Zinc Coordination Lipid Nanoparticles Co-Delivering Calcium Peroxide and Chelating STING agonist for Enhanced Cancer Metalloimmunotherapy.

Metalloimmunotherapy has achieved great preclinical success against malignant tumors. Nonetheless, the limited immune cell infiltration and impaired immunogenicity within the tumor microenvironment (TME) significantly hinder its translation to clinical applications. In this study, a zinc coordination lipid nanoparticle is developed loaded with calcium peroxide hydrate (CaO2) nanoparticles and the STING agonist diABZI-2, which is termed A-CaO2-Zn-LNP. The release of Zn2+ from the A-CaO2-Zn-LNP and the calcium overload synergistically induced immunogenic cell death (ICD). In addition, CaO2 nanoparticles can consume H+ and release oxygen (O2) under acidic conditions. This treatment increased the pH and alleviated the hypoxia of the TME. Along with cGAS-STING activation by diABZI-2, A-CaO2-Zn-LNP ultimately results in enhanced anti-tumor systemic immunity and long-term immune memory via alleviating the immunosuppressive microenvironment. Taken together, A-CaO2-Zn-LNP offers a new nanoplatform that expands its application for cancer treatment by metalloimmunotheray.

The application effect of the optimized scheduling model of virtual power plant participation in the new electric power system.

To build a comprehensive framework for virtual power plant (VPP) development aligned with market dynamics and to devise effective strategies to foster its growth, this study undertakes several key steps. Firstly, it constructs a VPP development framework based on market conditions, to drive the evolution of new power systems and facilitating energy transformation. Secondly, through a blend of theoretical analysis and model construction, the fundamental principles of VPP are systematically elucidated, and a decision model for the VPP development framework, focusing on price demand response, is formulated. Lastly, an optimal scheduling model for the new power system is developed, with its efficacy validated across three distinct scenarios. The findings underscore the critical importance of integrating energy storage technologies, particularly pumped storage hydropower systems, for achieving balance and optimization within new power systems. Model verification reveals that the incorporation of energy storage power stations significantly enhances system stability and efficiency, particularly in addressing the volatility associated with renewable energy sources. Additionally, the analysis indicates that while the adoption of energy storage technologies may marginally increase overall power generation costs, the total power generation cost declines with the integration of battery storage and pumped storage hydropower stations. This suggests that leveraging energy storage technologies not only enhances system operational reliability but also contributes to reducing the overall cost of power production to a certain extent. In summary, this study presents an economic and environmentally sustainable scheduling model for new power systems within the context of market trading environments. By offering both theoretical insights and practical guidance, it aims to support sustainable development and energy transformation initiatives. Ultimately, the study is poised to foster the adoption of clean energy, facilitate the establishment of smart grids, and bolster the sustainable utilization of energy resources, thereby advancing environmental conservation efforts.

Bioinspired Core-shell nanospheres integrated in multi-signal immunochromatographic sensor for high throughput sensitive detection of Bongkrekic acid in food.

Nowadays, notable progress has been achieved in detecting foodborne toxins by employing nanoenzyme-based lateral flow immunoassay (NLFIA) sensors in point-of-care testing (POCT). It continues to be a major challenge to maximize the enzyme-like performance of nanozymes for educe any potential uncertainties in catalytic process. In this study, we employed a facile and efficient self-assembly approach to fabricate nucleoid-shell structured biomimetic nanospheres CuS@Au-Pt (CAP), which demonstrates enhanced brightness of the colorimetric signal, excellent affinity, and excellent peroxidase activity. The integration of CAP with a competitive-assay NLFIA platform enabled sensitive immunochromatographic detection of bongkrekic acid (BA), with LOD as low as 0.66 ng/mL. After signal amplification through enzyme-like reaction, the detection range was extended around 1-fold. Additionally, CAP-NLFIA effectively detected BA with a recovery rate of 80.96-119.36% for real samples. The study proposes using CAP as a signal reporter in a dual-readout LFIA, which can establish a high throughput sensitive detection platform.

Key periodontal pathogens may mediate potential pathogenic relationships between periodontitis and crohn's disease.

