Augmenting Cancer Therapy with a Supramolecular Immunogenic Cell Death Inducer: A Lysosome-Targeted NIR-Light-Activated Ruthenium(II) Metallacycle.

Though immunogenic cell death (ICD) has garnered significant attention in the realm of anticancer therapies, effectively stimulating strong immune responses with minimal side effects in deep-seated tumors remains challenging. Herein, we introduce a novel self-assembled near-infrared-light-activated ruthenium(II) metallacycle, Ru1105 (λem = 1105 nm), as a first example of a Ru(II) supramolecular ICD inducer. Ru1105 synergistically potentiates immunomodulatory responses and reduces adverse effects in deep-seated tumors through multiple regulated approaches, including NIR-light excitation, increased reactive oxygen species (ROS) generation, selective targeting of tumor cells, precision organelle localization, and improved tumor penetration/retention capabilities. Specifically, Ru1105 demonstrates excellent depth-activated ROS production (∼1 cm), strong resistance to diffusion, and anti-ROS quenching. Moreover, Ru1105 exhibits promising results in cellular uptake and ROS generation in cancer cells and multicellular tumor spheroids. Importantly, Ru1105 induces more efficient ICD in an ultralow dose (10 µM) compared to the conventional anticancer agent, oxaliplatin (300 µM). In vivo experiments further confirm Ru1105's potency as an ICD inducer, eliciting CD8+ T cell responses and depleting Foxp3+ T cells with minimal adverse effects. Our research lays the foundation for the design of secure and exceptionally potent metal-based ICD agents in immunotherapy.

Synthesis of Isotypic Giant Polymolybdate Cages for Efficient Photocatalytic C-C Coupling Reactions.

The construction of isotypic high-nuclearity inorganic cages with identical pristine parent structure and increasing nuclearity is highly important for molecular growth and structure-property relationship study, yet it still remains a great challenge. Here, we provide an in situ growth approach for successfully synthesizing a series of new giant hollow polymolybdate dodecahedral cages, Mo250, Mo260-I, and Mo260-E, whose structures are growth based on giant polymolybdate cage Mo240. Remarkably, they show two pathways of nuclear growth based on Mo240, that is, the growth of 10 and 20 Mo centers on the inner and outer surfaces to afford Mo250 and Mo260-I, respectively, and the growth of 10 Mo centers both on the inner and outer surfaces to give Mo260-E. To the best of our knowledge, this is the first study to display the internal and external nuclear growth of a giant hollow polyoxometalate cage. More importantly, regular variations in structure and nuclearity confer these polymolybdate cages with different optical properties, oxidative activities, and hydrogen atom transfer effect, thus allowing them to exhibit moderate to excellent photocatalytic performance in oxidative cross-coupling reactions between different unactivated alkanes and N-heteroarenes. In particular, Mo240 and Mo260-E with better comprehensive abilities can offer the desired coupling product with yield up to 92% within 1 h.

Abnormal causal connectivity of anterior cingulate cortex-visual cortex circuit related to nonsteroidal anti-inflammatory drug efficacy in migraine.

The anterior cingulate cortex (ACC) and visual cortex are integral components of the neurophysiological mechanisms underlying migraine, yet the impact of altered connectivity patterns between these regions on migraine treatment remains unknown. To elucidate this issue, we investigated the abnormal causal connectivity between the ACC and visual cortex in patients with migraine without aura (MwoA), based on the resting-state functional magnetic resonance imaging data, and its predictive ability for the efficacy of nonsteroidal anti-inflammatory drugs (NSAIDs). The results revealed increased causal connectivity from the bilateral ACC to the lingual gyrus (LG) and decreased connectivity in the opposite direction in nonresponders compared with the responders. Moreover, compared with the healthy controls, nonresponders exhibited heightened causal connectivity from the ACC to the LG, right inferior occipital gyrus (IOG) and left superior occipital gyrus, while connectivity patterns from the LG and right IOG to the ACC were diminished. Based on the observed abnormal connectivity patterns, the support vector machine (SVM) models showed that the area under the receiver operator characteristic curves for the ACC to LG, LG to ACC and bidirectional models were 0.857, 0.898, and 0.939, respectively. These findings indicate that neuroimaging markers of abnormal causal connectivity in the ACC-visual cortex circuit may facilitate clinical decision-making regarding NSAIDs administration for migraine management.

