Design and synthesis of magnesium-modified copper oxide nanosheets as efficient electrocatalysts for CO2 reduction.

Electroreduction of carbon dioxide (CO2) to multiple carbon products plays a significant role in carbon neutrality and the production of valuable chemicals. Herein, we developed a magnesium-modified copper oxide nanosheet catalyst (Mg-CuO) using a post-impregnation method. Comprehensive elemental analysis demonstrated the effective incorporation of magnesium into CuO nanosheets, resulting in a noticeable alteration of the electron density of Cu atoms. Consequently, the Mg-CuO nanosheets exhibited an increased efficiency for CO2 electroreduction in comparison with the unmodified CuO nanosheets. The optimized Mg-CuO catalyst exhibited faradaic efficiencies of 46.33% for ethylene production and 62.64% for C2+ production at -1.3 V vs. reversible hydrogen electrode (RHE). DFT proved that the introduction of Mg species could increase the charge density of Cu and decrease the adsorption energy of *CO, which promoted C-C coupling and enhanced the selectivity of C2+ products. This study presents an effective way to adjust the electronic structure of common copper-based electrocatalysts and the corresponding interaction with *CO, resulting in an improved faradaic efficiency of C2+ products.

Successful treatment of hemophagocytic intravascular large B-cell lymphoma with CNS involvement with BTK inhibitor combined with rituximab and high-dose methotrexate.

This is a case of hemophagocytic intravascular large B-cell lymphoma (IVLBCL) with central nervous system (CNS) involvement. Although R-CHOP chemotherapy regimen has been shown significant improvement in survival rate. The prognosis and outcomes remain unsatisfactory, which is identified as outstanding challenges and need solutions. Gene and molecular profiling studies may provide new therapeutic strategies, especially the BCR/TLR/IL-1R/NF-κB signaling pathway in IVLBCL. Here, we treated the hemophagocytic IVLBCL CNS-involved patient with the Bruton tyrosine kinase inhibitor (BTKi) to block NF-κB pathway, and indicated that the second-generation BTKi zanubrutinib-based treatment was feasible and efficient.

Mass Production of Carbon Nanotube Transistor Biosensors for Point-of-Care Tests.

Low-dimensional semiconductor-based field-effect transistor (FET) biosensors are promising for label-free detection of biotargets while facing challenges in mass fabrication of devices and reliable reading of small signals. Here, we construct a reliable technology for mass production of semiconducting carbon nanotube (CNT) film and FET biosensors. High-uniformity randomly oriented CNT films were prepared through an improved immersion coating technique, and then, CNT FETs were fabricated with coefficient of performance variations within 6% on 4-in. wafers (within 9% interwafer) based on an industrial standard-level process. The CNT FET-based ion sensors demonstrated threshold voltage standard deviations within 5.1 mV at each ion concentration, enabling direct reading of the concentration information based on the drain current. By integrating bioprobes, we achieved detection of biosignals as low as 100 aM through a plug-and-play portable detection system. The reliable technology will contribute to commercial applications of CNT FET biosensors, especially in point-of-care tests.

Metal-Organic Framework with Dual Excitation Pathways as Efficient Bifunctional Catalyst for Photo-assisted Li-O2 Batteries.

Li-O2 batteries (LOBs) have sparked significant interest due to their fascinating high theoretical energy density. However, the large overpotential for the formation and oxidation of Li2O2 during charge and discharge process seriously hinders the further development and application of LOBs. In this work, metal-organic frameworks (MOFs) with different metal clusters (Fe, Ti, Zr) are successfully synthesized, and they are employed as the photoelectrodes for the photo-assisted LOBs. The special dual excitation pathways of Fe-MOF under illumination and the superior separation efficiency of photocarriers, which significantly enhance the activation of O2/Li2O2, improving the catalytic activity of oxygen reduction reaction and oxygen evolution reaction. Moreover, compared to traditional inorganic semiconductor crystals, Fe-MOF exhibits large specific surface area and excellent O2 adsorption ability. Therefore, the LOB with Fe-MOF as the cathode exhibits large specific capacity, ultralow charge/discharge overpotential of 0.22 V at 0.05 mA cm-2 and excellent stability of 195 cycles under illumination. This study provides an environmentally friendly and highly efficient photocatalyst for LOBs, and a new strategy for designing photoelectrodes.