BACKGROUND: Crohn's disease (CD)-associated periodontitis is common. However, the role of periodontal pathogens in the Coexistence of CD and periodontal disease remains unclear. METHODS: To investigate the potential relationship mediated by periodontal pathogens between periodontitis and CD, we collected salivary samples from healthy participants (H group, n = 12), patients with CD (Ch group, n = 10), patients with periodontitis (Ps group, n = 12), and patients with Coexistence of CD and periodontal disease (Cp group, n = 12) and analyzed them by 16 S rRNA sequencing. RESULTS: Patients with Coexistence of CD and periodontal disease had increased levels of Fusobacterium, Actinomyces, Leptotrichia, and Prevotella, which correlated with the severity of periodontitis. Conversely, the levels of Streptococcus, Neisseria, Haemophilus, and Gemella, which decreased in Coexistence of CD and periodontal disease, were negatively correlated with the severity of periodontitis. To further investigate the role of periodontal pathogens in CD development, representative periodontal pathogens causing periodontitis, Porphyromonas gingivalis and Fusobacterium nucleatum, were administered to mice. These pathogens migrate to, and colonize, the gut, accelerating CD progression and aggravating colitis, and even systemic inflammation. In vitro experiments using a Caco-2/periodontal pathogen coculture revealed that P. gingivalis and F. nucleatum increased intestinal permeability by directly disrupting the tight junctions of intestinal epithelial cells. CONCLUSION: Our findings strongly suggest that periodontal pathogens play a role in the relationship between periodontitis and CD. These results provide a basis for understanding the pathogenesis of Coexistence of CD and periodontal disease and may lead to the development of novel therapeutic strategies.

An Improved Synchrosqueezing S-Transform and Its Application in a GPR Detection Task.

The S-transform is a fundamental time-frequency (T-F) domain analysis method in ground penetrating radar (GPR) data processing and can be used for identifying targets, denoising, extracting thin layers, and high-resolution imaging. However, the S-transform spectrum experiences energy leakage near the instantaneous frequency. This phenomenon causes frequency components to erroneously spread over a wider range, impacting the accuracy and precision of GPR data processing. Synchrosqueezing is an effective method to prevent spectrum leakage. In this work, we introduce the synchrosqueezing generalized phase-shifting S-transform (SS-GPST). Initially, it resolves the compatibility issue between the S-transform and the synchrosqueezing strategy through phase-shifting. Subsequently, the SS-GPST accomplishes spectral energy focusing and resolution enhancement via a generalized parameter and synchrosqueezing. A synthetic signal test shows that the SS-GPST excels over other methods at focusing degree, spectral resolution, and signal reconstruction accuracy and speed. In actual GPR tunnel detection data processing, we assess the adaptability of the SS-GPST from three aspects: spectral energy distribution, thin layer identification, and data denoising. The results indicate: (1) compared to other methods, the SS-GPST accurately expresses spectral components with a strong focusing degree and fewer interference components; (2) high-frequency slices of the SS-GPST accurately detect the top and bottom interfaces of a 3.0-3.5 cm reinforcement protection layer; and (3) due to fewer interference components in the SS-GPST spectrum, reconstructing GPR profiles through the SS-GPST inverse transform is an efficient denoising technique. The SS-GPST demonstrates adaptability to different data processing purposes, offers high-resolution T-F spectra, and shows potential to supersede the S-transform.

Decision model for durable clinical benefit from front- or late-line immunotherapy alone or with chemotherapy in non-small cell lung cancer.

