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The growing knowledge of ferroptosis has suggested the role and therapeutic potential of ferroptosis in cancer, but has not been translated into effective therapy. Liver cancer, primarily hepatocellular carcinoma (HCC), is highly lethal with limited treatment options. LIFR is frequently downregulated in HCC. Here, by studying hepatocyte-specific and inducible Lifr-knockout mice, we show that loss of Lifr promotes liver tumorigenesis and confers resistance to drug-induced ferroptosis. Mechanistically, loss of LIFR activates NF-κB signaling through SHP1, leading to upregulation of the iron-sequestering cytokine LCN2, which depletes iron and renders insensitivity to ferroptosis inducers. Notably, an LCN2-neutralizing antibody enhances the ferroptosis-inducing and anticancer effects of sorafenib on HCC patient-derived xenograft tumors with low LIFR expression and high LCN2 expression. Thus, anti-LCN2 therapy is a promising way to improve liver cancer treatment by targeting ferroptosis.

To address the challenges of high error rates and poor generalization in current deep learning models for predicting lattice thermal conductivity (LTC), we introduce CrysGraphFormer, an innovative equivariant crystal graph transformer model tailored for this task. The model incorporates an improved multi-head self-attention mechanism and human-designed feature descriptors. By utilizing a message-passing mechanism to update node information, it introduces relative coordinate differences to represent crystal symmetry, avoiding the traditionally used complex and computationally expensive higher-order representations. We constructed a comprehensive dataset containing 5729 LTC data points (300 K), including 5477 materials from AFLOW, 112 MAX and MAB phase materials calculated using VASP, and 140 for half-Heusler alloys. Experimental results demonstrate that the CrysGraphFormer model achieves state-of-the-art performance in LTC prediction tasks and excels in predicting fundamental properties. The model offers good interpretability, providing insights from chemical and materials science perspectives. Furthermore, we validated the model's application potential in the field of thermoelectric materials by predicting the LTC of 59 thermoelectric materials and 55 ternary semiconductor materials, with results consistent with DFT calculations. Finally, the uncertainty of CrysGraphFormer was assessed using the Monte Carlo Dropout method. [ABSTRACT FROM AUTHOR]

PURPOSE: To describe the impact of fractionation scheme and tumor location on toxicities in stereotactic body radiation therapy (SBRT) for ≥5-cm non-small cell lung cancer (NSCLC), as part of a multi-institutional analysis. METHODS: Patients with primary ≥5-cm N0 M0 NSCLC who underwent ≤5-fraction SBRT were examined across multiple high-volume SBRT centers. Collected data included clinical/treatment parameters; toxicities were prospectively assessed at each institution according to the Common Terminology Criteria for Adverse Events. Patients treated daily were compared with those treated every other day (QOD)/other nondaily regimens. Stratification between central and peripheral tumors was also performed. RESULTS: Ninety-two patients from 12 institutions were evaluated (2004-2016), with median follow-up of 12 months. In total there were 23 (25%) and 6 (7%) grade ≥2 and grade ≥3 toxicities, respectively. Grades 2 and 3 pulmonary toxicities occurred in 9% and 4%, respectively; 1 patient treated daily experienced grade 5 radiation pneumonitis. Of the entire cohort, 46 patients underwent daily SBRT, and 46 received QOD (n=40)/other nondaily (n=6) regimens. Clinical/treatment parameters were similar between groups; the QOD/other group was more likely to receive 3-/4-fraction schemas. Patients treated QOD/other experienced significantly fewer grade ≥2 toxicities as compared with daily treatment (7% vs 43%, P.05). CONCLUSIONS: From this multi-institutional study, toxicity of SBRT for ≥5-cm lesions is acceptable, and daily treatment was associated with a higher rate of toxicities.

The development of modern information technology has recently put forward higher requirements for the ingenious design of electromagnetic wave absorbing (EMA) materials with a broad bandwidth at a low filling ratio. Herein, three-dimensional (3D) S-doped Co3O4 microflowers@reduced graphene oxide (S-Co3O4@RGO) aerogels are successfully prepared by interface and defect engineering with superior EMA capability. The 3D structure with a high surface-to-volume ratio can effectively avoid the agglomeration of Co3O4 and enhance the RGO–Co3O4 heterointerfaces to implement multiple reflection mechanisms. The synergistic effect of atom and phase cross-hybridization can improve defect-induced polarization centres and coherent interface-induced interface polarization. Meanwhile, the defects located at the interface have more charge transfer to enhance interface polarization than that at the interior, which is first proposed and demonstrated by density functional theory (DFT) calculations. Thus, the minimal reflection loss value can reach −56.7 dB (3.6 mm, 5.44 GHz) and the maximum effective absorption bandwidth is 8.48 GHz (ranging from 9.28 to 17.76 GHz) at a matching thickness of 2.3 mm with a filling ratio of 5 wt%. This work opens a new pathway to synthesize electromagnetic wave absorbents with synergistic defect and interface induced polarization loss, and has tremendous potential for EMA applications. [ABSTRACT FROM AUTHOR]

Byline: Yuan-Gui. Chen, An-Chuan. Li, Wen-Yao. Li, Miao-Yun. Huang, Xiao-Bo. Li, Ming-Qiu. Chen, Mutian. Zhang, Ben-Hua. Xu We highly appreciate your comments. It is well known that there are considerable [...]