Efficacy of percutaneous mechanical thrombus removal in acute lower extremity deep venous thrombosis.

BACKGROUND: Acute lower extremity deep venous thrombosis (LEDVT) is a common vascular emergency with significant morbidity risks, including post-thrombotic syndrome (PTS) and pulmonary embolism. Traditional treatments like catheter-directed thrombolysis (CDT) often result in variable success rates and complications. AIM: To investigate the therapeutic efficacy of percutaneous mechanical thrombus removal in acute LEDVT. METHODS: A retrospective analysis was performed to examine 58 hospitalised patients with acute LEDVT between August 2019 and August 2022. The patients were categorised into the percutaneous mechanical thrombectomy (PMT) group (n = 24) and CDT group (n = 32). The follow-up, safety and treatment outcomes were compared between the two groups. The main observational indexes were venous patency score, thrombus removal effect, complications, hospitalisation duration and PTS. RESULTS: The venous patency score was 9.04 ± 1.40 in the PMT group and 8.81 ± 1.60 in the CDT group, and the thrombus clearance rate was 100% in both groups. The complication rate was 8.33% in the PMT group and 34.84% in the CDT group, and the difference was statistically significant (P < 0.05). The average hospitalisation duration was 6.54 ± 2.48 days in the PMT group and 8.14 ± 3.56 days in the CDT group. The incidence of PTS was lower in the PMT group than in the CDT group; however, the difference was not statistically significant (P < 0.05). CONCLUSION: Compared with CDT, treatment of LEDVT via PMT was associated with a better thrombus clearance rate, clinical therapeutic effect and PTS prevention function, but the difference was not statistically significant. Moreover, PMT was associated with a reduced urokinase dosage, shortened hospitalisation duration and reduced incidence of complications, such as infections and small haemorrhages. These results indicate that PMT has substantial beneficial effects in the treatment of LEDVT.

RefAI: a GPT-powered retrieval-augmented generative tool for biomedical literature recommendation and summarization.

OBJECTIVES: Precise literature recommendation and summarization are crucial for biomedical professionals. While the latest iteration of generative pretrained transformer (GPT) incorporates 2 distinct modes-real-time search and pretrained model utilization-it encounters challenges in dealing with these tasks. Specifically, the real-time search can pinpoint some relevant articles but occasionally provides fabricated papers, whereas the pretrained model excels in generating well-structured summaries but struggles to cite specific sources. In response, this study introduces RefAI, an innovative retrieval-augmented generative tool designed to synergize the strengths of large language models (LLMs) while overcoming their limitations. MATERIALS AND METHODS: RefAI utilized PubMed for systematic literature retrieval, employed a novel multivariable algorithm for article recommendation, and leveraged GPT-4 turbo for summarization. Ten queries under 2 prevalent topics ("cancer immunotherapy and target therapy" and "LLMs in medicine") were chosen as use cases and 3 established counterparts (ChatGPT-4, ScholarAI, and Gemini) as our baselines. The evaluation was conducted by 10 domain experts through standard statistical analyses for performance comparison. RESULTS: The overall performance of RefAI surpassed that of the baselines across 5 evaluated dimensions-relevance and quality for literature recommendation, accuracy, comprehensiveness, and reference integration for summarization, with the majority exhibiting statistically significant improvements (P-values <.05). DISCUSSION: RefAI demonstrated substantial improvements in literature recommendation and summarization over existing tools, addressing issues like fabricated papers, metadata inaccuracies, restricted recommendations, and poor reference integration. CONCLUSION: By augmenting LLM with external resources and a novel ranking algorithm, RefAI is uniquely capable of recommending high-quality literature and generating well-structured summaries, holding the potential to meet the critical needs of biomedical professionals in navigating and synthesizing vast amounts of scientific literature.

Association of IL­6 and MMP­3 gene polymorphisms with adolescent idiopathic scoliosis: A systematic review and meta­analysis.

