Ag-CeO2 Based on Electrochemical Sensor for High-Efficient On-Site Detection of Nitrite in Aquaculture Water and Beverages.

Nitrite is one of the most common nitrogenous compounds, which is not only an important indicator of aquaculture water but also widely used as a food additive. Its potential toxicity poses a huge threat to aquatic products and human health. Therefore, it is important to develop a convenient and rapid sensor for the high-efficient onsite detection of nitrite. In this work, a novel electrochemical sensor was developed for the qualitative and quantitative analysis of nitrite. The developed nitrite electrochemical detection system is easily applied in onsite detection. The electrochemical working electrode was constructed based on the combination of Ag-CeO2 and conductive carbon paste (CPE) with excellent electrocatalysis activity and rapid electron transfer ability. By the application of the developed system and under the optimal conditions, the linear range was from 40.0 µM to 500.0 µM, and the detection limit was reduced to 4.3 µM. The recovery was between 92.1% and 108.1%, and the relative standard deviations (RSDs) were 0.49%~9.31%. The sensor exhibited superior reproducibility, high stability sensitivity, and anti-interference ability, confirming its effectiveness for nitrite analysis. Finally, the developed electrochemical sensor was successfully applied to detect nitrite in beverages and aquaculture water samples, indicating that this approach has great potential in onsite food testing and environmental monitoring.

BrainMass: Advancing Brain Network Analysis for Diagnosis with Large-scale Self-Supervised Learning.

Foundation models pretrained on large-scale datasets via self-supervised learning demonstrate exceptional versatility across various tasks. Due to the heterogeneity and hard-to-collect medical data, this approach is especially beneficial for medical image analysis and neuroscience research, as it streamlines broad downstream tasks without the need for numerous costly annotations. However, there has been limited investigation into brain network foundation models, limiting their adaptability and generalizability for broad neuroscience studies. In this study, we aim to bridge this gap. In particular, (1) we curated a comprehensive dataset by collating images from 30 datasets, which comprises 70,781 samples of 46,686 participants. Moreover, we introduce pseudo-functional connectivity (pFC) to further generates millions of augmented brain networks by randomly dropping certain timepoints of the BOLD signal. (2) We propose the BrainMass framework for brain network self-supervised learning via mask modeling and feature alignment. BrainMass employs Mask-ROI Modeling (MRM) to bolster intra-network dependencies and regional specificity. Furthermore, Latent Representation Alignment (LRA) module is utilized to regularize augmented brain networks of the same participant with similar topological properties to yield similar latent representations by aligning their latent embeddings. Extensive experiments on eight internal tasks and seven external brain disorder diagnosis tasks show BrainMass's superior performance, highlighting its significant generalizability and adaptability. Nonetheless, BrainMass demonstrates powerful few/zero-shot learning abilities and exhibits meaningful interpretation to various diseases, showcasing its potential use for clinical applications.

Reactivation of prior responses drives serial dependence and stabilizes working memory representations.

Serial dependence has shown seemingly contradictory effects on visual perception and working memory. While serial dependence promotes perpetual and mnemonic stability, it biases behavioral reports towards prior information. The neural mechanisms that drive both biasing and adaptive stabilizing effects are not well understood. We proposed and tested a reactivation and integration mechanism that can account for these contradictory effects. We used multivariate pattern analyses of EEG data (26 human participants, 17 females, 9 males) to examine the reactivation of prior reported orientation during the delay period of a visual working memory task. The reactivation strength of prior reports, but not prior sensory items, was predictive of the magnitude of serial-dependency biases. These reactivated representations integrated with the representation of the current memory item and improved the ability to decode the current contents of memory. Overall, our data provide convergent evidence suggesting that prior reports in a visual working memory task are reactivated on the subsequent trial and become integrated with current memory representations. This similarity-dependent reactivation mechanism drives both report biasing and stabilization effects attributed to serial-dependence in working memory.Significance Statement A primary objective of working memory is to differentiate the present from the past. However, in a continuous visual experience, recent past information often remains relevant for processing subsequent information. How can working memory leverage relevant past information to aid perception and memory while avoiding unwanted influence from irrelevant past information? Here, we show that maintaining new information in working memory can selectively reactivate and assimilate similar information from the recent past. This reactivation biases memory for present items towards the past, which may not always be desirable, but it also enhances the fidelity and precision of these memories, which is certainly an adaptive feature.

