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Targeting ferroptosis, an iron-dependent form of regulated cell death triggered by the lethal overload of lipid peroxides, in cancer therapy is impeded by our limited understanding of the intersection of tumour’s metabolic feature and ferroptosis vulnerability. In the present study, arginine is identified as a ferroptotic promoter using a metabolites library. This effect is mainly achieved through arginine’s conversion to polyamines, which exerts their potent ferroptosis-promoting property in an H 2 O 2 -dependent manner. Notably, the expression of ornithine decarboxylase 1 (ODC1), the critical enzyme catalysing polyamine synthesis, is significantly activated by the ferroptosis signal——iron overload——through WNT/MYC signalling, as well as the subsequent elevated polyamine synthesis, thus forming a ferroptosis-iron overload-WNT/MYC-ODC1-polyamine-H 2 O 2 positive feedback loop that amplifies ferroptosis. Meanwhile, we notice that ferroptotic cells release enhanced polyamine-containing extracellular vesicles into the microenvironment, thereby further sensitizing neighbouring cells to ferroptosis and accelerating the “spread” of ferroptosis in the tumour region. Besides, polyamine supplementation also sensitizes cancer cells or xenograft tumours to radiotherapy or chemotherapy through inducing ferroptosis. Considering that cancer cells are often characterized by elevated intracellular polyamine pools, our results indicate that polyamine metabolism exposes a targetable vulnerability to ferroptosis and represents an exciting opportunity for therapeutic strategies for cancer. Ferroptosis plays an important role in response to radiotherapy and chemotherapy, however, the sensitivity of cancer cell to ferroptosis varies. Here, the authors show that ODC1-mediated polyamine synthesis induces ferroptosis and demonstrate the potential of targeting this axis by combining polyamine supplements with radiotherapy or chemotherapy in preclinical lung cancer models.

This study used the Surveillance, Epidemiology, and End Results (SEER) data to investigate the changes in incidence, treatment, and survival of lung cancer from 1973 to 2015. The clinical and epidemiological data of patients with lung cancer were obtained from the SEER database. Joinpoint regression models were used to estimate the rate changes in lung cancer related to incidence, treatment, and survival. From 1973 to 2015, the average incidence of lung cancer was 59.0/100,000 person-years. The incidence increased initially, reached a peak in 1992, and then gradually decreased. A higher incidence rate was observed in males than in females and in black patients than in other racial groups. Since 1985, adenocarcinoma became the most prevalent histopathological type. The surgical rate for lung cancer was about 25%, and treatment with chemotherapy showed an increasing trend, while the radiotherapy rate was in downward trend. The surgical rate for non-small-cell lung cancer (NSCLC) was higher than that for small cell lung cancer (SCLC), while chemotherapy for SCLC far exceeded that for NSCLC. Treatment with chemotherapy and radiotherapy for advanced stage had higher rate than early stage. The 5-year relative survival rate of lung cancer increased with time, but <21%. In the past four decades, the lung cancer incidence increased initially and then gradually decreased. Surgical rate experienced a fluctuant reduction, while the chemotherapy rate was in upward trend. The 5-year relative survival rate increased with years, but was still low.

Background Lung cancer is one of the most common tumors in the world, and metastasis is one of the major causes of tumor-related death in lung cancer patients. Tumor-associated macrophages (TAMs) are a major component of the tumor microenvironment (TME) and are frequently associated with tumor metastasis in human cancers. However, the regulatory mechanisms of TAMs in lung cancer metastasis remain unclear. Methods Single-cell sequencing analysis of lung cancer and normal tissues from public databases and from 14 patients who underwent surgery at Zhongshan Hospital was performed. In vitro co-culture experiments were performed to evaluate the effects of TAMs on lung cancer migration and invasion. Changes in the expression of IL-6, STAT3, C/EBPΒ, and EMT pathway were verified using RT-qPCR, western blotting, and immunofluorescence. Dual luciferase reporter assays and ChIP were used to reveal potential regulatory sites on the transcription factor sets. In addition, the effects of TAMs on lung cancer progression and metastasis were confirmed by in vivo models. Results TAM infiltration is associated with tumor progression and poor prognosis. IL-6 secreted by TAMs can activate the JAK2/STAT3 pathway through autocrine secretion, and STAT3 acts as a transcription factor to activate the expression of C/EBPβ, which further promotes the transcription and expression of IL-6, forming positive feedback loops for IL6-STAT3-C/EBPβ-IL6 in TAMs. IL-6 secreted by TAMs promotes lung cancer progression and metastasis in vivo and in vitro by activating the EMT pathway, which can be attenuated by the use of JAK2/STAT3 pathway inhibitors or IL-6 monoclonal antibodies. Conclusions Our data suggest that TAMs promote IL-6 expression by forming an IL6-STAT3-C/EBPβ-IL6 positive feedback loop. Released IL-6 can induce the EMT pathway in lung cancer to enhance migration, invasion, and metastasis. The use of IL-6-neutralizing antibody can partially counteract the promotion of LUAD by TAMs. A novel mechanism of macrophage-promoted tumor progression was revealed, and the IL6-STAT3-C/EBPβ-IL6 signaling cascade may be a potential therapeutic target against lung cancer. Graphical Abstract IL-6 secreted by TAM acts on itself to promote STAT3 phosphorylation, and pSTAT3 transfers into the nucleus, promotes the expression of C/EBPβ. C/EBPβ is able to further promote IL-6 expression, which forms positive feedback for IL-6 secretion. IL-6 secreted by TAMs acts on lung cancer to promote their metastasis through activation of EMT.

