Anwar Rayan

Paclitaxel (PTX) is among the most widely used antimicrotubular chemotherapy agents available from natural sources. It has a wide range of antitumor effectiveness, particularly against breast, ovarian and lung malignancies. IDD‑1040 is a novel anticancer chemical conjugate that combines lipoic acid with PTX and demonstrates an anticancer efficiency superior to that of PTX alone. The aim of the present study was to investigate the analytical, formulation and pharmacokinetic aspects of IDD‑1040, shedding light on its pharmacological behavior and the possible mechanisms underlying its enhanced anticancer activity. IDD‑1040 was administered to mice as an intravenous bolus, and the pharmacokinetic parameters were determined over the following 7 days. The results revealed a total clearance of 1.689 l/h.kg, volume of distribution of 1.93 l/kg, average half‑life of 1.14 h and terminal half‑life of 8.64 h. Notably, the area under the curve of IDD‑1040 was >14‑fold higher than that of PTX, suggesting slower metabolism and that prodrug itself may have antitumor activity. An in vitro tubulin polymerization assay revealed distinct tubulin‑binding characteristics for IDD‑1040 compared with PTX. Due to the poor water solubility of IDD‑1040, a formulation development experiment was conducted. In total, 31 formulations were prepared that became transparent when diluted with water. In addition, some formulations achieved a relatively high drug content (12 mg/g) without the use of surfactants. Moreover, they included fewer excipients compared with the formulations diluted with water, suggesting a promising approach for drug formulation. In summary, IDD‑1040 exhibited extended circulation, efficient tissue distribution and reduced metabolite formation in vitro, warranting further exploration of its mechanisms of action and therapeutic potential. Future studies are recommended to assess the stability, pharmacokinetics and pharmacodynamics of these refined IDD‑1040 formulations to gauge their suitability for clinical application.

In recent years, the integration of technology into education has significantly transformed teaching methods, especially in science education. Tools like PhET simulations have proven highly effective in enhancing student engagement and comprehension. Research has highlighted the value of simulation-based learning in fostering critical thinking and problem-solving skills. This study aimed to explore the impact of simulations, with a focus on PhET, on improving elementary students’ learning outcomes, an area that remains under-researched. The study compared the performance of two groups of third-grade students: one group learned about solubility using PhET simulations, while the other relied on traditional textbook instruction. Each group comprised fifty students. The study lasted for a two-month period. The instructional approach was investigative learning. Data were gathered through student responses to materials science questions aligned with Bloom’s Taxonomy, allowing for a detailed evaluation of their understanding and application of scientific concepts. Responses were assessed for accuracy and scored accordingly. We ran an independent-sample t-test to decide whether the difference in the mean score in science achievement between the two research groups was significant. The results showed that students using PhET simulations not only achieved significantly higher scores but also demonstrated their ability to explain their reasoning during problem-solving tasks. These findings emphasize the substantial advantages of incorporating digital tools like PhET simulations into elementary science education, as they enhance conceptual understanding and better equip students to tackle future scientific challenges. The present research results complement the previous research on using technology in the chemistry elementary classroom and add the issue of simulations to this research. The results of this study are centered on the topic of solubility. To broaden the generalizability of these findings, future research should examine the effects of simulations on student achievement in a wider range of elementary science topics.

This study introduces the intelligent learning engine (ILE) optimization technology, a novel approach designed to revolutionize screening processes in bioinformatics, cheminformatics, and a range of other scientific fields. By focusing on the efficient and precise identification of candidates with desirable characteristics, the ILE technology marks a significant leap forward in addressing the complexities of candidate selection in drug discovery, protein classification, and beyond. The study’s primary objective is to address the challenges associated with optimizing screening processes to efficiently select candidates across various fields, including drug discovery and protein classification. The methodology employed involves a detailed algorithmic process that includes dataset preparation, encoding of protein sequences, sensor nucleation, and optimization, culminating in the empirical evaluation of molecular activity indexing, homology-based modeling, and classification of proteins such as G-protein-coupled receptors. This process showcases the method’s success in multiple sequence alignment, protein identification, and classification. Key results demonstrate the ILE’s superior accuracy in protein classification and virtual high-throughput screening, with a notable breakthrough in drug development for assessing drug-induced long QT syndrome risks through hERG potassium channel interaction analysis. The technology showcased exceptional results in the formulation and evaluation of novel cancer drug candidates, highlighting its potential for significant advancements in pharmaceutical innovations. The findings underline the ILE optimization technology as a transformative tool in screening processes due to its proven effectiveness and broad applicability across various domains. This breakthrough contributes substantially to the fields of systems optimization and holds promise for diverse applications, enhancing the process of selecting candidate molecules with target properties and advancing drug discovery, protein classification, and modeling.