Bortezomib restrains M2 polarization and reduces CXCL16-associated CXCR6+CD4 T cell chemotaxis in bleomycin-induced pulmonary fibrosis.

BACKGROUND: The development of pulmonary fibrosis involves a cascade of events, in which inflammation mediated by immune cells plays a pivotal role. Chemotherapeutic drugs have been shown to have dual effects on fibrosis, with bleomycin exacerbating pulmonary fibrosis and bortezomib alleviating tissue fibrotic processes. Understanding the intricate interplay between chemotherapeutic drugs, immune responses, and pulmonary fibrosis is likely to serve as the foundation for crafting tailored therapeutic strategies. METHODS: A model of bleomycin-induced pulmonary fibrosis was established, followed by treatment with bortezomib. Tissue samples were collected for analysis of immune cell subsets and functional assessment by flow cytometry and in vitro cell experiments. Additionally, multi-omics analysis was conducted to further elucidate the expression of chemokines and chemokine receptors, as well as the characteristics of cell populations. RESULTS: Here, we observed that the expression of CXCL16 and CXCR6 was elevated in the lung tissue of a pulmonary fibrosis model. In the context of pulmonary fibrosis or TGF-ß1 stimulation in vitro, macrophages exhibited an M2-polarized phenotype and secreted more CXCL16 than those of the control group. Moreover, flow cytometry revealed increased expression levels of CD69 and CXCR6 in pulmonary CD4 T cells during fibrosis progression. The administration of bortezomib alleviated bleomycin-induced pulmonary fibrosis, accompanied by reduced ratio of M2-polarized macrophages and decreased accumulation of CD4 T cells expressing CXCR6. CONCLUSIONS: Our findings provide insights into the key immune players involved in bleomycin-induced pulmonary fibrosis and offer preclinical evidence supporting the repurposing strategy and combination approaches to reduce lung fibrosis.

FePd Nanozyme- and SKN-Encapsulated Functional Lipid Nanoparticles for Cancer Nanotherapy via ROS-Boosting Necroptosis.

Cell necroptosis has presented great potential, acting as an effective approach against tumor apoptotic resistance, and it could be further enhanced via accompanying reactive oxygen species (ROS) overexpression. However, whether overproduced ROS assists the necroptotic pathway remains unclear. Thus, iron-palladium nanozyme (FePd NZ)- and shikonin (SKN)-encapsulated functional lipid nanoparticles (FPS-LNPs) were designed to investigate the ROS overexpression-enhanced SKN-induced necroptosis. In this system, SKN acts as an effective necroptosis inducer for cancer cells, and FePd NZ, a sensitive Fenton reaction catalyst, produces extra-intracellular ROS to reinforce the necroptotic pathway. Both in vitro and in vivo antitumor evaluation revealed that FPS-LNPs presented the best tumor growth inhibition efficacy compared with FP-LNPs or SKN-LNPs alone. Meanwhile, induced necroptosis by FPS-LNPs can further trigger the release of damage-associated molecular patterns (DAMPs) and antigens from dying tumor cells to activate the innate immune response. Taking biosafety into consideration, this study has provided a potential nanoplatform for cancer nanotherapy via inducing necroptosis to avoid apoptosis resistance and activate CD8+ T cell immune response.

Enhancing Glioblastoma Immunotherapy with Integrated Chimeric Antigen Receptor T Cells through the Re-Education of Tumor-Associated Microglia and Macrophages.

Glioblastoma (GBM) is an aggressive brain cancer that is highly resistant to treatment including chimeric antigen receptor (CAR)-T cells. Tumor-associated microglia and macrophages (TAMs) are major contributors to the immunosuppressive GBM microenvironment, which promotes tumor progression and treatment resistance. Hence, the modulation of TAMs is a promising strategy for improving the immunotherapeutic efficacy of CAR-T cells against GBM. Molecularly targeting drug pexidartinib (PLX) has been reported to re-educate TAMs toward the antitumorigenic M1-like phenotype. Here, we developed a cell-drug integrated technology to reversibly conjugate PLX-containing liposomes (PLX-Lip) to CAR-T cells and establish tumor-responsive integrated CAR-T cells (PLX-Lip/AZO-T cells) as a combination therapy for GBM. We used a mouse model of GBM to show that PLX-Lip was stably maintained on the surface of PLX-Lip/AZO-T cells in circulation and these cells could transmigrate across the blood-brain barrier and deposit PLX-Lip at the tumor site. The uptake of PLX-Lip by TAMs effectively re-educated them into the M1-like phenotype, which in turn boosted the antitumor function of CAR-T cells. GBM tumor growth was completely eradicated in 60% of the mice after receiving PLX-Lip/AZO-T cells and extended their overall survival time beyond 50 days; in comparison, the median survival time of mice in other treatment groups did not exceed 35 days. Overall, we demonstrated the successful fusion of CAR-T cells and small-molecule drugs with the cell-drug integrated technology. These integrated CAR-T cells provided a superior combination strategy for GBM treatment and presented a reference for the construction of integrated cell-based drugs.

