Recent breakthroughs in graphene quantum dot-enhanced sonodynamic and photodynamic therapy.

Water-soluble graphene quantum dots (GQDs) have recently exhibited considerable potential for diverse biomedical applications owing to their exceptional optical and chemical properties. However, the pronounced heterogeneity in the composition, size, and morphology of GQDs poses challenges for a comprehensive understanding of the intricate correlation between their structural attributes and functional properties. This variability also introduces complexities in scaling the production processes and addressing safety considerations. Light and sound have firmly established their role in clinical applications as pivotal energy sources for minimally invasive therapeutic interventions. Given the limited penetration depth of light, photodynamic therapy (PDT) predominantly targets superficial conditions such as dermatological disorders, head and neck malignancies, ocular ailments, and early-stage esophageal cancer. Conversely, ultrasound-based sonodynamic therapy (SDT) capitalizes on its superior ability to propagate and focus ultrasound within biological tissues, enabling a diverse range of therapeutic applications, including the management of gliomas, breast cancer, hematological tumors, and modulation of the blood-brain barrier (BBB). Considering the advancements in theranostic and precision therapies, reevaluating these conventional energy sources and their associated sensitizers is imperative. This review introduces three prevalent treatment modalities that harness light and sound stimuli: PDT, SDT, and a synergistic approach that integrates PDT and SDT. This study delineated the therapeutic dynamics and contemporary designs of sensitizers tailored to these modalities. By exploring the historical context of the field and elucidating the latest design strategies, this review underscores the pivotal role of GQDs in propelling the evolution of PDT and SDT. This aspires to stimulate researchers to develop "multimodal" therapies integrating both light and sound stimuli.

Recent Progress in Prompt Molecular Detection of Exosomes Using CRISPR/Cas and Microfluidic-Assisted Approaches Toward Smart Cancer Diagnosis and Analysis.

Exosomes are essential indicators of molecular mechanisms involved in interacting with cancer cells and the tumor environment. As nanostructures based on lipids and nucleic acids, exosomes provide a communication pathway for information transfer by transporting biomolecules from the target cell to other cells. Importantly, these extracellular vesicles are released into the bloodstream by the most invasive cells, i. e., cancer cells; in this way, they could be considered a promising specific biomarker for cancer diagnosis. In this matter, CRISPR-Cas systems and microfluidic approaches could be considered practical tools for cancer diagnosis and understanding cancer biology. CRISPR-Cas systems, as a genome editing approach, provide a way to inactivate or even remove a target gene from the cell without affecting intracellular mechanisms. These practical systems provide vital information about the factors involved in cancer development that could lead to more effective cancer treatment. Meanwhile, microfluidic approaches can also significantly benefit cancer research due to their proper sensitivity, high throughput, low material consumption, low cost, and advanced spatial and temporal control. Thereby, employing CRISPR-Cas- and microfluidics-based approaches toward exosome monitoring could be considered a valuable source of information for cancer therapy and diagnosis. This review assesses the recent progress in these promising diagnosis approaches toward accurate cancer therapy and in-depth study of cancer cell behavior.

Bioresource Polymer Composite for Energy Generation and Storage: Developments and Trends.

The ever-growing demand of human society for clean and reliable energy sources spurred a substantial academic interest in exploring the potential of biological resources for developing energy generation and storage systems. As a result, alternative energy sources are needed in populous developing countries to compensate for energy deficits in an environmentally sustainable manner. This review aims to evaluate and summarize the recent progress in bio-based polymer composites (PCs) for energy generation and storage. The articulated review provides an overview of energy storage systems, e. g., supercapacitors and batteries, and discusses the future possibilities of various solar cells (SCs), using both past research progress and possible future developments as a basis for discussion. These studies examine systematic and sequential advances in different generations of SCs. Developing novel PCs that are efficient, stable, and cost-effective is of utmost importance. In addition, the current state of high-performance equipment for each of the technologies is evaluated in detail. We also discuss the prospects, future trends, and opportunities regarding using bioresources for energy generation and storage, as well as the development of low-cost and efficient PCs for SCs.