Generative artificial intelligence tools are flourishing across various sciences, particularly in the educational domain. ChatGPT, with its versions 3.5 and 4.0, stands out for its multilingual capabilities, catering to both students and educators. This research aimed to evaluate the performance differences between these versions, and importantly, to compare the accuracy of ChatGPT's responses in English versus Arabic. In our study, we presented ChatGPT with 39 chemistry problems related to 6th-7th grade curriculum, including twenty-five open questions and fourteen multiple-choice questions. Each response was categorized as accurate, partially accurate, or inaccurate. Our analysis, focused on trends across versions and languages, revealed significant enhancements in version 4.0, particularly in its ability to process Arabic. However, despite these improvements, our findings indicate that responses in English consistently outperformed those in Arabic in terms of accuracy. In light of this discrepancy, we suggest that ChatGPT either incorporates additional Arabic databases into its training regimen or develops a code that adopts the following strategy to ensure more accurate responses in science education: questions should first be translated from Arabic to English, addressed, and then retranslated into Arabic before being presented to the user. This approach takes advantage of the greater accuracy of responses in English to benefit Arabic-speaking users, and it may also improve outcomes for speakers of other languages who experience less precise answers in the fields of chemistry or science education.

In recent years, artificial intelligence (AI) has emerged as a valuable resource for teaching and learning, and it has also shown promise as a tool to help solve problems. A tool that has gained attention in education is ChatGPT, which supports teaching and learning through AI. This research investigates the difficulties faced by ChatGPT in comprehending and responding to chemistry problems pertaining to the topic of Introduction to Material Science. By employing the theoretical framework proposed by Holme et al., encompassing categories such as transfer, depth, predict/explain, problem solving, and translate, we evaluate ChatGPT’s conceptual understanding difficulties. We presented ChatGPT with a set of thirty chemistry problems within the Introduction to Material Science domain and tasked it with generating solutions. Our findings indicated that ChatGPT encountered significant conceptual knowledge difficulties across various categories, with a notable emphasis on representations and depth, where difficulties in representations hindered effective knowledge transfer.

Biofilms, which consist of microorganisms embedded in a polymer-rich matrix, contribute to a variety of infections and increase antimicrobial resistance. Thus, there is a constant need to develop new chemotherapeutic agents to combat biofilms. This review article focuses on the use of alkyl gallates, gallic acid and its esters (methyl, ethyl, propyl, butyl, hexyl, octyl, and dodecyl gallate), most of which are found in plants, to inhibit biofilm formation. The studies under review reveal that alkyl gallates have the capacity to prevent biofilm development and eradicate mature biofilms through mechanisms that suppress the synthesis of the extracellular polymeric matrix, inhibit quorum-sensing signaling, and alter the microbial cell membrane. The effects are stronger the greater the length of the alkyl chain. Moreover, the alkyl gallates’ preventive activity against biofilm formation occurs at doses below the minimum inhibitory concentration. More importantly, combining alkyl gallates with antimicrobials or blue-light irradiation produces a synergistic effect on the inhibition of biofilm formation that can be used to treat infections and overcome microbial resistance.

KRAS mutations, which are the main cause of the pathogenesis of lethal pancreatic adenocarcinomas, impair the functioning of the GTPase subunit, thus rendering it constitutively active and signaling intracellular pathways that end with cell transformation. In the present study, the AsPC‑1 cell line, which has a G12D‑mutated KRAS gene sequence, was utilized as a cellular model to test peptide nucleic acid‑based antisense technology. The use of peptide nucleic acids (PNAs) that are built to exhibit improved hybridization specificity and have an affinity for complementary RNA and DNA sequences, as well as a simple chemical structure and high biological stability that affords resistance to nucleases and proteases, enabled targeting of the KRAS‑mutated gene to inhibit its expression at the translation level. Because PNA‑based antisense molecules should be capable of binding to KRAS mRNA sequences, PNAs were utilized to target the mRNA of the mutated KRAS gene, a strategy that could lead to the development of a novel drug for pancreatic cancer. Moreover, it was demonstrated that introducing new PNA to cells inhibited the growth of cancer cells and induced apoptotic death and, notably, that it can inhibit G12D‑mutated KRAS gene expression, as demonstrated by RT‑PCR and western blotting. Altogether, these data strongly suggest that the use of PNA‑based antisense agents is an attractive therapeutic approach to treating KRAS‑driven cancers and may lead to the development of novel drugs that target the expression of other mutated genes.