Ion/Electron Co-Conductive Triple-Phase Interface Enabling Fast Redox Reaction Kinetics in Lithium-Sulfur Batteries.

Lithium-sulfur batteries (LSBs) are promising next-generation energy storage systems because of their high energy densities and high theoretical specific capacities. However, most catalysts in the LSBs are based on carbon materials, which can only improve the conductivity and are unable to accelerate lithium-ion transport. Therefore, it would be worthwhile to develop a catalytic electrode exhibiting both ion and electron conductivity. Herein, a triple-phase interface using lithium lanthanum titanate/carbon (LLTO/C) nanofibers to construct ion/electron co-conductive materials was used to afford enhanced adsorption of lithium polysulfides (LiPSs), high conductivity, and fast ion transport in working LSBs. The triple-phase interface accelerates the kinetics of the soluble LiPSs and promotes uniform Li2S precipitation/dissolution. Additionally, the LLTO/C nanofibers decrease the reaction barrier of the LiPSs, significantly improving the conversion of LiPSs to Li2S and promoting rapid conversion. Specifically, the LLTO promotes ion transport owing to its high ionic conductivity, and the carbon enhances the conductivity to improve the utilization rate of sulfur. Therefore, the LSBs with LLTO/C functional separators deliver stable life cycles, high rates, and good electrocatalytic activities. This strategy is greatly important for designing ion/electron conductivity and interface engineering, providing novel insight for the development of the LSBs.

Factors associated with the intrinsic capacity in older adults: A scoping review.

INTRODUCTION: In 2015, the term 'intrinsic capacity' (IC) was proposed by the World Health Organisation to promote healthy aging. However, the factors associated with IC are still discrepant and uncertain. AIM: We aim to synthesise the factors connected with IC. METHODS: This scoping review followed the five-stage framework of Arksey and O'Malley and was reported using PRISMA-ScR guidelines. RESULTS: In all, 29 articles were included. IC of older adults is associated with demographic characteristics, socioeconomic factors, disease conditions, behavioural factors, and biomarkers. Age, sex, marital status, occupation status, education, income/wealth, chronic diseases, hypertension, diabetes, disability, smoking status, alcohol consumption, and physical activity were emerged as important factors related to the IC of older adults. CONCLUSIONS: This review shows that IC is related to multiple factors. Understanding these factors can provide the healthcare personnel with the theoretical basis for intervening and managing IC in older adults. RELEVANCE TO CLINICAL PRACTICE: The influencing factors identified in the review help to guide older adults to maintain their own intrinsic capacity, thereby promoting their health and well-being. The modifiable factors also provide evidence for healthcare personnel to develop targeted intervention strategies to delay IC decline. NO PATIENT OR PUBLIC CONTRIBUTION: As this is a scoping review, no patient or public contributions are required.

Mining strategies for isolating plastic-degrading microorganisms.

Plastic waste is a growing global pollutant. Plastic degradation by microorganisms has captured attention as an earth-friendly tactic. Although the mechanisms of plastic degradation by bacteria, fungi, and algae have been explored over the past decade, a large knowledge gap still exists regarding the identification, sorting, and cultivation of efficient plastic degraders, primarily because of their uncultivability. Advances in sequencing techniques and bioinformatics have enabled the identification of microbial degraders and related enzymes and genes involved in plastic biodegradation. In this review, we provide an outline of the situation of plastic degradation and summarize the methods for effective microbial identification using multidisciplinary techniques such as multiomics, meta-analysis, and spectroscopy. This review introduces new strategies for controlling plastic pollution in an environmentally friendly manner. Using this information, highly efficient and colonizing plastic degraders can be mined via targeted sorting and cultivation. In addition, based on the recognized rules and plastic degraders, we can perform an in-depth analysis of the associated degradation mechanism, metabolic features, and interactions.