The pathogenesis of adolescent idiopathic scoliosis (AIS) remains unclear. It has been found that interleukin-6 (IL-6) rs1800795 locus and matrix metalloproteinase-3 (MMP-3) rs3025058 locus gene polymorphisms may be associated with AIS susceptibility, which has been controversial and needs to be further confirmed by updated meta-analysis. The aim of the present study was to investigate the association of MMP-3 rs3025058 and IL-6 rs1800795 single nucleotide polymorphisms (SNPs) with susceptibility to AIS. All relevant articles that met the criteria were retrieved and included, and the publication dates were limited from January 2005 to December 2023. The allele frequencies and different genotype frequencies of IL-6 rs1800795 and MMP-3 rs3025058 loci in each study were extracted and statistically analyzed by ReviewManager 5.4 software, and the odds ratio (OR) and 95% confidence interval (95% CI) of different genetic models were calculated. The results of the meta-analysis showed that there was no significant association between the gene polymorphism of IL-6 rs1800795 locus and the pathogenesis of AIS. The allele 5A and genotype 5A5A of MMP-3 rs3025058 SNP were associated with AIS susceptibility (5A vs. 6A, OR=1.18; 95% CI, 1.04-1.33; 5A5A vs. 6A6A, OR=1.65; 95% CI, 1.23-2.21; and 5A5A vs. 5A6A + 6A6A, OR=1.54; 95% CI, 1.19-1.99). Results of subgroup analysis revealed that the allele 5A and genotype 5A5A of MMP-3 rs3025058 SNP were associated with AIS susceptibility in the Caucasian population, and the susceptibility of AIS was associated with the genotype 5A5A of MMP-3 rs3025058 SNP in an Asian population. There was no significant association between the gene polymorphism of IL-6 rs1800795 locus and the pathogenesis of AIS, while the allele 5A of MMP-3 rs3025058 locus was associated with the susceptibility to AIS, especially in the Caucasian population.

Differential regulation of lung homeostasis and silicosis by the TAM receptors MerTk and Axl.

Introduction: TAM receptor-mediated efferocytosis plays an important function in immune regulation and may contribute to antigen tolerance in the lungs, a site with continuous cellular turnover and generation of apoptotic cells. Some studies have identified failures in efferocytosis as a common driver of inflammation and tissue destruction in lung diseases. Our study is the first to characterize the in vivo function of the TAM receptors, Axl and MerTk, in the innate immune cell compartment, cytokine and chemokine production, as well as the alveolar macrophage (AM) phenotype in different settings in the airways and lung parenchyma. Methods: We employed MerTk and Axl defective mice to induce acute silicosis by a single exposure to crystalline silica particles (20 mg/50 µL). Although both mRNA levels of Axl and MerTk receptors were constitutively expressed by lung cells and isolated AMs, we found that MerTk was critical for maintaining lung homeostasis, whereas Axl played a role in the regulation of silica-induced inflammation. Our findings imply that MerTk and Axl differently modulated inflammatory tone via AM and neutrophil recruitment, phenotype and function by flow cytometry, and TGF-ß and CXCL1 protein levels, respectively. Finally, Axl expression was upregulated in both MerTk-/- and WT AMs, confirming its importance during inflammation. Conclusion: This study provides strong evidence that MerTk and Axl are specialized to orchestrate apoptotic cell clearance across different circumstances and may have important implications for the understanding of pulmonary inflammatory disorders as well as for the development of new approaches to therapy.

Ketogenic Diet Alters the Epigenetic and Immune Landscape of Prostate Cancer to Overcome Resistance to Immune Checkpoint Blockade Therapy.

Resistance to immune checkpoint blockade (ICB) therapy represents a formidable clinical challenge limiting the efficacy of immunotherapy. In particular, prostate cancer poses a challenge for ICB therapy due to its immunosuppressive features. A ketogenic diet (KD) has been reported to enhance response to ICB therapy in some other cancer models. However, adverse effects associated with continuous KD were also observed, demanding better mechanistic understanding and optimized regimens for using KD as an immunotherapy sensitizer. In this study, we established a series of ICB-resistant prostate cancer cell lines and developed a highly effective strategy of combining anti-PD1 and anti-CTLA4 antibodies with histone deacetylase inhibitor (HDACi) vorinostat, a cyclic KD (CKD), or dietary supplementation of the ketone body ß-hydroxybutyrate (BHB), which is an endogenous HDACi. CKD and BHB supplementation each delayed prostate cancer tumor growth as monotherapy, and both BHB and adaptive immunity were required for the antitumor activity of CKD. Single-cell transcriptomic and proteomic profiling revealed that HDACi and ketogenesis enhanced ICB efficacy through both cancer cell-intrinsic mechanisms, including upregulation of MHC class I molecules, and -extrinsic mechanisms, such as CD8+ T-cell chemoattraction, M1/M2 macrophage rebalancing, monocyte differentiation toward antigen-presenting cells, and diminished neutrophil infiltration. Overall, these findings illuminate a potential clinical path of using HDACi and optimized KD regimens to enhance ICB therapy for prostate cancer. SIGNIFICANCE: Optimized cyclic ketogenic diet and 1,3-butanediol supplementation regimens enhance the efficacy of immune checkpoint blockade in prostate cancer through epigenetic and immune modulations, providing dietary interventions to sensitize tumors to immunotherapy.

