Recent Advances in the Development of Pyrazole Derivatives as Anticancer Agents

Pyrazole derivatives, as a class of heterocyclic compounds, possess unique chemical structures that confer them with a broad spectrum of pharmacological activities. They have been extensively explored for designing potent and selective anticancer agents. In recent years, numerous pyrazole derivatives have been synthesized and evaluated for their anticancer potential against various cancer cell lines. Structure-activity relationship studies have shown that appropriate substitution on different positions of the pyrazole ring can significantly enhance anticancer efficacy and tumor selectivity. It is noteworthy that many pyrazole derivatives have demonstrated multiple mechanisms of anticancer action by interacting with various targets including tubulin, EGFR, CDK, BTK, and DNA. Therefore, this review summarizes the current understanding on the structural features of pyrazole derivatives and their structure-activity relationships with different targets, aiming to facilitate the development of potential pyrazole-based anticancer drugs. We focus on the latest research advances in anticancer activities of pyrazole compounds reported from 2018 to present.

Modeling human anti-pig xenoimmune responses in a pig artery tissue grafted humanized mouse model

BACKGROUND

Blood vessels that contain endothelial cells (ECs) on the surface are in direct contact with host blood and are the first target of xenograft rejection. Currently, our understanding of human anti-pig vessel immune responses is primarily based on in vitro assays using pig ECs. Therefore, it is necessary to develop an animal model that permits in vivo study of human immunological rejection of pig vessels.

METHODS

Pig artery tissues (PAT) were transplanted into human immune system (HIS) mice or immunodeficient NSG mice (as controls). Intragraft human immune cell infiltration and antibody deposition were quantified using histology and immunohistochemistry. Donor antigen-specific immune responses were quantified using a mixed lymphocyte reaction and a complement-dependent killing assay.

RESULTS

Pig CD31+ ECs were detected and increased 2-fold from weeks 3 to 5 in PAT xenografts from immunodeficient NSG mice. However, compared with NSG mice, PAT xenografts in HIS mice had significantly lower numbers of porcine CD31+ ECs and showed a marked reduction from week 3 to week 5. PAT xenograft rejection in HIS mice is associated with intensive infiltration of human immune cells, deposition of human IgM and IgG antibodies, and the formation of a tertiary lymphoid structure. Robust donor pig antigen-specific human T cells and antibody responses were detected in PAT-transplanted HIS mice.

CONCLUSION

We have developed a humanized mouse model to evaluate human anti-pig xenoimmune responses by PAT transplantation in vivo. This model is expected to facilitate the refinement of pig gene-editing strategies (the expression on EC surface) and the testing of local immunosuppressive strategies for clinical pig organ xenotransplantation.

CSL-CTEA: a systematic method for evaluating novel intelligent cognitive assessment tools

With the intensification of global population aging, the incidence of cognitive disorders such as dementia continues to rise. The Mini-Mental State Examination (MMSE) and other alternative tools can help doctors detect subtle changes in cognitive function at an early stage. These assessment tools can make a diagnosis before symptoms become severe, providing opportunities for early intervention, which is crucial for delaying disease progression and improving the quality of life of patients. However, traditional cognitive assessment methods are overly complex and affected by various factors. With the development of artificial intelligence technology, many new assessment tools are constantly being developed and improved. How to evaluate the effectiveness of intelligent electronic cognitive assessment tools is particularly important. We have proposed the Correlation and Supervised Learning-based Cognitive Tool Effectiveness Assessment Method (CSL-CTEA) to evaluate the effectiveness of intelligent electronic cognitive assessment tools, including: (1) experimental design and data collection based on traditional scales and intelligent electronic assessment tools, (2) consistency and correlation tests; (3) accuracy analysis of assessment results based on supervised learning. We used CSL-CTEA to explore the effectiveness of a certain electronic assessment. This intelligent electronic cognitive assessment tool includes voice tests, orientation tests, and picture recognition tests to assess cognitive abilities from multiple perspectives. The results show that the electronic assessment is in good agreement with traditional cognitive assessment methods. The various indicators of the electronic assessment can explain the changes in MMSE scores to some extent. The study also found that the electronic assessment performs well in determining whether the subject is at cognitive risk. To some extent, the electronic assessment can replace traditional cognitive assessment methods such as MMSE to help people judge whether they are at risk of cognitive decline.