Glyphosate Disorders Soil Enchytraeid Gut Microbiota and Increases Its Antibiotic Resistance Risk.

Pesticides promote the stable development of intensive global agriculture. Nevertheless, their residues in the soil can cause ecological and human health risks. Glyphosate is a popular herbicide and is generally thought to be ecologically safe and nontoxic, but this conclusion has been questioned. Herein, we investigated the interaction among soil fauna (Enchytraeus crypticus) exposed to glyphosate and found that glyphosate induced oxidative stress and detoxification responses in E. crypticus and disturbed their lipid metabolism and digestive systems. We further demonstrated that glyphosate disordered the gut microbiota of E. crypticus and increased the abundance of resistance determinants with significant human health risks. Empirical tests and structural equation models were then used to confirm that glyphosate could cause E. crypticus to generate reactive oxygen species, indirectly interfering with their gut microbiota. Our study provides important implications for deciphering the mechanisms of the ecotoxicity of pesticides under the challenge of worldwide pesticide contamination.

Effect of different noninvasive ventilation interfaces on the prevention of facial pressure injury: A network meta-analysis.

OBJECTIVE: To assess the effect of different noninvasive ventilation interfaces on preventing the facial pressure injury. METHODS: This network meta-analysis was conducted following the PRISMA reporting guidelines. Seven electronic databases were systematically searched for randomised controlled trials about the comparative effectiveness of different interfaces in preventing facial pressure injury with noninvasive ventilation in adults and newborns from inception to June 2023. The acronym of PICOS was used and the keywords as well as inclusion/exclusion criteria were determined. Study selection and data extraction were performed by two independent reviewers. The Cochrane risk of bias assessment tool was used to assess the methodological quality. RESULTS: A total of 78 randomised controlled trials involving 7,291 patients were included. The results of network meta-analysis showed that the effectiveness of the eight noninvasive ventilation interfaces on the prevention of facial pressure injury was in the order of: nasal cannula > full-face mask > rotation of nasal mask with nasal prongs > helmet > nasal mask > oronasal mask > nasal prongs > face mask. The use of full-face mask in adults and nasal cannula in newborns had the best effect on preventing the incidence of facial pressure injury. CONCLUSIONS: The use of full-face mask in adults and nasal cannula in newborns had the most clinical advantage in preventing the incidence of facial pressure injury and were worthy promoting in clinical practice. IMPLICATIONS FOR CLINICAL PRACTICE: This study provides a certain theoretical basis for the selection of appropriate interface for patients with noninvasive ventilation. Clinical practitioners should choose the appropriate interfaces based on the patient's specific condition to reduce the incidence of facial pressure injury, enhance patient comfort, and improve the effectiveness of respiratory therapy.

Distinctly altered lipid components in hepatocellular carcinoma relate to impaired T cell-dependent antitumor immunity.

BACKGROUND AND AIMS: T cells are master effectors of anti-tumor immunity in cancer. Recent studies suggest that altered lipid metabolism imposed by the tumor microenvironment constrains anti-tumor immunity. However, the tumor-associated lipid species changes that dampen T cell ability to control tumor progression are not fully understood. Here, we plan to clarify the influences of distinctly altered lipid components in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) on T-cell function, aiming to seek lipid metabolic targets for improving T cell anti-tumor effects. METHODS: Tumor tissues and non-tumor liver from HCC patients were collected for RNA-sequencing, lipid profiling and T cell characterizing, followed by correlation analysis. Additionally, the effects of significantly changed lipid components on anti-tumor potential of T cells were tested by in vitro cell experiments and/or in vivo tumor inoculated model. RESULTS: Altered lipid metabolism coincides with impaired T cell response in HBV-related HCC. Characteristic lipid composition, significantly marked by accumulation of long-chain acylcarnitines (LCACs) and reduction of lysophosphatidylcholines (LPCs), are found in the tumor tissue. Notably, LCACs accumulated are associated with T cells exhaustion and deficient functionality, while LPCs correlate to anti-tumor effects of T cells. In particular, supplement of LPCs, including LPC (20:0) and LPC (22:0), directly promote the activation and IFN-γ secretion of T cells in vitro, and suppress tumor growth in vivo. CONCLUSIONS: Our study highlights the distinctly changed lipid components closely related to T cell dysregulation in HCC, and suggests a promising strategy by decreasing LCACs and increasing LPCs for anti-tumor immunotherapy.

