective: The aim of this laboratory study was to evaluate the effect of three home bleaching agents: Vivastyle Paint On, Vivastyle, and Opalascence PF on the color stability of the microfilled composite Durafill, the nanofilled composite Filtek Z 350, and the glass ionomer cement Fuji II. Materials and Methods: There were 3 groups in this study (n=40)-Group I: durafill, Group II: Filtek Z 350, and Group III: Fuji II. Each group was further subdivided into 4 subgroups (n=10), Subgroup A: bleaching with Vivastyle Paint On, Subgroup B: bleaching with Vivastyle, Subgroup C: bleaching with Opalascence PF, and Subgroup D: control specimens stored in distilled water. Bleaching was carried out following the manufacturer′s instructions for a period of 14 days. At the end of the bleaching regimen, the specimens were tested for color change using the CIELAB technique and a reflectance spectrophotometer. Results: The data was subjected to statistical analysis. A Kruskal-Wallis variance analysis and Mann Whitney U test were done to determine the significant color change of the restorative materials. All restorative materials demonstrated a significantly higher color change (ΔE) with Vivastyle ( P < 0.0001). The mean color change of GIC (11.4 ± 0.3) was the highest among the materials followed by Durafill (7.5 ± 0.1). Filtek z 350 (0.3 ± 0.1) showed the least color change with all the bleaching agents. Conclusion: Glass ionomer cement showed the highest color change followed by the microfilled composite. The nanofilled composite was found to be highly stable in terms of color.

Environmentally benign, highly stable oxides exhibiting desirable optical properties and high near-IR reflectance are being researched for their potential application as pigments. Mg1−xMxV2O6 (M = Mn, Cu, Co, or Ni) oxides with brannerite-type structures were synthesized by the conventional solid-state reaction method to study their optical properties. These series exhibit structural transitions from brannerite (C2/m) to distorted brannerite (P1¯) and NiV2O6-type (P1¯) structures. The average color of Mg1−xMxV2O6 compounds varies from reddish-yellow to brown to dark brown. The L*a*b* color coordinates reveal that Mg1−xCuxV2O6 and Mg1−xNixV2O6 show more red hues in color with x = 0.4 and x = 0.5, respectively. The UV–Vis diffuse reflectance spectra indicate a possible origin for these results include the ligand-to-metal charge transfer (O2− 2p-V5+ 3d), metal-to-metal charge transfer (from Mn2+ 3d/Cu2+ 3d/Co2+ 3d/Ni2+ 3d to V5+ 3d), band gap transitions, and d–d transitions. Magnetic property measurements revealed antiferromagnetic behavior for the compounds Mg1−xMxV2O6 (M = Mn, Cu, Co, and Ni), and an oxidation state of +2 for the M ions was deduced from their Curie–Weiss behavior. The system Mg1−xMnxV2O6 has a NIR reflectance in the range between 40% and 70%, indicating its potential to be utilized in the pigment industry.

Most of the water losses occur during water distribution in pipelines during transportation. In order to eradicate the losses, an "IoT based water distribution system" integrated with "Fog and Cloud Computing" proposed for water distribution and underground health monitoring of pipes. For developing an effective water distribution system based on Internet of Things (IoT), the demand of the consumer should be analysed. So, towards predicting the water demand for consumers, Deep learning methodology called Long Short-Term Memory (LSTM) is compared with traditional Time Series methodology called Auto Regressive Integrated Moving Average (ARIMA) in terms of error and accuracy. Now based on demand prediction with higher accuracy, an IoT integrated "Water Distribution Network (WDN)" is designed using hydraulic engineering. This WDN design will ensure minimal losses during transportation and quality of water to the consumers. This will lead to development of a smart system for water distribution. [ABSTRACT FROM AUTHOR]