High Accuracy of Clinical Verification of Electrohydrodynamic-Driven Nanobox-on-Mirror Platform for Molecular Identification of Respiratory Viruses.

The molecular detection of multiple respiratory viruses provides evidence for the rational use of drugs and effective health management. Herein, we developed and tested the clinical performance of an electrohydrodynamic-driven nanobox-on-mirror platform (E-NoM) for the parallel, accurate, and sensitive detection of four respiratory viral antigens. The E-NoM platform uses gold-silver alloy nanoboxes as the core material with the deposition of a silver layer as a shell on the core surfaces to amplify and enable a reproducible Raman signal readout that facilitates accurate detection. Additionally, the E-NoM platform employs gold microelectrode arrays as the mirror with electrohydrodynamics to manipulate the fluid flow and enhance molecular interactions for an improved biosensing response. The presence of viral antigens binds the nanobox-based core-shell nanostructure on the gold microelectrode and creates the nanocavity with extremely strong "hot spots" to benefit sensitive analysis. Significantly, in a large clinical cohort with 227 patients, the designed E-NoM platform demonstrates the capability of screening respiratory infection with achieved clinical specificity, sensitivity, and accuracy of 100.0, 96.48, and 96.91%, respectively. It is anticipated that the E-NoM platform can find a position in clinical usage for respiratory disease diagnosis.

Molecular Stratification and Treatment Monitoring of Lung Cancer Using a Small Extracellular Vesicle-Activated Nanocavity Architecture.

Development of molecular diagnostics for lung cancer stratification and monitoring is crucial for the rational planning and timely adjustment of treatments to improve clinical outcomes. In this regard, we propose a nanocavity architecture to sensitively profile the protein signature on small extracellular vesicles (sEVs) to enable accurate, noninvasive staging and treatment monitoring of lung cancer. The nanocavity architecture is formed by molecular recognition through the binding of sEVs with the nanobox-based core-shell surface-enhanced Raman scattering (SERS) barcodes and mirrorlike, asymmetric gold microelectrodes. By imposing an alternating current on the gold microelectrodes, a nanofluidic shear force was stimulated that supported the binding of sEVs and the efficient assembly of the nanoboxes. The binding of sEVs further induced a nanocavity between the nanobox and the gold microelectrode that significantly amplified the electromagnetic field to enable the simultaneous enhancement of Raman signals from four SERS barcodes and generate patient-specific molecular sEV signatures. Importantly, evaluated on a cohort of clinical samples (n = 76) on the nanocavity architecture, the acquired patient-specific sEV molecular signatures achieved accurate identification, stratification, and treatment monitoring of lung cancer patients, highlighting its potential for transition to clinical utility.

Mechano-growth factor regulates periodontal ligament stem cell proliferation and differentiation through Fyn-RhoA-YAP signaling.

BACKGROUND: Mechano-growth factor (MGF), which is a growth factor produced specifically in response to mechanical stimuli, with potential of tissue repair and regeneration. Our previous research has shown that MGF plays a crucial role in repair of damaged periodontal ligaments by promoting differentiation of periodontal ligament stem cells (PDLSCs). However, the molecular mechanism is not fully understood. This study aimed to investigated the regulatory effect of MGF on differentiation of PDLSCs and its molecular mechanism. METHODS: Initially, we investigated how MGF impacts cell growth and differentiation, and the relationship with the activation of Fyn-p-YAPY357 and LATS1-p-YAPS127. Then, inhibitors were used to interfere Fyn phosphorylation to verify the role of Fyn-p-YAP Y357 signal after MGF stimulation; moreover, siRNA was used to downregulate YAP expression to clarify the function of YAP in PDLSCs proliferation and differentiation. Finally, after C3 was used to inhibit the RhoA expression, we explored the role of RhoA in the Fyn-p-YAP Y357 signaling pathway in PDLSCs proliferation and differentiation. RESULTS: Our study revealed that MGF plays a regulatory role in promoting PDLSCs proliferation and fibrogenic differentiation by inducing Fyn-YAPY357 phosphorylation but not LATS1-YAP S127 phosphorylation. Moreover, the results indicated that Fyn could not activate YAP directly but rather activated YAP through RhoA in response to MGF stimulation. CONCLUSION: The research findings indicated that the Fyn-RhoA-p-YAPY357 pathway is significant in facilitating the proliferation and fibrogenic differentiation of PDLSCs by MGF. Providing new ideas for the study of MGF in promoting periodontal regenerative repair.