Bend but don't break: Prioritization protects working memory from displacement but leaves it vulnerable to distortion from distraction.

Perceptual distraction distorts visual working memory representations. Previous research has shown that memory responses are systematically biased towards passively viewed visual distractors that are similar to the memoranda. However, it remains unclear whether the prioritization of one working memory representation over another reduces the impact of perceptual distractors. We designed a study with five different types of visual distraction that varied in engagement and found evidence for both subtle distortions and catastrophic failures of memory. Importantly, prioritization protected working memories from catastrophic loss (fewer "swap errors") but rendered them more vulnerable to distortion (greater attractive "biases" towards the distractor). Our findings demonstrate that prioritization does not simply protect working memory from any and all interference, but rather it reduces the likelihood of catastrophic disruption from perceptual distraction at the cost of an increased likelihood of distortion.

Which cutoff value of the Montreal Cognitive Assessment should be used for post-stroke cognitive impairment? A systematic review and meta-analysis on diagnostic test accuracy.

BACKGROUND: Post-stroke cognitive impairment (PSCI) is one of the serious complications of stroke. The Montreal Cognitive Assessment (MoCA), as a brief cognitive impairment screening tool, is widely used in stroke survivors. However, some studies have suggested that the use of the universal cutoff value of 26 may be inappropriate for detecting cognitive impairments in stroke settings. AIM: We conducted this study to identify the optimal cutoff value of the MoCA in screening for PSCI. METHODS: PubMed, CINAHL, Embase, the Cochrane Library, and Web of Science were searched for eligible studies until March 23, 2023. All studies were screened by two independent researchers. The quality of each article was evaluated by the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate mixed-effects model was used to pool sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and the summary receiver operating characteristic curve. RESULTS: Twenty-four studies with a total of 4231 patients were included in this review. Despite the lack of evidence of publication bias, a high degree of heterogeneity was observed. A meta-analysis revealed that a cutoff value of 21/22 yielded the best diagnostic accuracy. The optimal cutoff varied in different regions, stroke types, and stroke phases as well. CONCLUSION: The optimal cutoff of MoCA was 21/22 for stroke populations rather than the initially recommended cutoff of 26. A revised (lower) cutoff should be considered for stroke survivors.

Comparison of meteoric water lines at different temporal scales and regression methods in inland monsoon region, Northwest China.

The local meteoric water line (LMWL) is an important basis for tracing the regional hydrological processes with stable isotopes. The establishment of LMWL, which can represent the overall characteristics of stable isotopes of local precipitation, is crucial for accurately revealing the hydrological processes. The influences of different temporal scales and regression methods on the established LMWL were analyzed and compared based on nine years of stable isotopic data of precipitation in Changwu Tableland, a typical area of the inland monsoon region of Northwest China. The results showed that, for different regression methods, the LMWL established by stable isotopes of annual precipitation was basically stable, whereas the LWML established by each precipitation event and the monthly precipitation data showed significant differences with different regression methods. The LMWL from the ordinary least squares regression (OLSR), major axis regression (MA) and reduced major axis regression (RMA) methods were significantly different based on the data of precipitation event, monthly precipitation data, and annual precipitation data, respectively. Only when OLSR, MA and RMA considering precipitation weighting were used, the LMWL established by these scale data was relatively close. This suggested that special attention should be paid to the selection of precipitation stable isotope data scale and regression method when LMWL was established in areas with temporal heterogeneity of precipitation and stable isotopic characteristics. For regions where stable isotope observations of precipitation were difficult and data were limited, the precipitation weighted major axis regression or reduced major axis regression methods are recommended during the establishment of representative LMWL.

Explicit attentional goals unlock implicit spatial statistical learning.

People can quickly learn spatial distributions of targets and direct attention to likely regions of targets. These implicitly learned spatial biases have been shown to be persistent, transferring to other similar visual search tasks. However, a persistent attentional bias is incompatible with frequently changing goals in our typical daily environment. We propose a flexible goal-specific probability cueing mechanism to address this discrepancy. We examined whether participants could learn and utilize target-specific spatial priority maps across five experiments (each N = 24). In Experiment 1, participants were faster to find the target at the target-specific high-probability location, in line with a goal-specific probability cueing effect. This demonstrated that separate spatial priorities derived from statistical learning can be flexibly activated based on the current goal. In Experiment 2, we ensured the results were not driven solely by intertrial priming. In Experiment 3, we ensured the results were driven by early attentional guidance effects. In Experiment 4, we extended our findings to a complex spatial distribution including four locations, supporting a sophisticated representation of target likelihood in the activated spatial priority maps. Finally, in Experiment 5, we confirmed that the effect was driven by the activation of an attentional template and not associative learning between the target cue and a spatial location. Our findings demonstrate a previously unrecognized mechanism for flexibility within statistical learning. The goal-specific probability cueing effect relies on coordination of feature-based and location-based attention, utilizing information that crosses traditional boundaries between top-down control and selection history. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Understanding the ecological effects of the fungicide difenoconazole on soil and Enchytraeus crypticus gut microbiome.