Turán type inequalities for generalized Mittag-Leffler function

In this paper, we show several Turán type inequalities for a generalized Mittag-Leffler function with four parameters via the [Formula: see text]-gamma function.

Predicting combinations of drugs by exploiting graph embedding of heterogeneous networks

BACKGROUND

Drug combination, offering an insight into the increased therapeutic efficacy and reduced toxicity, plays an essential role in the therapy of many complex diseases. Although significant efforts have been devoted to the identification of drugs, the identification of drug combination is still a challenge. The current algorithms assume that the independence of feature selection and drug prediction procedures, which may result in an undesirable performance.

RESULTS

To address this issue, we develop a novel Semi-supervised Heterogeneous Network Embedding algorithm (called SeHNE) to predict the combination patterns of drugs by exploiting the graph embedding. Specifically, the ATC similarity of drugs, drug-target, and protein-protein interaction networks are integrated to construct the heterogeneous networks. Then, SeHNE jointly learns drug features by exploiting the topological structure of heterogeneous networks and predicting drug combination. One distinct advantage of SeHNE is that features of drugs are extracted under the guidance of classification, which improves the quality of features, thereby enhancing the performance of prediction of drugs. Experimental results demonstrate that the proposed algorithm is more accurate than state-of-the-art methods on various data, implying that the joint learning is promising for the identification of drug combination.

CONCLUSIONS

The proposed model and algorithm provide an effective strategy for the prediction of combinatorial patterns of drugs, implying that the graph-based drug prediction is promising for the discovery of drugs.

Two Novel Diterpenoid Alkaloids from Aconitum Pendulum

Two previously uncharacterized compounds, an aconitine-type C19-diterpenoid alkaloid (1) and a napelline-type diterpenoid alkaloid C20-diterpenoid alkaloid (2), as well as ten known compounds (3-12), were isolated from Aconitum pendulum. Their structures were elucidated based on spectroscopic data, including 1D and 2D NMR, IR, HR-ESI-MS, and single-crystal X-ray diffraction analysis. The anti-insecticidal activities of these compounds were evaluated by contact toxicity tests against two-spotted spider mites, and compounds 1, 2, and 9 showed moderate contact toxicity, with LC50 values of 0.86±0.09, 0.95±0.23, and 0.89±0.19 mg/mL, respectively. This study highlights the potential use of diterpenoid alkaloids as natural plant-derived pesticides for the management of plant pests.

Mitigation of Anti-Drug Antibody Production for Augmenting Anticancer Efficacy of Therapeutic Protein via Co-Injection of Nano-Rapamycin

The induction of anti-drug antibody (ADA) is a formidable challenge for protein-based therapy. Trichosanthin (TCS) as a class of ribosome-inactivating proteins is widely studied in tumor treatment. However, the immunogenicity can induce the formation of ADA, which can cause hypersensitivity reactions and neutralize the efficacy of TCS, thus limiting its clinical application in cancer therapy. Here, a promising solution to this issue is presented by co-administration of the rapamycin nanoparticles and TCS. PEGylated rapamycin amphiphilic molecule is designed and synthesized as a prodrug and a delivery carrier, which can self-assemble into a nanoparticle system with encapsulation of free rapamycin, a hydrophobic drug. It is found that co-injection of the PEGylated rapamycin nanoparticles and TCS could mitigate the formation of anti-TCS antibody via inducing durable immunological tolerance. Importantly, the combination of TCS and the rapamycin nanoparticles has an enhanced effect on inhibit the growth of breast cancer. This work provides a promising approach for protein toxin-based anticancer therapy and for promoting the clinical translation.

Cobalt-Catalyzed Enantioselective Hydrotrifluoromethoxylation of Aromatic Alkenes

The construction of optically pure benzyl trifluoromethoxy (OCF3) compounds continues to present challenges due to limited enantioselectivity-control or the necessity for OCF3-containing substrates in the only two previous reports. Herein, we have developed a salen-Co-catalyzed enantioselective hydrotrifluoromethoxylation reaction involving aromatic alkenes and trifluoromethyl arylsulfonate (TFMS). This method effectively produces a range of chiral benzyl trifluoromethoxy compounds with enantiomeric excesses ranging from 75% to 99%.

An inequality for generalized complete elliptic integral

In this paper, we show an elegant inequality involving the ratio of generalized complete elliptic integrals of the first kind and generalize an interesting result of Alzer.