A selenium-based NIR-II photosensitizer for a highly effective and safe phototherapy plan.

High efficiency, stability, long emission wavelength (NIR-II), and good biocompatibility are crucial for photosensitizers in phototherapy. However, current Food and Drug Administration (FDA)-approved organic fluorophores exhibit poor chemical stability and photostability as well as short emission wavelength, limiting their clinical usage. To address this, we developed Se-IR1100, a novel organic photosensitizer with a photostable and thermostable benzobisthiadiazole (BBTD) backbone. By incorporating selenium as a heavy atom and constructing a D-A-D structure, Se-IR1100 exhibits a maximum fluorescence emission wavelength of 1100 nm. Compared with FDA-approved indocyanine green (ICG), DSPE-PEGylated Se-IR1100 nanoparticles exhibit prominent photostability and long-lasting photothermal effects. Upon 808 nm laser irradiation, Se-IR1100 NPs efficiently convert light energy into heat and reactive oxygen species (ROS), inducing cancer cell death in cellular studies and living organisms while maintaining biocompatibility. With salient photostability and a photothermal conversion rate of 55.37%, Se-IR1100 NPs hold promise as a superior photosensitizer for diagnostic and therapeutic agents in oncology. Overall, we have designed and optimized a multifunctional photosensitizer Se-IR1100 with good biocompatibility that performs NIR-II fluorescence imaging and phototherapy. This dual-strategy method may offer novel approaches for the development of multifunctional probes using dual-strategy or even multi-strategy methods in bioimaging, disease diagnosis, and therapy.

Aggregation enhanced fluorescence and Raman signals for highly sensitive cancer detection.

The implementation of early cancer detection benefits the treatment outcomes with remarkably improved survival rate through the detection of rare circulating biomarkers in body fluids. Spectroscopic technologies play a crucial role in sensitive biomarker measurements by outputting extremely strong signals. In particular, the aggregation enhanced fluorescence and Raman technologies feature the detection of targets down to single-molecule level, thereby demonstrating the great promise of early cancer detection. In this review, we focus on the aggregation-induced emission (AIE) and aggregation-related surface-enhanced Raman scattering (SERS) spectroscopic strategies for detecting cancer biomarkers. We discuss the AIE and SERS based biomarker detection using target-driven aggregation as well as the aggregated nanoprobes. Furthermore, we deliberate on the progress of developing AIE and SERS integrated platforms. Ultimately, we put forth the potential challenges and perspectives on the way to use these two spectroscopic technologies in clinical settings. It is expected this review can inspire the design of AIE and SERS integrated platform for highly sensitive and accurate cancer detection.

HerbMet: Enhancing metabolomics data analysis for accurate identification of Chinese herbal medicines using deep learning.

INTRODUCTION: Chinese herbal medicines have been utilized for thousands of years to prevent and treat diseases. Accurate identification is crucial since their medicinal effects vary between species and varieties. Metabolomics is a promising approach to distinguish herbs. However, current metabolomics data analysis and modeling in Chinese herbal medicines are limited by small sample sizes, high dimensionality, and overfitting. OBJECTIVES: This study aims to use metabolomics data to develop HerbMet, a high-performance artificial intelligence system for accurately identifying Chinese herbal medicines, particularly those from different species of the same genus. METHODS: We propose HerbMet, an AI-based system for accurately identifying Chinese herbal medicines. HerbMet employs a 1D-ResNet architecture to extract discriminative features from input samples and uses a multilayer perceptron for classification. Additionally, we design the double dropout regularization module to alleviate overfitting and improve model's performance. RESULTS: Compared to 10 commonly used machine learning and deep learning methods, HerbMet achieves superior accuracy and robustness, with an accuracy of 0.9571 and an F1-score of 0.9542 for distinguishing seven similar Panax ginseng species. After feature selection by 25 different feature ranking techniques in combination with prior knowledge, we obtained 100% accuracy and an F1-score for discriminating P. ginseng species. Furthermore, HerbMet exhibits acceptable inference speed and computational costs compared to existing approaches on both CPU and GPU. CONCLUSIONS: HerbMet surpasses existing solutions for identifying Chinese herbal medicines species. It is simple to use in real-world scenarios, eliminating the need for feature ranking and selection in classical machine learning-based methods.