Increasing knowledge of the impacts of pesticides on soil ecological communities is fundamental to a comprehensive understanding of the functional changes in the global agroecosystem industry. In this study, we examined microbial community shifts in the gut of the soil-dwelling organism Enchytraeus crypticus and functional shifts in the soil microbiome (bacteria and viruses) after 21 d of exposure to difenoconazole, one of the main fungicides in intensified agriculture. Our results demonstrated reduced body weight and increased oxidative stress levels of E. crypticus under difenoconazole treatment. Meanwhile, difenoconazole not only altered the composition and structure of the gut microbial community, but also interfered with the soil-soil fauna microecology stability by impairing the abundance of beneficial bacteria. Using soil metagenomics, we revealed that bacterial genes encoding detoxification and viruses encoding carbon cycle genes exhibited a dependent enrichment in the toxicity of pesticides via metabolism. Taken together, these findings advance the understanding of the ecotoxicological impact of residual difenoconazole on the soil-soil fauna micro-ecology, and the ecological importance of virus-encoded auxiliary metabolic genes under pesticide stress.

When and for whom organizational identification is more effective in eliciting safety voice: an empirical study from the construction industry perspective.

Safety voice (SV) is a form of voice in which employees express opinions or concerns about organizational safety. It plays an important role in preventing accidents and promoting safety performance. The purpose of this study is to reveal the emotional factors and boundary conditions behind employee engagement in SV, especially in the construction context. This study, therefore, investigated how organizational identification (OID) drove construction project participants' SV using a three-way interaction model of perceived insider status (PIS) as an individual difference and safety climate (SC) as an organizational contextual difference. The proposed model was tested using a sample of 357 participants in different construction projects. The results showed that OID was positively correlated with SV. The interaction effect of OID and PIS on SV depended on SC, with PIS enhancing the identification-voice relationship at a low level of SC and weakening it at a high level of SC.

Long-Chain Acylcarnitines Induce Senescence of Invariant Natural Killer T Cells in Hepatocellular Carcinoma.

CD1d-restricted invariant natural killer T (iNKT) cells actively patrol the liver and possess valuable antitumor potential. However, clinical trials evaluating administration of iNKT cell-specific agonist α-galactosylceramide (α-GalCer) have failed to achieve obvious tumor regression. Improving the efficacy of iNKT cell-based immunotherapy requires a better understanding of the factors restraining the clinical benefits. In the context of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), we found circulating and hepatic iNKT cells were hyperactivated but demonstrated imbalances in ratio and defective α-GalCer responsiveness. Exogenous IL2 helped to expand residual α-GalCer-responsive clones with reduced T-cell receptor diversity. However, transcriptome-wide analysis revealed activation of the senescence-associated secretory phenotype and dampened cytotoxicity in iNKT cells, weakening their immune surveillance capacity. The senescent status of iNKT cells from the patients was further illustrated by cell-cycle arrest, impaired telomere maintenance, perturbed calcium transport-related biological processes, and altered metabolism. Lipidomic profiling revealed the accumulation of long-chain acylcarnitines (LCAC) and aberrant lipid metabolism in HCC tissue. Exogenous LCACs, especially palmitoyl-carnitine and stearoyl-carnitine, inhibited iNKT cell expansion and promoted senescence. Collectively, our results provide deeper insights into iNKT cell dysregulation and identify a cell senescence-associated challenge for iNKT cell-based immunotherapy in HBV-related HCC. The mechanistic links between iNKT cell senescence and accumulated LCACs suggest new targets for anti-HCC immunotherapies. SIGNIFICANCE: Patients with HBV-related HCC exhibit a cell senescence-associated dysregulation of invariant natural killer cells that is related to altered lipid metabolism and accumulated LCACs in tumor tissue.