Prompt Tuning in Biomedical Relation Extraction.

Biomedical relation extraction (RE) is critical in constructing high-quality knowledge graphs and databases as well as supporting many downstream text mining applications. This paper explores prompt tuning on biomedical RE and its few-shot scenarios, aiming to propose a simple yet effective model for this specific task. Prompt tuning reformulates natural language processing (NLP) downstream tasks into masked language problems by embedding specific text prompts into the original input, facilitating the adaption of pre-trained language models (PLMs) to better address these tasks. This study presents a customized prompt tuning model designed explicitly for biomedical RE, including its applicability in few-shot learning contexts. The model's performance was rigorously assessed using the chemical-protein relation (CHEMPROT) dataset from BioCreative VI and the drug-drug interaction (DDI) dataset from SemEval-2013, showcasing its superior performance over conventional fine-tuned PLMs across both datasets, encompassing few-shot scenarios. This observation underscores the effectiveness of prompt tuning in enhancing the capabilities of conventional PLMs, though the extent of enhancement may vary by specific model. Additionally, the model demonstrated a harmonious balance between simplicity and efficiency, matching state-of-the-art performance without needing external knowledge or extra computational resources. The pivotal contribution of our study is the development of a suitably designed prompt tuning model, highlighting prompt tuning's effectiveness in biomedical RE. It offers a robust, efficient approach to the field's challenges and represents a significant advancement in extracting complex relations from biomedical texts. Supplementary Information: The online version contains supplementary material available at 10.1007/s41666-024-00162-9.

Knockdown of TOP2A suppresses IL-17 signaling pathway and alleviates the progression of ulcerative colitis.

BACKGROUND: Ulcerative colitis (UC) is a chronic inflammatory disease of the colonic mucosa, with a gradually increasing incidence. Therefore, it is necessary to actively seek targets for the treatment of UC. METHODS: Common differentially expressed genes (DEGs) were screened from two microarray data sets related to UC. Protein-protein interaction network was constructed to find the hub genes. The UC mouse model and cell model were induced by dextran sulfate sodium (DSS). The pathological changes of colon tissue were observed by hematoxylin-eosin staining. Immunohistochemistry and immunofluorescence were performed to detect the expressions of Ki67 and Claudin-1. The performance of mice was observed by disease activity index (DAI). The effect of TOP2A on proliferation, inflammation, oxidative stress, and interleukin-17 (IL-17) signaling pathway in UC model was measured by cell counting kit-8, enzyme-linked immunosorbent assay, and western blot. RESULTS: Through bioinformatics analysis, 295 common DEGs were screened, and the hub gene TOP2A was selected. In UC model, there was obvious inflammatory cell infiltration in the colon and less goblet cells, while si-TOP2A lessened it. More Ki67 positive cells and less Claudin-1 positive cells were observed in UC model mice. Furthermore, knockdown of TOP2A increased the body weight and colon length of UC mice, while the DAI was decreased. Through in vivo and in vitro experiments, knockdown of TOP2A also inhibited inflammation and IL-17 signaling pathway, and promoted proliferation in DSS-induced NCM460 cells. CONCLUSION: Knockdown of TOP2A alleviated the progression of UC by suppressing inflammation and inhibited IL-17 signaling pathway.

Recharacterization of RSL3 reveals that the selenoproteome is a druggable target in colorectal cancer.