Sudden sulfamethoxazole shock leads to nitrite accumulation in microalgae-nitrifying bacteria consortia: Physiological responses and light regulating strategy.

Antibiotic shock may potentially impact the performance of promising microalgae-nitrifying bacteria consortia (MNBC) processes. This study investigated physiological behaviors of MNBC under sulfamethoxazole (SMX) shock (mg/L level) and verified a light regulating strategy for improving process performance. Results showed that SMX shock did not affect ammonium removal but caused nitrite accumulation, resulting from combined effects of excessive reactive oxidative species (ROS) production, inhibited microalgal photosynthetic activity, upregulated expressions of amoA and hao, and downregulated expression of nxrA. Moreover, high ammonium concentration aggravated nitrite accumulation and reduced ammonium removal owing to significantly reduced dissolved oxygen (DO). Increasing light intensity enhanced microalgal photo-oxygenation and promoted expressions of all nitrification-related genes, thus improving ammonium removal and alleviating nitrite accumulation. A central composite design coupled with response surface methodology (CCD-RSM) further demonstrated the negative impacts of SMX shock and high ammonium on MNBC and the effectiveness of the light regulation in maintaining stable process performance. This study provides theoretical basis for physiological responses and regulatory strategy of the MNBC process facing short-term antibiotic shock.

Effects of non-nutritive sweeteners on growth and intestinal health by regulating hypothalamic RNA profile and ileum microbiota in guinea pigs.

BACKGROUND: Non-nutritive sweeteners (NNS) are commonly used in sweetened foods and beverages; however their role in metabolic regulation is still not clear. In this experiment, we used guinea pigs as an animal model to study the effect of NNS on body growth and intestinal health by modifying gut microbiota and hypothalamus-related proteins. RESULTS: For a 28-day feeding experiment a total of 40 guinea pigs were randomly divided into four groups, one control (CN) group and three treatments, in which three NNS were added to the diet: rebaudioside A (RA, 330 mg kg-1), sodium saccharin (SS, 800 mg kg-1), and sucralose (TGS, 167 mg kg-1), respectively. The TGS group exhibited significantly reduced food consumption in comparison with the CN group (P < 0.05) whereas the RA group showed increased food consumption in comparison with the CN group (P < 0.05). Notably, Taste receptor type 1 subunit 2 (T1R2) expression in the hypothalamus was significantly higher in the RA group than in the CN group (P < 0.05). The mRNA expressions of appetite-stimulated genes arouti-related neuropeptide (AGRP), neuropeptide Y (NPY), and thyroid stimulating hormone (TSHB) were significantly higher than those in the CN group (P < 0.05) but mRNA expressions of appetite-suppressed genes tryptophan hydroxylase 2(THP2) were significantly lower in the TGS group (P < 0.05). Furthermore, NNS in the guinea pig diets (RA, SS, TGS) significantly increased the relative abundance of Muribaculaceae but decreased the relative abundance of Clostridia_vadin BB60 in comparison with the CN group (P < 0.05). We also found that dietary supplementation with RA also significantly altered the relative abundance of Lactobacillus. CONCLUSION: Our finding confirmed that dietary supplementation with RA and TGS affected body growth and intestinal health by modulating hypothalamic RNA profiles and ileum microbiota, suggesting that NNS should be included in guinea-pig feeding. © 2024 Society of Chemical Industry.

Exploring potential neuroimaging biomarkers for the response to non-steroidal anti-inflammatory drugs in episodic migraine.

