Discovery of Oral Chemotherapeutic Reversal Agents for Treating Multidrug Resistance Cancer.

The major limitation of cancer treatment is multidrug resistance (MDR), which leads to the inactivation of chemotherapeutic drugs and greater than 90% mortality. To solve this ordeal, we applied ligand-based drug design and bioiosteric replacement strategy from an indazole to a pyrazole ring to discover compounds 27 and 43 with good potential for reversing drug resistance in combination with paclitaxel, and their reversal fold values were 53.2 and 51.0 at 5 µM, respectively, against an MDR cancer cell line (KBvin). Based on the PK profile results, we selected compound 43 with a longer half-life for mechanistic and animal experiments. Combination treatment with compound 43 and paclitaxel-induced apoptosis and enhanced subG1 by decreasing mitochondrial membrane potential in KBvin cells. In addition, 43 also inhibited P-gp function by interfering with ATPase activity. Meanwhile, cotreatment with compound 43 and paclitaxel significantly suppressed tumor growth (TGI = 55.5%) at a dose of 200 mg/kg (PO) in a xenograft model and showed no obvious liver or kidney toxicity by H&E staining. Overall, compound 43 may serve as a safe and effective oral resistance reversal chemotherapeutic agent.

Design of an Artificial Intelligence of Things-Based Sesame Oil Evaluator for Quality Assessment Using Gas Sensors and Deep Learning Mechanisms.

Traditional oil quality measurement is mostly based on chemical indicators such as acid value, peroxide value, and p-anisidine value. This process requires specialized knowledge and involves complex steps. Hence, this study designs and proposes a Sesame Oil Quality Assessment Service Platform, which is composed of an Intelligent Sesame Oil Evaluator (ISO Evaluator) and a Cloud Service Platform. Users can quickly assess the quality of sesame oil using this platform. The ISO Evaluator employs Artificial Intelligence of Things (AIoT) sensors to detect changes in volatile gases and the color of the oil during storage. It utilizes deep learning mechanisms, including Artificial Neural Network (ANN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM) to determine and evaluate the quality of the sesame oil. Evaluation results demonstrate that the linear discriminant analysis (LDA) value is 95.13. The MQ2, MQ3, MQ4, MQ7, and MQ8 sensors have a positive correlation. The CNN combined with an ANN model achieves a Mean Absolute Percentage Error (MAPE) of 8.1820% for predicting oil quality, while the LSTM model predicts future variations in oil quality indicators with a MAPE of 0.44%. Finally, the designed Sesame Oil Quality Assessment Service Platform effectively addresses issues related to digitization, quality measurement, supply quality observation, and scalability.

Design and synthesis of pyrazole derivatives against neutrophilic inflammation.

Neutrophils are the most abundant immune cells. However, neutrophil dysregulation leads to acute and chronic inflammation and is involved in various diseases. The aim of this study was to develop anti-inflammatory agents in human neutrophils. A drug screening was conducted on in-house compounds with the potential to inhibit the respiratory burst, which involves the generation of superoxide anions in human neutrophils. Bioisosteric replacement was then applied to design more active derivatives. The most potent inhibitors of superoxide anion generation activity were compounds 58 and 59, which had IC50 values of 13.30 and 9.06 nM, respectively. The inhibitory effects of 58 and 59 were reversed by H89, a PKA inhibitor. PDE selective screening indicated that the best inhibitory effects were PDE4B1 and PDE4D2, and the inhibitory activities were 83% and 85%, respectively, at a 10 µM concentration of 59. The final molecular simulation experiment highlighted the slightly different binding poses of 58 and 59 in the PDE4 active site. An in vivo pharmacokinetic study revealed that the half-life of 59 was approximately 79 min when using intravenous bolus administration. This work introduced a new class structure of PDE4 inhibitors resulting in potent neutrophil inactivation activity, with the aim of contributing to new anti-inflammatory drug discovery.

Novel (-)-arctigenin derivatives inhibit signal transducer and activator of transcription 3 phosphorylation and P-glycoprotein function resensitizing multidrug resistant cancer cells in vitro and in vivo.

Multidrug resistance (MDR) is considered one of the significant chemotherapy failures of cancer patients and resulting in tumor recurrence and refractory cancer. The collateral sensitivity phenomenon is suggested as a potential alternative therapy for coring multidrug resistance in cancer. To achieve better effects and reduce toxicity, a polypharmacology strategy was applied. Arctigenin has been reported as a signal transducer and activator of transcription 3 (STAT3) inhibitor as an anticancer drug with low toxicity. However, the effective dosage of arctigenin was too high for re-sensitization in MDR cell lines. Therefore, we have designed and synthesized arctigenin derivatives and have evaluated their chemoreversal effects in KBvin and KB cells. The results conveyed that compounds 9, 10, and 12 displayed significant collateral sensitivity effects on MDR cancer cells, and the corresponding calculated RF values were 32, 174, and 133, respectively. In addition, compounds 9, 10, and 12 were identified to influence the activation of STAT3 and the function of P-glycoprotein in KBvin cells. Combining the active compounds (9, 10, and 12) with paclitaxel significantly inhibits MDR tumor growth in a zebrafish xenograft tumor model without toxicity. Thus, this study provided novel effective arctigenin derivatives and is considered a potential co-treatment with paclitaxel for treating MDR tumors.