Ferroptosis is an iron-dependent, non-apoptotic form of cell death resulting from the accumulation of lipid peroxides. Colorectal cancer (CRC) accumulates high levels of intracellular iron and reactive oxygen species (ROS), thereby sensitizing cells to ferroptosis. The selenoprotein glutathione peroxidase (GPx4) is a key enzyme in the detoxification of lipid peroxides and can be inhibited by the compound (S)-RSL3 ([1S,3R]-RSL3). However, the stereoisomer (R)-RSL3 ([1R,3R]-RSL3), which does not inhibit GPx4, exhibits equipotent activity to (S)-RSL3 across a panel of CRC cell lines. Utilizing CRC cell lines with an inducible knockdown of GPx4, we demonstrate that (S)-RSL3 sensitivity does not align with GPx4 dependency. Subsequently, a biotinylated (S)-RSL3 was then synthesized to perform affinity purification-mass spectrometry (AP-MS), revealing that (S)-RSL3 acts as a pan-inhibitor of the selenoproteome, targeting both the glutathione and thioredoxin peroxidase systems as well as multiple additional selenoproteins. To investigate the therapeutic potential of broadly disrupting the selenoproteome as a therapeutic strategy in CRC, we employed further chemical and genetic approaches to disrupt selenoprotein function. The findings demonstrate that the selenoprotein inhibitor Auranofin can induce ferroptosis and/or oxidative cell death both in-vitro and in-vivo. Consistent with this data we observe that AlkBH8, a tRNA-selenocysteine methyltransferase required for the translational incorporation of selenocysteine, is essential for CRC growth. In summary, our research elucidates the complex mechanisms underlying ferroptosis in CRC and reveals that modulation of the selenoproteome provides multiple new therapeutic targets and opportunities in CRC.

Ensemble pretrained language models to extract biomedical knowledge from literature.

OBJECTIVES: The rapid expansion of biomedical literature necessitates automated techniques to discern relationships between biomedical concepts from extensive free text. Such techniques facilitate the development of detailed knowledge bases and highlight research deficiencies. The LitCoin Natural Language Processing (NLP) challenge, organized by the National Center for Advancing Translational Science, aims to evaluate such potential and provides a manually annotated corpus for methodology development and benchmarking. MATERIALS AND METHODS: For the named entity recognition (NER) task, we utilized ensemble learning to merge predictions from three domain-specific models, namely BioBERT, PubMedBERT, and BioM-ELECTRA, devised a rule-driven detection method for cell line and taxonomy names and annotated 70 more abstracts as additional corpus. We further finetuned the T0pp model, with 11 billion parameters, to boost the performance on relation extraction and leveraged entites' location information (eg, title, background) to enhance novelty prediction performance in relation extraction (RE). RESULTS: Our pioneering NLP system designed for this challenge secured first place in Phase I-NER and second place in Phase II-relation extraction and novelty prediction, outpacing over 200 teams. We tested OpenAI ChatGPT 3.5 and ChatGPT 4 in a Zero-Shot setting using the same test set, revealing that our finetuned model considerably surpasses these broad-spectrum large language models. DISCUSSION AND CONCLUSION: Our outcomes depict a robust NLP system excelling in NER and RE across various biomedical entities, emphasizing that task-specific models remain superior to generic large ones. Such insights are valuable for endeavors like knowledge graph development and hypothesis formulation in biomedical research.

AE-GPT: Using Large Language Models to extract adverse events from surveillance reports-A use case with influenza vaccine adverse events.

Though Vaccines are instrumental in global health, mitigating infectious diseases and pandemic outbreaks, they can occasionally lead to adverse events (AEs). Recently, Large Language Models (LLMs) have shown promise in effectively identifying and cataloging AEs within clinical reports. Utilizing data from the Vaccine Adverse Event Reporting System (VAERS) from 1990 to 2016, this study particularly focuses on AEs to evaluate LLMs' capability for AE extraction. A variety of prevalent LLMs, including GPT-2, GPT-3 variants, GPT-4, and Llama2, were evaluated using Influenza vaccine as a use case. The fine-tuned GPT 3.5 model (AE-GPT) stood out with a 0.704 averaged micro F1 score for strict match and 0.816 for relaxed match. The encouraging performance of the AE-GPT underscores LLMs' potential in processing medical data, indicating a significant stride towards advanced AE detection, thus presumably generalizable to other AE extraction tasks.