BACKGROUND: Non-steroidal anti-inflammatory drugs (NSAIDs) are considered first-line medications for acute migraine attacks. However, the response exhibits considerable variability among individuals. Thus, this study aimed to explore a machine learning model based on the percentage of amplitude oscillations (PerAF) and gray matter volume (GMV) to predict the response to NSAIDs in migraine treatment. METHODS: Propensity score matching was adopted to match patients having migraine with response and nonresponse to NSAIDs, ensuring consistency in clinical characteristics and migraine-related features. Multimodal magnetic resonance imaging was employed to extract PerAF and GMV, followed by feature selection using the least absolute shrinkage and selection operator regression and recursive feature elimination algorithms. Multiple predictive models were constructed and the final model with the smallest predictive residuals was chosen. The model performance was evaluated using the area under the receiver operating characteristic (ROCAUC) curve, area under the precision-recall curve (PRAUC), balance accuracy (BACC), sensitivity, F1 score, positive predictive value (PPV), and negative predictive value (NPV). External validation was performed using a public database. Then, correlation analysis was performed between the neuroimaging predictors and clinical features in migraine. RESULTS: One hundred eighteen patients with migraine (59 responders and 59 non-responders) were enrolled. Six features (PerAF of left insula and left transverse temporal gyrus; and GMV of right superior frontal gyrus, left postcentral gyrus, right postcentral gyrus, and left precuneus) were observed. The random forest model with the lowest predictive residuals was selected and model metrics (ROCAUC, PRAUC, BACC, sensitivity, F1 score, PPV, and NPV) in the training and testing groups were 0.982, 0.983, 0.927, 0.976, 0.930, 0.889, and 0.973; and 0.711, 0.648, 0.639, 0.667,0.649, 0.632, and 0.647, respectively. The model metrics of external validation were 0.631, 0.651, 0.611, 0.808, 0.656, 0.553, and 0.706. Additionally, a significant positive correlation was found between the GMV of the left precuneus and attack time in non-responders. CONCLUSIONS: Our findings suggest the potential of multimodal neuroimaging features in predicting the efficacy of NSAIDs in migraine treatment and provide novel insights into the neural mechanisms underlying migraine and its optimized treatment strategy.

An Ultrasound-Activated Supramolecular Modulator Enhancing Autophagy to Prevent Ventricular Arrhythmias Post-Myocardial Infarction.

Ventricular arrhythmias (VAs) triggered by myocardial infarction (MI) are the leading cause of sudden cardiac mortality worldwide. Current therapeutic strategies for managing MI-induced VAs, such as left stellate ganglion resection and ablation, are suboptimal, highlighting the need to explore safer and more effective intervention strategies. Herein, we rationally designed two supramolecular sonosensitizers RuA and RuB, engineered through acceptor modification to generate moderate reactive oxygen species (ROS) to modulate VAs. Both RuA and RuB demonstrated high ultrasound (US)-activated ROS production efficiency, with singlet oxygen (1O2) quantum yield (ΦΔ) of 0.70 and 0.88, respectively, surpassing ligand IR1105 and the conventional sonosensitizer ICG (ΦΔ=0.40). In vitro, RuB, at a modest concentration and under US intensity notably boosts pro-survival autophagy in microglia BV2 cell. To improve in vivo stability and biocompatibility, RuB was further encapsulated into DSPE-PEG5000 to prepare RuB nanoparticles (RuB NPs). In vivo studies after microinjection of RuB NPs into the paraventricular nucleus (PVN) and subsequent US exposure, demonstrated that RuB NPs-mediated US modulation effectively suppresses sympathetic nervous activity (SNA) and inflammatory responses, thereby preventing VAs. Importantly, no tissue injury was observed post RuB NPs-mediated US modulation. This work pioneers the design of long-wave emission supramolecular sonosensitizers, offering new insights into regulating cardiovascular diseases.

Grouper annexin A2 affects RGNNV by regulating the host immune response.

Annexin A2 (AnxA2) is ubiquitous in vertebrates and has been identified as a multifunctional protein participating in a series of biological processes, such as endocytosis, exocytosis, signal transduction, transcription regulation, and immune responses. However, the function of AnxA2 in fish during virus infection still remains unknown. In this study, we identified and characterized AnxA2 (EcAnxA2) in Epinephelus coioides. EcAnxA2 encoded a 338 amino acids protein with four identical annexin superfamily conserved domains, which shared high identity with other AnxA2 of different species. EcAnxA2 was widely expressed in different tissues of healthy groupers, and its expression was significantly increased in grouper spleen cells infected with red-spotted grouper nervous necrosis virus (RGNNV). Subcellular locatio n analyses showed that EcAnxA2 diffusely distributed in the cytoplasm. After RGNNV infection, the spatial distribution of EcAnxA2 was unaltered, and a few EcAnxA2 co-localized with RGNNV during the late stage of infection. Furthermore, overexpression of EcAnxA2 significantly increased RGNNV infection, and knockdown of EcAnxA2 reduced RGNNV infection. In addition, overexpressed EcAnxA2 reduced the transcription of interferon (IFN)-related and inflammatory factors, including IFN regulatory factor 7 (IRF7), IFN stimulating gene 15 (ISG15), melanoma differentiation related gene 5 (MDA5), MAX interactor 1 (Mxi1) laboratory of genetics and physiology 2 (LGP2), IFN induced 35 kDa protein (IFP35), tumor necrosis factor receptor-associated factor 6 (TRAF6) and interleukin 6 (IL-6). The transcription of these genes was up-regulated when EcAnxA2 was inhibited by siRNA. Taken together, our results showed that EcAnxA2 affected RGNNV infection by down-regulating the host immune response in groupers, which provided new insights into the roles of AnxA2 in fish during virus infection.

