Al-Hadba'a University College

Steel guardrails on expressways are a vital piece of traffic safety infrastructure. Unexpected events, such as accidents, might cause a freight vehicle travelling on the road to lose control. Because it may prevent the freight vehicle from speeding off the road, a steel guardrail can help keep the driver safe. As a result, the steel guardrail’s guiding ability, anti-collision performance and safety behaviour are crucial indices to measure expressway steel safety in collision accidents between freight vehicles and the steel guardrails. In this study, finite element (FE) simulation is carried out on the collision between freight cars and an expressway three-wave steel guardrail. A two-wave beam steel guardrail has been compared to the simulation results. The dynamic simulation results were predicted using the LS-Dyna FE simulator at a speed of 90 km/h and impact angles of 10°, 15°, 20°, 25°, and 30°. To estimate the steel guardrail’s protective function in real-time experimental approaches, freight vehicles clash with steel guardrails on expressways, resulting in the steel guardrail collapsing and the freight car rushing off the road. To accurately anticipate the safety of highway steel guardrails, FE modelling is the best option. The expressway three-wave steel guardrail absorbs more than 60% of the freight car’s principal translational momentum in a collision, reducing collision force transmitted to passengers and highway accident severity.

This comprehensive review delineates the latest advancements in stimuli-responsive drug delivery systems engineered for the targeted treatment of breast carcinoma. The manuscript commences by introducing mammary carcinoma and the current therapeutic methodologies, underscoring the urgency for innovative therapeutic strategies. Subsequently, it elucidates the logic behind the employment of stimuli-responsive drug delivery systems, which promise targeted drug administration and the minimization of adverse reactions. The review proffers an in-depth analysis of diverse types of stimuli-responsive systems, including thermoresponsive, pH-responsive, and enzyme-responsive nanocarriers. The paramount importance of material choice, biocompatibility, and drug loading strategies in the design of these systems is accentuated. The review explores characterization methodologies for stimuli-responsive nanocarriers and probes preclinical evaluations of their efficacy, toxicity, pharmacokinetics, and biodistribution in mammary carcinoma models. Clinical applications of stimuli-responsive systems, ongoing clinical trials, the potential of combination therapies, and the utility of multifunctional nanocarriers for the co-delivery of assorted drugs and therapies are also discussed. The manuscript addresses the persistent challenge of drug resistance in mammary carcinoma and the potential of stimuli-responsive systems in surmounting it. Regulatory and safety considerations, including FDA guidelines and biocompatibility assessments, are outlined. The review concludes by spotlighting future trajectories and emergent technologies in stimuli-responsive drug delivery, focusing on pioneering approaches, advancements in nanotechnology, and personalized medicine considerations. This review aims to serve as a valuable compendium for researchers and clinicians interested in the development of efficacious and safe stimuli-responsive drug delivery systems for the treatment of breast carcinoma.

The advancement of novel technologies, coupled with bioinformatics, has led to the discovery of additional genes, such as long noncoding RNAs (lncRNAs), that are associated with drug resistance. LncRNAs are composed of over 200 nucleotides and do not possess any protein coding function. These lncRNAs exhibit lower conservation across species, are typically expressed at low levels, and often display high specificity towards specific tissues and developmental stages. The LncRNA MALAT1 plays crucial regulatory roles in various aspects of genome function, encompassing gene transcription, splicing, and epigenetics. Additionally, it is involved in biological processes related to the cell cycle, cell differentiation, development, and pluripotency. Recently, MALAT1 has emerged as a novel mechanism contributing to drug resistance or sensitivity, attracting significant attention in the field of cancer research. This review aims to explore the mechanisms through which MALAT1 confers resistance to chemotherapy and radiotherapy in cancer cells.

The lateral confinement coefficient (Ks) crucially influences the strength, ductility and seismic performances of the reinforced concrete columns (RCC), which is highly relevant for structural engineers and researchers. To address this purpose and enhance predictive performance this study utilizes novel hybrid evolutionary ensemble modeling approach by utilizing various input parameters from 204 data collected from different literatures. A typical random forest method provided less accuracy (R2 = 0.84) in estimating the Ks values, hence; Artificial Neural Network (ANN) based Random Forest (RF) and Gradient Boosting (GB) evolutionary models was employed in this study. Statistically, the performance of the ANN based evolutionary RF GB models (R2 = 0.948 R2 = 0.933) were comparatively greater than the typical RF ensemble model. Also, the performance of the ANN-RF and ANN-GB was compared by using various statistical parameters like RMSE for ANN-RF as 0.0943 and ANN-GB as 0.1065 along with other indices. In addition to the statistical indices, different visual representations like REC curve, Taylor diagram and residuals leverage plots were developed for comparing the performances of the model. The statistical values and plots reveal that both the models provide reliable and superior alternative for Ks prediction capable of handling complex non-linear relationships. Since there are more feature variables available for estimating the Ks value, the SHAP analysis and sensitivity analysis was also carried out to find out the feature variable which impacts the output while modifying the respective variables. Finally, the rank analysis was carried out by comparing all the performance indicators of both the models, which depicted that the ANN-RF model outperforms the ANN-GB model in training, whereas in testing conditions, ANN-GB model performed better for estimating the values of Ks, contributing safer design and resilient RCC columns. The Graphical User Interface (GUI) was developed based on the best performing model.

The green synthesis approach has drawn a lot of interest as an environmentally friendly and sustainable acceptable means of producing a diverse range of nanoparticles (NPs). This piece described a rapid approach for synthesizing selenium nanoparticles (SeNPs) with grape seed extract. A biologically active composition of selenium-chitosan nanoparticles (Se-chitosan NPs) has been prepared and characterized using, ultraviolet–visible, scanning electron microscopy, transmission electron microscopy, and zeta potential and size distribution experiments. To study the anticancer activity of prepared NP cytotoxicity (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay of chitosan nanoparticles (Chito-NPs), SeNPs were tested on two cancer cell lines: A549 and normal cell line (HK-2). In addition to a series of morphological changes, induction of apoptosis, reactive oxygen species (ROS) generation, and mitochondrial membrane potential. The results showed that the synthesized NPs were spherical with 55.285 and 30.9 nm, for SeNPs and Se-chitosan NPs, respectively. In the A549 cell line, SeNPs and Se-chitosan NPs exhibited dose-dependent cytotoxicity, with an IC50 for Chito-NPs of 24.09 µg/mL, whereas for SeNPs it was 18.56 µg/mL. Conversely, normal cell lines (MCF-10) were not significantly cytotoxically affected by SeNPs and Se-chitosan NPs. Additionally, SeNP and Se-chitosan NP treatment resulted in increased ROS generation and caused mitochondrial dysfunction. Based on ROS-mediated pathways, the results demonstrated that Chito-NPs, SeNPs, and Se-chitosan NPs cause apoptosis and death in A549 cells. As nanotherapeutics, Chito-NPs, SeNPs, and Se-chitosan NPs appear to offer a great deal of unrealized potential based on these findings. Further investigation is warranted and clinically significant to elucidate the specific therapeutic potential and safety of these NPs when applied in vivo. In this work, we show that exposure to SeNPs, Chito-NPs, and Se-chitosan NPs alters the human lung cancer cell line A549’s ROS route of signaling, thereby causing the induction of apoptosis.