Anchoring Carbon Spheres on Titanium Dioxide Modified Commercial Polyethylene (PE) Separator to Suppress Lithium Dendrites for Lithium Metal Batteries.

Lithium dendrites are easily generated for excessively-solved lithium ions (Li+) inside the lithium metal batteries, which will lead serious safety issues. In this experiment, carbon spheres (CS) are successfully anchored on TiO2 (CS@TiO2) in the hydrothermal polymerization, which is filtrated on the commercial PE separator (CS@TiO2@PE). The negative charge in CS can suppress random diffusion of anions through electrostatic interactions. Density functional theory (DFT) calculations show that CS contributes to the desolvation of Li+, thereby increasing the migration rate of Li+. Furthermore, TiO2 exhibits high affinity to liquid electrolytes and acts as a physical barrier to lithium dendrite formation. CS@TiO2 is a combination of the advantages of CS and TiO2. As results, the Li+ transference number of the CS@TiO2@PE separator can be promoted to 0.63. The Li||Li cell with the CS@TiO2@PE separator exhibits a stable cycle performance for more than 600 h and lower polarization voltage (17 mV) at 1 mA cm-2. The coulombic efficiency (CE) of the Li||Cu cells employe the CS@TiO2@PE separator is 81.63% over 130 cycles. The discharge capacity of LiFePO4||Li cells based on the CS@TiO2@PE separator is 1.73 mAh (capacity retention = 91.53% after 260 cycles). Thus, the CS@TiO2 layer inhibits lithium dendrite formation.

Dynamic Prognosis Prediction for Patients on DAPT After Drug-Eluting Stent Implantation: Model Development and Validation.

BACKGROUND: The rapid evolution of artificial intelligence (AI) in conjunction with recent updates in dual antiplatelet therapy (DAPT) management guidelines emphasizes the necessity for innovative models to predict ischemic or bleeding events after drug-eluting stent implantation. Leveraging AI for dynamic prediction has the potential to revolutionize risk stratification and provide personalized decision support for DAPT management. METHODS AND RESULTS: We developed and validated a new AI-based pipeline using retrospective data of drug-eluting stent-treated patients, sourced from the Cerner Health Facts data set (n=98 236) and Optum's de-identified Clinformatics Data Mart Database (n=9978). The 36 months following drug-eluting stent implantation were designated as our primary forecasting interval, further segmented into 6 sequential prediction windows. We evaluated 5 distinct AI algorithms for their precision in predicting ischemic and bleeding risks. Model discriminative accuracy was assessed using the area under the receiver operating characteristic curve, among other metrics. The weighted light gradient boosting machine stood out as the preeminent model, thus earning its place as our AI-DAPT model. The AI-DAPT demonstrated peak accuracy in the 30 to 36 months window, charting an area under the receiver operating characteristic curve of 90% [95% CI, 88%-92%] for ischemia and 84% [95% CI, 82%-87%] for bleeding predictions. CONCLUSIONS: Our AI-DAPT excels in formulating iterative, refined dynamic predictions by assimilating ongoing updates from patients' clinical profiles, holding value as a novel smart clinical tool to facilitate optimal DAPT duration management with high accuracy and adaptability.

Preparation of Surface Dispersed WO3/BiVO4 Heterojunction Arrays and Their Photoelectrochemical Performance for Water Splitting.

In this work, a surface dispersed heterojunction of BiVO4-nanoparticle@WO3-nanoflake was successfully prepared by hydrothermal combined with solvothermal method. We optimized the morphology of the WO3 nanoflakes and BiVO4 nanoparticles by controlling the synthesis conditions to get the uniform BiVO4 loaded on the surface of WO3 arrays. The phase composition and morphology evolution with different reaction precursors were investigated in detail. When used as photoanodes, the WO3/BiVO4 composite exhibits superior activity with photocurrent at 3.53 mA cm-2 for photoelectrochemical (PEC) water oxidation, which is twice that of pure WO3 photoanode. The superior surface dispersion structure of the BiVO4-nanoparticle@WO3-nanoflake heterojunction ensures a large effective heterojunction area and relieves the interfacial hole accumulation at the same time, which contributes to the improved photocurrents together with the stability of the WO3/BiVO4 photoanodes.

Study on the radiotherapy effect and serum neutral granulocyte lymphocyte ratio and inflammatory factor expression of nasopharyngeal carcinoma.