Background Most cancer cells have fundamentally different metabolic characteristics, particularly much higher glycolysis rates than normal tissues, which support the increased demand for biosynthesis and promote tumor progression. We found that transforming growth factor (TGF)-β plays a dual function in regulating glycolysis and cell proliferation in non-small cell lung cancer. Methods We used the PET/MRI imaging system to observe the glucose metabolism of subcutaneous tumors in nude mice. Energy metabolism of non-small cell lung cancer cell lines detected by the Seahorse XFe96 cell outflow analyzer. Co-immunoprecipitation assays were used to detect the binding of Smads and HIF-1α. Western blotting and qRT-PCR were used to detect the regulatory effects of TGF-β and HIF-1α on c-MYC, PKM1/2, and cell cycle-related genes. Results We discovered that TGF-β could inhibit glycolysis under normoxia while significantly promoting tumor cells’ glycolysis under hypoxia in vitro and in vivo . The binding of hypoxia-inducible factor (HIF)-1α to the MH2 domain of phosphorylated Smad3 switched TGF-β function to glycolysis by changing Smad partners under hypoxia. The Smad-p107-E2F4/5 complex that initially inhibited c-Myc expression was transformed into a Smad-HIF-1α complex that promoted the expression of c-Myc. The increased expression of c-Myc promoted alternative splicing of PKM to PKM2, resulting in the metabolic reprogramming of tumor cells. In addition, the TGF-β/Smad signal lost its effect on cell cycle regulatory protein p15/p21. Furthermore, high expression of c-Myc inhibited p15/p21 and promoted the proliferation of tumor cells under hypoxia. Conclusions Our results indicated that HIF-1α functions as a critical factor in the dual role of TGF-β in tumor cells, and may be used as a biomarker or therapeutic target for TGF-β mediated cancer progression.

The localization of outdoor acoustic sources has attracted attention in wireless sensor networks. In this paper, the steered response power (SRP) localization of band-pass signal associated with steering time delay uncertainty and coarser spatial grids is considered. We propose a modified SRP-based source localization method for enhancing the localization robustness in outdoor scenarios. In particular, we derive a sufficient condition dependent on the generalized cross-correlation (GCC) waveform function for robust on-grid source localization and show that the SRP function with GCCs satisfying this condition can suppress the disturbances induced by the grid distance and the uncertain steering time delays. Then a GCC refinement procedure for band-pass GCCs is designed, which uses complex wavelet functions in multiple sub-bands to filter the GCCs and averages the envelopes of the filtered GCCs as the equivalent GCC to match the sufficient condition. Simulation results and field experiments demonstrate the excellent performance of the proposed method against the existing SRP-based methods.

The Pt-chitosan-TiO2 charge transfer (CT) complex was synthesized via the sol-gel and impregnation method. The synthesized photocatalysts were thoroughly characterized, and their photocatalytic activity were evaluated toward H2 production through water reduction under visible-light irradiation. The effect of the preparation conditions of the photocatalysts (the degree of deacetylation of chitosan, addition amount of chitosan, and calcination temperature) on the photocatalytic activity was discussed. The optimal Pt-10%DD75-T200 showed a H2 generation rate of 280.4 μmol within 3 h. The remarkable visible-light photocatalytic activity of Pt-chitosan-TiO2 was due to the CT complex formation between chitosan and TiO2, which extended the visible-light absorption and induced the ligand-to-metal charge transfer (LMCT). The photocatalytic mechanism of Pt-chitosan-TiO2 was also investigated. This paper outlines a new and facile pathway for designing novel visible-light-driven photocatalysts that are based on TiO2 modified by polysaccharide biomass wastes that are widely found in nature.

Gamma-ray spectroscopy is essential in nuclear science, enabling the identification of radioactive materials through energy spectrum analysis. However, high count rates lead to pile-up effects, resulting in spectral distortions that hinder accurate isotope identification and activity estimation. This phenomenon highlights the need for automated and precise approaches to pile-up correction. We propose a novel deep learning (DL) framework plugging count rate information of pile-up signals with a 2D attention U-Net for energy spectrum recovery. The input to the model is an Energy–Duration matrix constructed from preprocessed pulse signals. Temporal and spatial features are jointly extracted, with count rate information embedded to enhance robustness under high count rate conditions. Training data were generated using an open-source simulator based on a public gamma spectrum database. The model’s performance was evaluated using Kullback–Leibler (KL) divergence, Mean Squared Error (MSE) Energy Resolution (ER), and Full Width at Half Maximum (FWHM). Results indicate that the proposed framework effectively predicts accurate spectra, minimizing errors even under severe pile-up effects. This work provides a robust framework for addressing pile-up effects in gamma-ray spectroscopy, presenting a practical solution for automated, high-accuracy spectrum estimation. The integration of temporal and spatial learning techniques offers promising prospects for advancing high-activity nuclear analysis applications.

