Unfolding Protein-Based Hapten Coupling via Thiol-Maleimide Click Chemistry: Enhanced Immunogenicity in Anti-Nicotine Vaccines Based on a Novel Conjugation Method and MPL/QS-21 Adjuvants.

Vaccines typically work by eliciting an immune response against larger antigens like polysaccharides or proteins. Small molecules like nicotine, on their own, usually cannot elicit a strong immune response. To overcome this, anti-nicotine vaccines often conjugate nicotine molecules to a carrier protein by carbodiimide crosslinking chemistry to make them polymeric and more immunogenic. The reaction is sensitive to conditions such as pH, temperature, and the concentration of reactants. Scaling up the reaction from laboratory to industrial scales while maintaining consistency and yield can be challenging. Despite various approaches, no licensed anti-nicotine vaccine has been approved so far due to the susboptimal antibody titers. Here, we report a novel approach to conjugate maleimide-modified nicotine hapten with a disulfide bond-reduced carrier protein in an organic solvent. It has two advantages compared with other approaches: (1) The protein was unfolded to make the peptide conformation more flexible and expose more conjugation sites; (2) thiol-maleimide "click" chemistry was utilized to conjugate the disulfide bond-reduced protein and maleimide-modified nicotine due to its availability, fast kinetics, and bio-orthogonality. Various nicotine conjugate vaccines were prepared via this strategy, and their immunology effects were investigated by using MPL and QS-21 as adjuvants. The in vivo study in mice showed that the nicotine-BSA conjugate vaccines induced high anti-nicotine IgG antibody titers, compared with vaccines prepared by using traditional condensation methods, indicating the success of the current strategy for further anti-nicotine or other small-molecule vaccine studies. The enhancement was more significant by using MPL and QS-21 than that of traditional aluminum adjuvants.

Harnessing the potential of de-sulfated heparin for targeted drug delivery: A three-component approach exemplified by conjugation with galactose and paclitaxel.

Heparin, an anticoagulant with a century-long history of use, has been investigated over the past decade as a potential drug delivery vehicle. Despite its safety and efficacy, its interactions with many proteins through specific sulfate patterns can complicate drug delivery by mediating diverse biological functions. Here, we present the synthesis of a three-component drug delivery system comprising de-sulfated heparin as the carrier, galactose as the targeting moiety, and paclitaxel as the therapeutic drug. Removal of sulfates eliminated most of its anticoagulant effects in all intermediates. Through coupling with galactose and paclitaxel, the system improved the solubility of the drug and achieved selective targeting and efficient drug delivery to HepG2 cells, a liver carcinoma cell line with high galactose receptor expression. While the three-component system exhibited a slightly higher IC50 value than native paclitaxel, demonstrating its efficacy as a drug carrier, the IC50 value for the normal human liver cell line QSG7701 was significantly higher, indicating its selectivity and safety. Our study introduces a novel approach utilizing desulfated heparin as a carrier, warranting further investigation to unlock its potential in targeted drug delivery strategies.

Deciphering adipose development: Function, differentiation and regulation.

The overdevelopment of adipose tissues, accompanied by excess lipid accumulation and energy storage, leads to adipose deposition and obesity. With the increasing incidence of obesity in recent years, obesity is becoming a major risk factor for human health, causing various relevant diseases (including hypertension, diabetes, osteoarthritis and cancers). Therefore, it is of significance to antagonize obesity to reduce the risk of obesity-related diseases. Excess lipid accumulation in adipose tissues is mediated by adipocyte hypertrophy (expansion of pre-existing adipocytes) or hyperplasia (increase of newly-formed adipocytes). It is necessary to prevent excessive accumulation of adipose tissues by controlling adipose development. Adipogenesis is exquisitely regulated by many factors in vivo and in vitro, including hormones, cytokines, gender and dietary components. The present review has concluded a comprehensive understanding of adipose development including its origin, classification, distribution, function, differentiation and molecular mechanisms underlying adipogenesis, which may provide potential therapeutic strategies for harnessing obesity without impairing adipose tissue function.

