A polo-like kinase 1 inhibitor enhances erastin sensitivity in head and neck squamous cell carcinoma cells in vitro.

BACKGROUND: Polo-like kinase 1 (PLK1) is a critical therapeutic target in the treatment of head and neck squamous cell carcinoma (HNSCC). The objective of this study was to investigate the therapeutic effect of the combination of BI 2536, a PLK1 inhibitor, and erastin, a ferroptosis inducer, in HNSCC. METHODS: The proliferation, invasion, and migration abilities of Tu177 and FaDu cells upon exposure to BI 2536 and erastin, used in combination or alone, were tested. Fe2+, glutathione (GSH), and malondialdehyde (MDA) detection kits were used to determine whether the addition of BI 2536 enhanced the accumulation of Fe2+ and MDA, along with the depletion of GSH. Quantitative real-time PCR, western blot analyses were performed to investigate whether BI 2536 further altered the mRNA and expression level of ferroptosis genes. Furthermore, si PLK1 was used to investigate whether targeting PLK1 gene promoted erastin-induced ferroptosis. RESULTS: The combination of BI 2536 and erastin exerted a stronger cytotoxicity than treatment with a single agent. Compared with erastin treatment alone, the combination of BI 2536 and erastin lowered the ability of tumor cells to self-clone, invade, and migrate. BI 2536 enhanced the accumulation of Fe2+ and MDA, and the depletion of GSH. BI 2536 increased erastin-induced changes in ferroptosis-related gene mRNA and expression. Importantly, targeting PKL1 enhanced the anti-cancer effect of erastin. CONCLUSION: BI 2536 enhanced the sensitivity of HNSCC cells to erastin, which provides a new perspective for cancer treatment.

Confounder balancing in adversarial domain adaptation for pre-trained large models fine-tuning.

The excellent generalization, contextual learning, and emergence abilities in the pre-trained large models (PLMs) handle specific tasks without direct training data, making them the better foundation models in the adversarial domain adaptation (ADA) methods to transfer knowledge learned from the source domain to target domains. However, existing ADA methods fail to account for the confounder properly, which is the root cause of the source data distribution that differs from the target domains. This study proposes a confounder balancing method in adversarial domain adaptation for PLMs fine-tuning (CadaFT), which includes a PLM as the foundation model for a feature extractor, a domain classifier and a confounder classifier, and they are jointly trained with an adversarial loss. This loss is designed to improve the domain-invariant representation learning by diluting the discrimination in the domain classifier. At the same time, the adversarial loss also balances the confounder distribution among source and unmeasured domains in training. Compared to newest ADA methods, CadaFT can correctly identify confounders in domain-invariant features, thereby eliminating the confounder biases in the extracted features from PLMs. The confounder classifier in CadaFT is designed as a plug-and-play and can be applied in the confounder measurable, unmeasurable, or partially measurable environments. Empirical results on natural language processing and computer vision downstream tasks show that CadaFT outperforms the newest GPT-4, LLaMA2, ViT and ADA methods.

C-H-activated Csp2-Csp3 diastereoselective gridization enables ultraviolet-emitting stereo-molecular nanohydrocarbons with mulitple H···H interactions.

Gridization is an emerging molecular integration technology that enables the creation of multifunctional organic semiconductors through precise linkages. While Friedel-Crafts gridization of fluorenols is potent, direct linkage among fluorene molecules poses a challenge. Herein, we report an achiral Pd-PPh3-cataylized diastereoselective (>99:1 d.r.) gridization based on the C-H-activation of fluorene to give dimeric and trimeric windmill-type nanogrids (DWGs and TWGs). These non-conjugated stereo-nanogrids showcase intramolecular multiple H…H interactions with a low field shift to 8.51 ppm and circularly polarized luminescence with high luminescent dissymmetry factors (|gPL | = 0.012). Significantly, the nondoped organic light-emitting diodes (OLEDs) utilizing cis-trans-TWG1 emitter present an ultraviolet electroluminescent peak at ~386 nm (CIE: 0.17, 0.04) with a maximum external quantum efficiency of 4.17%, marking the highest record among nondoped ultraviolet OLEDs based on hydrocarbon compounds and the pioneering ultraviolet OLEDs based on macrocycles. These nanohydrocarbon offer potential nanoscafflolds for ultraviolet light-emitting optoelectronic applications.