Chronic gastritis may predict risk of cerebral small vessel disease.

BACKGROUND AND PURPOSE: Chronic gastritis, especially that caused by helicobacter pylori (HP) infection, has been associated with increased risk of ischemic stroke. But the relationship between chronic gastritis and cerebral small vessel disease (CSVD) remains largely undetermined. This study aimed to determine the potential predictors for CSVD, with chronic gastritis and its proxies as alternatives. METHOD: Patients aged 18 years or older with indications for electronic gastroscopy were enrolled. Presence of CSVD was evaluated with brain magnetic resonance imaging (MRI) results. Degree of CSVD was scored according to established criteria. Logistic regression analysis was used for identifying possible risk factors for CSVD. RESULTS: Of the 1191 enrolled patients, 757 (63.6%) were identified as with, and 434 (36.4%) as without CSVD. Multivariate analysis indicated that patients with chronic atrophic gastritis had an increased risk for CSVD than those without (adjusted odds ratio = 1.58; 95% CI, 1.08-2.32; P < 0.05). CONCLUSIONS: Chronic atrophic gastritis is associated with the presence of CSVD. We should routinely screen the presence of CSVD for patients with chronic atrophic gastritis.

Sensitive and specific detection of saccharide species based on fluorescence: update from 2016.

Increasing evidence supports the critical role of saccharides in various pathophysiological steps of tumor progression, where they regulate tumor proliferation, invasion, hematogenic metastasis, and angiogenesis. The identification and recognition of these saccharides provide a solid foundation for the development of targeted drug preparations, which are however not fully understood due to their complex and similar structures. In order to achieve fluorescence sensing of saccharides, extensive research has been conducted to design molecular probes and nanoparticles made of different materials. This paper aims to provide in-depth discussion of three main topics that cover the current status of the carbohydrate sensing based on the fluorescence sensing mechanism, including a phenylboronic acid-based sensing platform, non-boronic acid entities, as well as an enzyme-based sensing platform. It also highlights efforts made to understand the recognition mechanisms and improve the sensing properties of these systems. Finally, we present the challenge of achieving high selectivity and sensitivity recognition of saccharides, and suggest possible future avenues for exploration.

Uncovering the Novel Role of NR1D1 in Regulating BNIP3-Mediated Mitophagy in Ulcerative Colitis.

BACKGROUND: Ulcerative colitis (UC) is a chronic, incurable condition characterized by mucosal inflammation and intestinal epithelial cell (IEC) damage. The circadian clock gene NR1D1, implicated in UC and the critical mitophagy process for epithelial repair, needs further exploration regarding its role in mitophagy regulation in UC. METHODS: We created a jet lag mouse model and induced colitis with dextran sulfate sodium (DSS), investigating NR1D1's role. Intestinal-specific Nr1d1 knockout mice were also generated. RNA sequencing, chromatin immunoprecipitation (ChIP), and dual-luciferase reporter assays helped ascertain NR1D1's regulatory effect on BNIP3 expression. The mitochondrial state in IECs was assessed through transmission electron microscopy, while confocal microscopy evaluated mitophagy-associated protein expression in colon tissue and CCD841 cells. Cell apoptosis and reactive oxygen species (ROS) were measured via flow cytometry. RESULTS: We observed reduced NR1D1 expression in the IECs of UC patients, accentuated under jet lag and DSS exposure in mice. NR1D1 ablation led to disrupted immune homeostasis and declined mitophagy in IECs. NR1D1, usually a transcriptional repressor, was a positive regulator of BNIP3 expression, leading to impaired mitophagy, cellular inflammation, and apoptosis. Administering the NR1D1 agonist SR9009 ameliorated colitis symptoms, primarily by rectifying defective mitophagy. CONCLUSIONS: Our results suggest that NR1D1 bridges the circadian clock and UC, controlling BNIP3-mediated mitophagy and representing a potential therapeutic target. Its agonist, SR9009, shows promise in UC symptom alleviation.