Modelling rate of penetration in drilling operations using RBF, MLP, LSSVM, and DT models.

One of the most important problems that the drilling industry faces is drilling cost. Many factors affect the cost of drilling. Increasing drilling time has a significant role in increasing drilling costs. One of the solutions to reduce drilling time is to optimize the drilling rate. Drilling wells at the optimum time will reduce the time and thus reduce the cost of drilling. The drilling rate depends on different factors, some of which are controllable and some are uncontrollable. In this study, several smart models and a correlation were proposed to predict the rate of penetration (ROP) which is very important for planning a drilling operation. 5040 real data points from a field in the South of Iran have been used. The ROP was modelled using Radial Basis Function, Decision Tree (DT), Least Square Vector Machine (LSSVM), and Multilayer Perceptron (MLP). Bayesian Regularization Algorithm (BRA), Scaled Conjugate Gradient Algorithm and Levenberg-Marquardt Algorithm were employed to train MLP and Gradient Boosting (GB) was used for DT. To evaluate the accuracy of the developed models, both graphical and statistical techniques were used. The results showed that DT-GB model with an R2 of 0.977, has the best performance, followed by LSSVM and MLP-BRA with R2 of 0.971 and 0.969, respectively. Aside from that, the proposed empirical correlation has an acceptable accuracy in spite of simplicity. Moreover, sensitivity analysis illustrated that depth and pump pressure have the highest effects on ROP. In addition, the leverage approach approved that the developed DT-GB model is valid statistically and about 1% of the data are suspected or out of the applicability domain of the model.

Investigating the Performance of Carboxylate-Alumoxane Nanoparticles as a Novel Chemically Functionalized Inhibitor on Asphaltene Precipitation.

In recent years, researchers have attempted to find some practical approaches for asphaltene adsorption and the prevention or postponement of asphaltene precipitation. Among different techniques, nanotechnology has attracted the researchers' attention to overcome the formation damage resulting from the deposition of asphaltenes. In this study, the application of two types of carboxylate-alumoxane nanoparticles (functionalized boehmite by methoxyacetic acid (BMA) and functionalized pseudo-boehmite by methoxyacetic acid (PBMA)) for asphaltene adsorption and precipitation was investigated. First, the synthesis of two functionalized nanoparticles was performed via the sol-gel method. For the assessment of the adsorption efficiency and adsorption capacity of these nanoparticles toward asphaltene adsorption, the batch adsorption experiments applying ultraviolet-visible (UV-Vis) spectroscopy were performed. The Langmuir and Freundlich isotherms were studied to describe the interaction between asphaltene molecules and carboxylate-alumoxane nanoparticles. For determining the "onset" point of asphaltene precipitation, the indirect method, which was based on the difference in the optical property of various solutions containing different concentrations of asphaltene, was utilized by applying UV-Vis spectroscopy. The isotherm models indicate that the adsorption of asphaltene on the surface of nanoparticles is better fitted to the Freundlich isotherm model compared with the Langmuir model. In the presence of PBMA (0.1 wt %), the onset point was delayed around 26, 20, and 17% in the asphaltene concentrations of 1000, 3000, and 5000 ppm, respectively, in comparison with their reference synthetic oils. On the other hand, these postponements for BMA nanoparticles (0.1 wt %) were 17%, 9%, and insignificant for the asphaltene concentrations of 1000, 3000, and 5000 ppm, respectively. The results reveal that two functionalized nanoparticles tend to adsorb asphaltene molecules and have a positive impact on the postponement of asphaltene precipitation due to molecular interactions between the surface of carboxylate-alumoxane nanoparticles and asphaltene molecules. However, PBMA nanoparticles exhibited better performance on the asphaltene adsorption and postponement of asphaltene precipitation, which is related to its smaller size, as well as higher surface area, compared with BMA nanoparticles.