Background Health literacy is defined as the cognitive and social skills that determine the motivation and ability of individuals to gain access to, understand and use information in ways that promote and maintain good health. A Health Literacy Questionnaire (HLQ) is a toolkit with good reliability and validity. Accordingly, this study administered HLQ among older adults in China to examine its factor structure, reliability, homogeneity, and discriminant validity for use in understanding better the health literacy of older adults and determining corresponding measures. Methods Psychometric properties were examined based on the data collected via face-to-face interviews ( N  = 343). Tests included the difficulty level, composite scale reliability, confirmatory factor analysis (CFA), and Bayesian structural equation modeling (BSEM). Results The easiest scale to obtain a high score was “Social support for health” and the hardest, “Navigating the health care system” and “Appraisal of health information.” Two one-factor models fitted well with no correlated residuals allowed. After model modification, the CFA fit statistics of the other seven scales were good. All HLQ scales were found to be homogenous, with a composite reliability ranging from 0.74 to 0.85. The nine-factor Bayesian structural equation model fitted the data well (Posterior-Predictive-P value = 0.670; 95% Confidence Interval for the difference between the observed and replicated Chi-square values = − 163.320, 102.750). Conclusions The Chinese version of the HLQ has strong construct and content validity and high composite reliability when applied to older adults in Changsha City, China. Therefore, the nine-scale HLQ can now be administered to Chinese older adults, thereby providing a powerful approach to understanding the multidimensional area of health literacy.

Introduction This study aimed to compare the Forgotten Joint Score-12(FJS) outcomes and the minimum clinically important difference (MCID) of the FJS after high tibial osteotomy (HTO), unicompartmental knee arthroplasty (UKA), and total knee arthroplasty (TKA) with short-term follow-up (at least 2 years). Another objective of the study is to investigate the factors influencing FJS. It is hypothesized that there are differences in FJS outcomes among the three procedures. Methods Patients who underwent HTO, UKA, and TKA from January 2016 to December 2020 and were followed up for a minimum of 2 years were included in the study. The FJS were analyses from a cohort of people who submitted data to two years. The preoperative and postoperative clinical outcomes were compared and evaluated the patient-related factor. The FJS scores were predicted using multiple linear regression analysis. Additionally, Patient's Joint Perception (PJP) questions were used as anchors to determine the achievement of the forgotten joint, and FJS MCID were calculated using the receiver operating characteristic curve (ROC). Results Three hundred eighty-nine patients were included in the final study, and there were 111 patients in HTO groups,128patients in UKA groups, and 150 patients in TKA groups. The mean follow-up was 47.0 months. There was a significant difference in the total FJS, between the HTO, UKA, and TKA groups (FJS:59.38 ± 7.25, 66.69 ± 7.44 and 56.90 ± 6.85, p  < 0.001. We found the MCID of the FJS of HTO, UKA, and TKA were 63.54, 69.79, and 61.45, respectively. In multiple linear regression, younger age, and higher FS were significant predictors of better FJS. Conclusion Medial UKA demonstrated lower patient awareness in comparison to HTO and TKA, as assessed by the FJS. Younger age and higher FS were identified as significant predictors of improved FJS, providing valuable guidance for surgical decision-making.

Background Lung adenocarcinoma (LUAD) is a high-risk malignancy. Telomeres- (TRGs) and aging-related genes (ARGs) play an important role in cancer progression and prognosis. This study aimed to develop a novel prognostic model combined TRGs and ARGs signatures to predict the prognosis of patients with LUAD. Methods LUAD patient’s sample data and clinical data were obtained from public databases. The prognostic model was constructed and evaluated using the least absolute shrinkage and selection operator (LASSO), multivariate Cox analysis, time-dependent receiver operating characteristic (ROC), and Kaplan-Meier (K-M) analysis. Immune cell infiltration levels were assessed using single-sample gene set enrichment analysis (ssGSEA). Antitumor drugs with significant correlations between drug sensitivity and the expression of prognostic genes were identified using the CellMiner database. The distribution and expression levels of prognostic genes in immune cells were subsequently analyzed based on the TISCH database. Results This study identified eight characteristic genes that are significantly associated with LUAD prognosis and could serve as independent prognostic factors, with the low-risk group demonstrating a more favorable outcome. Additionally, a comprehensive nomogram was developed, showing a high degree of prognostic predictive value. The results from ssGSEA indicated that the low-risk group had higher immune cell infiltration. Ultimately, our findings revealed that the high-risk group exhibited heightened sensitivity to the Linsitinib, whereas the low-risk group demonstrated enhanced sensitivity to the OSI-027 drug. Conclusion The risk score exhibited robust prognostic capabilities, offering novel insights for assessing immunotherapy. This will provide a new direction to achieve personalized and precise treatment of LUAD in the future.