BACKGROUND: Predictive biomarkers and models of immune checkpoint inhibitors (ICIs) have been extensively studied in non-small cell lung cancer (NSCLC). However, evidence for many biomarkers remains inconclusive, and the opaqueness of machine learning models hinders practicality. We aimed to provide compelling evidence for biomarkers and develop a transparent decision tree model. METHODS: We consolidated data from 3,288 ICI-treated patients with NSCLC across real-world multicenter, public cohorts and the Choice-01 trial (ClinicalTrials.gov: NCT03856411). Over 50 features were examined for predicting durable clinical benefits (DCBs) from ICIs. Noteworthy biomarkers were identified to establish a decision tree model. Additionally, we explored the tumor microenvironment and peripheral CD8+ programmed death-1 (PD-1)+ T cell receptor (TCR) profiles. FINDINGS: Multivariate logistic regression analysis identified tumor histology, PD-ligand 1 (PD-L1) expression, tumor mutational burden, line, and regimen of ICI treatment as significant factors. Mutation subtypes of EGFR, KRAS, KEAP1, STK11, and disruptive TP53 mutations were associated with DCB. The decision tree (DT10) model, using the ten clinicopathological and genomic markers, showed superior performance in predicting DCB in the training set (area under the curve [AUC] = 0.82) and consistently outperformed other models in test sets. DT10-predicted-DCB patients manifested longer survival, an enriched inflamed tumor immune phenotype (67%), and higher peripheral TCR diversity, whereas the DT10-predicted-NDB (non-durable benefit) group showed an enriched desert immune phenotype (86%) and higher peripheral TCR clonality. CONCLUSIONS: The model effectively predicted DCB after front-/subsequent-line ICI treatment, with or without chemotherapy, for squamous and non-squamous lung cancer, offering clinicians valuable insights into efficacy prediction using cost-effective variables. FUNDING: This study was supported by the National Key R&D Program of China.

Evaluation of first-line and salvage therapies for unresectable malignant mesothelioma: A systematic review and network meta-analysis.

BACKGROUND: Randomized controlled trials (RCTs) of systemic therapies for unresectable malignant mesothelioma have reported conflicting results. It is crucial and urgent to find optimal treatment options for this malignancy, which currently has a poor prognosis. METHODS: Databases PubMed, EMBASE, Cochrane Library, ClinicalTrials.gov, and major international conferences were searched until February 29, 2024. The main outcomes of interest were overall survival (OS), progression-free survival (PFS), overall response rate (ORR), and grade ≥3 treatment-related adverse events (TRAEs). RESULTS: We analyzed 16 RCTs with a total of 5018 patients. Among first-line therapies, nivolumab and ipilimumab significantly increased OS and resulted in fewer grade ≥3 TRAEs. Bevacizumab plus chemotherapy significantly increased PFS. Among salvage therapies, ramucirumab and chemotherapy was associated with the best OS and PFS, but resulted in more grade ≥3 TRAEs. Subgroup analysis by histologic types suggested that in first-line settings, bevacizumab and chemotherapy increase OS the most for epithelioid type, while the nivolumab plus ipilimumab treatment increases OS the most for non-epithelioid type. In salvage therapies, ramucirumab and chemotherapy increase OS for both epithelioid and non-epithelioid types. CONCLUSION: Nivolumab plus ipilimumab was associated with the best OS among first-line treatments. Ramucirumab and chemotherapy was associated with the best clinical outcomes in salvage settings. Treatment for malignant mesothelioma should be tailored based on different clinicopathological characteristics.

Prediction performance comparison of biomarkers for response to immune checkpoint inhibitors in advanced non-small cell lung cancer.

BACKGROUND: The aim of the present study was to compare the predictive accuracy of PD-L1 immunohistochemistry (IHC), tissue or blood tumor mutation burden (tTMB, bTMB), gene expression profile (GEP), driver gene mutation, and combined biomarkers for immunotherapy response of advanced non-small cell lung cancer (NSCLC). METHODS: In part 1, clinical trials involved with predictive biomarker exploration for immunotherapy in advanced NSCLC were included. The area under the curve (AUC) of the summary receiver operating characteristic (SROC), sensitivity, specificity, likelihood ratio and predictive value of the biomarkers were evaluated. In part 2, public datasets of immune checkpoint inhibitor (ICI)-treated NSCLC involved with biomarkers were curated (N = 871). Odds ratio (OR) of the positive versus negative biomarker group for objective response rate (ORR) was measured. RESULTS: In part 1, the AUC of combined biomarkers (0.75) was higher than PD-L1 (0.64), tTMB (0.64), bTMB (0.68), GEP (0.67), and driver gene mutation (0.51). Combined biomarkers also had higher specificity, positive likelihood ratio and positive predictive value than single biomarkers. In part 2, the OR of combined biomarkers of PD-L1 plus TMB (PD-L1 cutoff 1%, 0.14; cutoff 50% 0.13) was lower than that of PD-L1 (cutoff 1%, 0.33; cutoff 50% 0.24), tTMB (0.28), bTMB (0.48), EGFR mutation (0.17) and KRAS mutation (0.47), for distinguishing ORR of patients after immunotherapy. Furthermore, positive PD-L1, tTMB-high, wild-type EGFR, and positive PD-L1 plus TMB were associated with prolonged progression-free survival (PFS). CONCLUSION: Combined biomarkers have superior predictive accuracy than single biomarkers for immunotherapy response of NSCLC. Further investigation is warranted to select optimal biomarkers for various clinical settings.