A novel conjugate of docetaxel and biotin (designated as IDD-1010) was designed and chemically synthesized via an ester linkage at position 2’ carbon in docetaxel. The synthesized pure IDD-1010 exhibits a potent anti-cancer activity in in vitro and in vivo studies. At 10 nM, IDD-1010 has induced increased apoptosis and mitotic arrest of PC3-Luc prostate cancer cells, causing aneuploidy and cell death at higher concentrations. Toxicology studies indicate that the maximal tolerated dose (MTD) of IDD-1010 is 150 mg/kg in mice; equivalent to about 12.2 mg/kg of body weight, or to about an 850 mg dose for a patient weighing 70 kg. The MTD-treated mice exhibited weight gain similar to that of the control group, with no gross pathological signs at 14 days post-dosing. At a lower dose, IDD-1010 treatment did not lead to any significant weight loss in mice, although decreased the tumor volume stemming from injecting cancer cells into the dorsal loop of mouse prostate, and it was found to be more potent than Paclitaxel (reference drug). Similarly, IDD-1010 treatment significantly reduced tumor weight and thereby increased the percentage of mice survival as compared to reference drug-treated and control groups. To summarize, the described experiments using IDD-1010, as compared to the reference drug, strongly suggest a potential treatment utility with a wider therapeutic window for prostate cancer. Henceforth, clinical research on such a novel drug candidate would be greatly worthwhile.

Dysregulation of glucose homeostasis followed by chronic hyperglycemia is a hallmark of diabetes mellitus (DM), a disease spreading as a worldwide pandemic for which there is no satisfactory dietary treatment or cure. The development of glucose-controlling drugs that can prevent complications of DM, such as hyperglycemia and oxidative stress, which contribute to the impairment of the key physiological processes in the body, is of grave importance. In pursuit of this goal, this study screened 41 plant extracts for their antidiabetic and antioxidant activities by employing assays to test for α-amylase inhibition and free radical scavenging activity (FRSA) and by measuring glucose uptake in L6-GLUT4myc cells. While extracts of Rhus coriaria, Punica granatum, Olea europaea, Pelargonium spp., Stevia rebaudiana, and Petroselinum crispum demonstrated significant α-amylase inhibition, the extracts of Rhus coriaria and Pelargonium spp. also demonstrated increased FRSA, and the extract of Rhus coriaria stimulated glucose uptake. These natural extracts, which are believed to have fewer side effects because they are prepared from edible plants, interfere with the process in the small intestine that breaks down dietary carbohydrates into monosaccharide and disaccharide derivatives, and thereby suppress increases in diet-induced blood glucose; hence, they may have clinical value for type 2 diabetes management. The Pelargonium spp. and Rhus coriaria extracts demonstrated the highest antidiabetic and antioxidant activities. Both plants may offer valuable medical benefits, especially because they can be taken as dietary supplements by patients with diabetes and can serve as sources of new, natural-based antidiabetic drug candidates. The enhancement of cellular glucose uptake stimulated by Rhus coriaria extract could lead to the development of clinical applications that regulate blood glucose levels from within the circulatory system. Isolating bioactive substances from these plant extracts and testing them in diabetic mice will significantly advance the development of natural drugs that have both antidiabetic and free radical-scavenging properties, likely with lesser side effects.

Streptococcus mutans bacterium is implicated in the pathogenesis of dental caries due to the production of biofilm and organic acids from dietary sucrose. Despite the availability of various means of prophylaxis, caries still has a high worldwide prevalence. Therefore, it is important to find new pharmaceuticals to inhibit S. mutans biofilm formation and acidogenicity. The aim of the current study was to evaluate the activity of lauryl gallate (dodecyl gallate) against S. mutans acidogenicity, the expression of biofilm-associated genes, and biofilm development on solid surfaces (polystyrene, glass). The biofilm quantities produced by S. mutans bacteria were assessed using colorimetric and optical profilometry techniques. Acidogenicity was evaluated by measuring the pH of the biofilm growth medium with microelectrode. Assessment of the expression of gene coding for glucan-binding protein B (gbpB), glucosyltranferases B, -C, -D (gtfB, -C, -D), and the F-ATPase β subunit of F₁ protein (atpD) was carried out using a quantitative reverse transcription-polymerase chain reaction (RT-qPCR). The results demonstrate the capacity of lauryl gallate to significantly inhibit S. mutans acidogenicity and biofilm development on solid surfaces, in a dose-dependent manner, compared to untreated bacteria (p < 0.05). The highest activity of lauryl gallate occurred at a concentration of 98.98 µM, at which it suppressed biofilm formation by 100% and lowered pH levels by 98%. The effect of lauryl gallate treatment on gene expression changes, as demonstrated by our RT-qPCR data, was limited to the gtfD gene only, was a significant (48%) decrease in gene expression, obtained for the biofilm-producing bacteria, while a 300% increase in fold change for the same gene occurred in the planktonic cells. It is important to note that in previous studies we showed a broader effect of related derivatives. However, a similar magnitude of difference in effects between biofilm and planktonic cells for the atpD gene was obtained after treatment with octyl gallate and reverse magnitude for the same gene after treatment with ethyl gallate. Therefore, to ascertain the possible direct or indirect effects of lauryl gallate, as well as octyl gallate and ethyl gallate, more research is needed to examine the effects on the amount of enzymes and on the enzymatic activity of the products of the affected genes that are involved in the production and maintenance of biofilm by S. mutans.