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The current study focuses on the preparation and optimization of lipid PLGA hybrid nanoparticles of 5-fluorouracil (5-FU-LPHNs) using a three-factor, three-level Box-Behnken design for sustained release and enhanced in-vitro anticancer efficacy. The morphology of the developed 5-FU-LPHNs was spherical and found in the range of 155.7–316.4 nm, entrapment efficiency (80%–92%), polydispersity index (0.11–0.19) and zeta potential (−19.7 mV to −29.4 mV) depicting nano-sized and stable nanoparticles. The XRD and DSC investigations showed the absence of characteristic peaks of 5-fluorouracil in the developed formulations indicating amorphization and successful encapsulation of 5-fluorouracil in the developed LPHNs. The in-vitro release showed a biphasic release pattern with an initial burst release pursued by sustained release up to 72 h. The in-vitro cytotoxicity studies of the developed 5-FU-LPHNs were found more cytotoxic than the free drug solution in HT-29 and HCT116 cancer cell lines. In both cell lines, the half maximal inhibitory concentration (IC50) values of 5-FU-LPHNs were approximately 2.06-fold and 1.83-fold, less than that of the 5-FU solution (p <.05). These results suggest that the developed LPHNs can be used as a potential drug delivery approach for the effective delivery of 5-fluorouracil with enhanced anticancer efficacy to colorectal tumors. [ABSTRACT FROM AUTHOR]

Objective This research aimed to explore and identify novel therapeutic targets for psoriasis, elucidate the underlying pathogenic mechanisms, and develop innovative drug candidates or repurpose existing drugs for effective treatment. Methods A comprehensive literature review was conducted to gather current knowledge on psoriasis pathogenesis and existing treatment modalities. Various molecular targets involved in key cellular processes, signaling pathways, and immune dysregulation were identified and evaluated as potential therapeutic targets. In vitro experiments using human skin cell cultures and animal models were employed to assess the efficacy, safety, and mechanism of action of developed drug candidates or repurposed drugs. Pharmacological evaluations, including bioavailability and pharmacokinetic studies, were performed to determine their potential for clinical translation. Results The study identified several promising therapeutic targets implicated in the pathogenesis of psoriasis, including specific cytokines, immune cell subsets, and signaling pathways. Experimental findings demonstrated the efficacy of newly developed drug candidates or repurposed drugs in suppressing keratinocyte hyper proliferation, mitigating inflammation, and modulating immune responses. Pharmacological evaluations indicated favorable drug properties, including suitable bioavailability and pharmacokinetic profiles. Conclusion The research findings provide valuable insights into the pathogenesis of psoriasis and potential therapeutic targets for intervention. The identification and development of novel drug candidates or repurposing existing drugs targeting these therapeutic targets hold promise for improved treatment outcomes in psoriasis patients. Further translational research and clinical trials are warranted to validate these findings and establish their clinical efficacy and safety. The interdisciplinary approach merging pharmacology and dermatology in this study showcases the importance of collaboration and highlights the potential for developing personalized treatment strategies for psoriasis patients. [ABSTRACT FROM AUTHOR]

With the growing cyber-infrastructure of smart grids, the threat of cyber-attacks has intensified, posing an increased risk of compromised communication links. Of particular concern is the false data injection (FDI) attack, which has emerged as a highly dangerous cyber-attack targeting smart grids. This paper addresses the limitations of the variable dummy value model proposed in the authors previous work and presents a novel defense methodology called the nonlinear function-based variable dummy value model for the AC power flow network. The proposed model is evaluated using the IEEE 14-bus test system, demonstrating its effectiveness in detecting FDI attacks. It has been shown that previous detection techniques are unable to detect FDI attacks, whereas the proposed method is shown to be successful in the detection of such attacks, guaranteeing the security of the smart grid's measurement infrastructure. [ABSTRACT FROM AUTHOR]

Discrete element modelling (DEM) is widely regarded as one of the most effective methods for simulating the soil-to-tool interaction. Discrete element simulations were carried out to evaluate the performance of mouldboard plough in paddy soil. The Hertz-Mindlin bonding contact model was applied to develop the bonding between soil particles. Maximum soil draught force (3.64 N) was obtained at 15 cm depth. The force decreased from 1.98 to 1.10 N as the depth decreased from 10 cm to 5 cm. From the results, the DEM have the potential to predict cutting forces of mouldboard plough in all direction draught, vertical and side (Fx, Fy and Fz. A linear relationship was observed throughout the simulation process between working depths. It is concluded that the EDEM model has the potential to serve as a reliable tool for determining the soil-tool interaction. [ABSTRACT FROM AUTHOR]

In this research, we propose an energy-management scheme for domestic users, which uses the load-shifting strategy of demand-side management (DSM). The research demonstrates that the energy sector's circular debt problem from the viewpoint of a developing country can be solved by incorporating DSM. Circular debt is a chain reaction that arises when the balance between cost and energy supply collapses. Circular debt is an ongoing problem in Pakistan, where economic crises are continuously posing a threat to the energy sector. DSM is envisioned to address these concerns in a dynamic way thoroughly: introducing DSM can minimize circular debt, increase grid reliability, and smooth the supply–demand operation. Circular debt is directly linked with the subsidy offered by the government of Pakistan. As the cost of energy utilized by consumers increases, the subsidy also increases due to the direct link between the two entities. Therefore, the subsidy can be controlled by energy-consumption management with the adoption of DSM. This study addresses that by incorporating optimized cost solutions, circular debt can be regulated to improve the economy of the energy sector. A genetic algorithm is used as an optimization tool to manage demand and generate an optimal schedule under a dynamic electricity pricing signal. To support the utility, a solar system is used as a secondary energy source. Finally, the results show a curtailment in the payable costs at both the consumer and government ends, thus reducing the circular debt in the bigger picture. The reduction is 18% without and 41% with renewable energy support. [ABSTRACT FROM AUTHOR]