"Three-in-One" Multifunctional Hollow Nanocages with Colorimetric Photothermal Catalytic Activity for Enhancing Sensitivity in Biosensing.

Immunochromatographic assays (ICAs) have been widely used in the field detection of mycotoxin contaminants. Nevertheless, the lack of multisignal readout capability and the ability of signaling tags to maintain their biological activity while efficiently loading antibodies remain a great challenge in satisfying diverse testing demands. Herein, we proposed a novel three-in-one multifunctional hollow vanadium nanomicrosphere (high brightness-catalytic-photothermal properties)-mediated triple-readout ICA (VHMS-ICA) for sensitive detection of T-2. As the key to this biosensing strategy, vanadium was used as the catalytic-photothermal characterization center, and natural polyphenols were utilized as the bridging ligands for coupling with the antibody while self-assembling with formaldehyde cross-linking into a hollow nanocage-like structure, which offers the possibility of realizing a three-signal readout strategy and improving the coupling efficiency to the antibody while preserving its biological activity. The constructed sensors showed a detection limit (LOD) of 2 pg/mL for T-2, which was about 345-fold higher than that of conventional gold nanoparticle-based ICA (0.596 ng/mL). As anticipated, the detection range of VHMS-ICA was extended about 8-fold compared with the colorimetric signal alone. Ultimately, the proposed immunosensor performed well in maize and oat samples, with satisfactory recoveries. Owing to the synergistic and complementary interactions between distinct signaling modes, the establishment of multimodal immunosensors with multifunctional tags is an efficient strategy to satisfy diversified detection demands.

Trifunctional Nanocomposites with Colorimetric Magnetic Catalytic Activities Labels in Sandwich Immunochromatographic Detection of Escherichia coli O157:H7.

The emergence of nanoenzymes has catalyzed the robust advancement of the lateral flow immunoassay (LFIA) in recent years. Among them, multifunctional nanocomposite enzymes with core-shell architectures are considered preferable for promoting the sensing ability due to their good biocompatibility, precise control over size, and surface properties etc. Herein, we developed a dual-channel ensured lateral flow immunoassay (DFLIA) platform utilizing a magnetic, colorimetric, and catalytic multifunctional nanocomposite enzyme (Fe3O4@TCPP@Pd) [TCPP, Tetrakis (4-carboxyphenyl) porphyrin] for the ultrasensitive and highly accurate rapid detection of Escherichia coli O157:H7 (E. coli O157:H7). Fe3O4@TCPP@Pd-mAb exhibits superior performance compared to traditional AuNPs, including enhanced sensitivity and an extended linear detection range, benefiting from its high brightness signal, strong magnetic separation ability, and high peroxidase activity (Vmax = 2.32 µM S1-). Moreover, the Fe3O4@TCPP@Pd-labeled mAb probe exhibited exceptional stability and high affinity toward E. coli O157:H7 (with an affinity constant of approximately 1.723 × 109 M-1), indicating its potential for the efficient capture of the pathogen. Impressively, the developed Fe3O4@TCPP@Pd-DFLIA achieved ultrasensitive detection for E. coli O157:H7 with pre- and postcatalytic naked-eye detection sensitivities of 255 cfu/mL and 77 cfu/mL, respectively, representing an approximately 41-fold improvement over the conventional AuNP-based LFIA and also possessed good specificity and reproducibility [relative standard deviation (RSD) < 10%]. Additionally, the established DFLIA exhibited satisfactory recoveries in detecting pork and milk samples, further validating the reliability of this platform for immunoassays and demonstrating its potential for utilization in bioassays and clinical diagnostics.