Engineered Metallacycle-Based Supramolecular Photosensitizers for Effective Photodynamic Therapy.

Although metallacycle-based supramolecular photosensitizers (PSs) have attracted increasing attention in biomedicine, their clinical translation is still hindered by their inherent dark toxicity. Herein, we report what to our knowledge is the first example of a molecular engineering approach to building blocks of metallacycles for constructing a series of supramolecular PSs (RuA-RuD), with the aim of simultaneously reducing dark toxicity and enhancing phototoxicity, and consequently obtaining high phototoxicity indexes (PI). Detailed in vitro investigations demonstrate that RuA-RuD display high cancer cellular uptake and remarkable antitumor activity even under hypoxic conditions. Notably, RuD exhibited no dark toxicity and displayed the highest PI value (≈406). Theoretical calculations verified that RuD has the largest steric hindrance and the lowest singlet-triplet energy gap (ΔEST , 0.61 eV). Further in vivo studies confirmed that RuD allows safe and effective phototherapy against A549 tumors.

SERS Multiplex Profiling of Melanoma Circulating Tumor Cells for Predicting the Response to Immune Checkpoint Blockade Therapy.

Immune checkpoint blockade (ICB) therapy has achieved remarkable success in many cancers including melanoma. However, ICB therapy benefits only a small proportion of patients and produces severe side effects for some patients. Thus, there is an urgent need to identify patients who are more likely to respond to ICB therapy to improve outcomes and minimize side effects. To predict ICB therapy responses, we design a surface-enhanced Raman scattering (SERS) assay for multiplex profiling of circulating tumor cells (CTCs) under basal and interferon-γ (IFN-γ) stimulation. Through simultaneous ensemble and single-cell measurements of CTCs, the SERS assay can reveal tumor heterogeneity and offer a comprehensive CTC phenotype for decision-making. Anisotropic gold-silver alloy nanoboxes are utilized as SERS plasmonic substrates for improved signal readouts of CTC surface biomarkers. By generating a unique CTC signature with four surface biomarkers, the developed assay enables the differentiation of CTCs from three different patient-derived melanoma cell lines. Significantly, in a cohort of 14 melanoma patients who received programmed cell death-1 blockade therapy, the changes of CTC signature induced by IFN-γ stimulation to CTCs show the potential to predict responders. We expect that the SERS assay can help select patients for receiving ICB therapy in other cancers.

Detection of Dengue Virus 2 with Single Infected Mosquito Resolution Using Yeast Affinity Bionanofragments and Plasmonic SERS Nanoboxes.

Dengue disease is an emerging global threat triggered by dengue virus (DENV) transmission, primarily by the mosquito Aedes aegypti. The accurate surveillance and sensitive detection of DENV in mosquito populations are critical for the protection of human populations worldwide that are in the habitat of these mosquito species. There are four DENV serotypes with DENV2 reported to cause the most severe complications. There are limited ultrasensitive methods to early detect DENV2 mosquito infection and prevent human infection. Herein, we report an innovative nanobased immunoassay platform for early, specific, and ultrasensitive detection of DENV2-secreted nonstructural 1 (NS1) protein biomarker in single infected mosquitoes with the limit of detection of 500 fg of recombinant DENV2 NS1. The high sensitivity and DENV2 serotype specificity of the platform are the result of using nanomixing, plasmonic SERS nanoboxes, and yeast affinity bionanofragments displaying single-chain variable fragments (nanoyeast scFvs). Nanoyeast scFvs used for high affinity capture of DENV2 NS1 provided an innovative and cost-efficient alternative to monoclonal antibodies and differentiated DENV2 NS1 from other DENV serotypes and Zika virus NS1. The platform used electrohydrodynamically driven nanomixing to enhance NS1 capture by the nanoyeast scFvs while reducing nonspecific interactions. High sensitivity detection of captured DENV2 NS1 was achieved using NS1-specific surface-enhanced Raman scattering (SERS) nanotags. These nanotechnologies provide a significant innovation for early DENV2 detection in single infected mosquitoes, improving the accurate surveillance of mosquito habitats and preventing infection and severe disease arising from DENV2 transmission.