Purpose: To compare target area delineation schemes in intensity-modulated radiotherapy (IMRT) effect on patients with locally advanced nasopharyngeal carcinoma (NPC). Methods: A total of 88 NPC patients received IMRT and were assigned into control group (n = 44) and observation group (n = 44) based on MRI and CT imaging. In the control group, the treatment range was determined as the clinical target volume (CTV) as the gross tumor volume (GTV) + 5 mm. In the observation group, high-risk target areas CTVp1 was GTVp + 5 mm, lymphatic drainage area CTVn1 was GTVn + 5 mm, medium-risk CTVp2 was CTVp1 + 5 mm margin + the whole nasopharyngeal area, CTVn2 was CTVn1 + 5 mm. Radiotherapy treatment course was 6-8 weeks, four times a week. Results: The observation group had higher total effective rate, with fewer complications. Neutrophil lymphocyte ratio (NLR), interleukin (IL)-6, and tumor necrosis factor (TNF)-α levels were lower after radiotherapy in both groups compared to before radiotherapy, with the observation group demonstrating lower levels than the control group. The effective group exhibited lower serum NLR, IL-6, and TNF-α compared to the non-effective group. T stage, target location, serum NLR, IL-6, and TNF-α were risk factors for the effect of radiotherapy. Conclusions: Serum NLR, IL-6, and TNF-α have predictive significance for radiotherapy effect.

Construction and validation of a novel tumor necrosis factor-related apoptosis-inducing ligand mutant MuR5S4-TR.

AIM: Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) can selectively kill tumor cells but has no significant effect on normal cells. However, the use of TRAIL is limited for resistance by more than 50% of the tumor cell lines. It's very important to develop a more efficient form of TRAIL for cancer treatment. METHODS: The N-terminal in soluble fragments (114-281aa) of TRAIL was redesigned to construct a novel TRAIL mutant-MuR5S4-TR. The Cell Counting Kit-8 method to explore the antitumor effects. The potential mechanisms were also explored. RESULTS: Novel TRAIL mutant with cell-penetrating peptides (CPP) like and Second mitochondria-derived activator of caspases (Smac) like structure-MuR5S4-TR was successfully constructed. The prokaryotic expression system was successfully built, and the MuR5S4-TR was purified and reconfirmed by western blot. MuR5S4-TR could enhance the antitumor effects of TRAIL in most of the cancer cell lines significantly, NCI-H460 lung cancer cell line, for instance. After MuR5S4-TR treatment, the expressions of death receptor 4 (DR4), DR5, Caspase-8, and cleaved Caspase-3 were remarkably increased, however, there was no significant difference in X-linked inhibitor of apoptosis expression. CONCLUSION: We constructed a novel TRAIL mutant with CPP-like and Smac-like structure-MuR5S4-TR. The MuR5S4-TR showed significantly stronger antitumor effects than TRAIL in many tumor cell lines. The MuR5S4-TR showed strong antitumor effects both in vitro and in vivo. This preliminary study implies that MuR5S4-TR may be a more efficient form of TRAIL for cancer therapy.

Sensitization of cancer cells to ferroptosis coincident with cell cycle arrest.

Ferroptosis is a non-apoptotic form of cell death that can be triggered by inhibiting the system xc- cystine/glutamate antiporter or the phospholipid hydroperoxidase glutathione peroxidase 4 (GPX4). We have investigated how cell cycle arrest caused by stabilization of p53 or inhibition of cyclin-dependent kinase 4/6 (CDK4/6) impacts ferroptosis sensitivity. Here, we show that cell cycle arrest can enhance sensitivity to ferroptosis induced by covalent GPX4 inhibitors (GPX4i) but not system xc- inhibitors. Greater sensitivity to GPX4i is associated with increased levels of oxidizable polyunsaturated fatty acid-containing phospholipids (PUFA-PLs). Higher PUFA-PL abundance upon cell cycle arrest involves reduced expression of membrane-bound O-acyltransferase domain-containing 1 (MBOAT1) and epithelial membrane protein 2 (EMP2). A candidate orally bioavailable GPX4 inhibitor increases lipid peroxidation and shrinks tumor volumes when combined with a CDK4/6 inhibitor. Thus, cell cycle arrest may make certain cancer cells more susceptible to ferroptosis in vivo.