Strategic development of a self-adjuvanting SARS-CoV-2 RBD vaccine: From adjuvant screening to enhanced immunogenicity with a modified TLR7 agonist.

Adjuvants enhance the body's immune response to a vaccine, often leading to better protection against diseases. Monophosphoryl lipid A analogues (MPLA, TLR4 agonists), α-galactosylceramide analogues (NKT cell agonists), and imidazoquinoline compounds (TLR7/8 agonists) are emerging novel adjuvants on market or under clinical trials. Despite significant interest in these adjuvants, a direct comparison of their adjuvant activities remains unexplored. We initially assessed the activities of various adjuvants from three distinct categories using the SARS-CoV-2 RBD trimer antigen. TLR4 and TLR7/8 agonists are discovered to elicit robust IgG2a/2b antibodies, which is crucial for eliciting antibody dependent cytotoxicity. While α-galactosylceramide analogs induced mainly IgG1 antibody. Then, because of the flexibility of the TLR7/8 agonist, we designed and synthesized a tri-component self-adjuvanting SARS-CoV-2 RBD vaccine, featuring a covalent TLR7 agonist and targeting mannoside. Animal studies indicated that this vaccine generated antigen-specific humoral immunity. Yet, its immunogenicity seems compromised, indicating the complexity of the vaccine.

Macrophage depletion damages hematopoiesis partially through inhibition of cell homing and expansion after hematopoietic cell transplantation.

Bone marrow macrophages (Mφ) are essential components of the bone marrow niche that regulate the function of hematopoietic stem cells. Poor graft function and inhibition of hematopoietic production can result from abnormal macrophage function; however, the underlying mechanism is unclear. Clodronate liposomes (Clo-Lip) have been used widely to deplete macrophages and study their functions. Our previous results showed that Clod-Lip-mediated clearance of macrophages plays a vital role in regulating hematopoietic reconstruction after allogeneic hematopoietic cell transplantation (HCT). In this study, using an isogenic hematopoietic stem cell transplantation model, we found that Clod-Lip-mediated clearance of macrophages suppressed hematopoietic reconstruction by inhibiting the homing process of hematopoietic cells. We also demonstrated that macrophage depletion inhibited the direct supportive effect of macrophages on hematopoietic stem and progenitor cells and erythroid differentiation but promoted the production of megakaryocytic progenitors ex vivo. We showed that macrophages increase CD49e expression on hematopoietic stem and progenitor cells (HSPCs). However, CD49e inhibitors did not support the proliferative effect of macrophages on hematopoietic cells. In contrast, macrophage E-selectin/ intercellular cell adhesion molecule-1 (ICAM-1) may be involved in directly regulating HSPCs. In conclusion, macrophage depletion with Clo-Lip partially disrupts bone marrow hematopoiesis after HCT by impeding donor cell homing and macrophage-HSPCs interactions.

Red blood cell transfusion in neurocritical patients: a systematic review and meta-analysis.

BACKGROUND: Anemia can lead to secondary brain damage by reducing arterial oxygen content and brain oxygen supply. Patients with acute brain injury have impaired self-regulation. Brain hypoxia may also occur even in mild anemia. Red blood cell (RBC) transfusion is associated with increased postoperative complications, poor neurological recovery, and mortality in critically ill neurologic patients. Balancing the risks of anemia and red blood cell transfusion-associated adverse effects is challenging in neurocritical settings. METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL), Embase, and MEDLINE (PubMed) from inception to January 31, 2024. We included all randomized controlled trials (RCTs) assessing liberal versus restrictive RBC transfusion strategies in neurocritical patients. We included all relevant studies published in English. The primary outcome was mortality at intensive care unit (ICU), discharge, and six months. RESULTS: Of 5195 records retrieved, 84 full-text articles were reviewed, and five eligible studies were included. There was no significant difference between the restrictive and liberal transfusion groups in ICU mortality (RR: 2.53, 95% CI: 0.53 to 12.13), in-hospital mortality (RR: 2.34, 95% CI: 0.50 to 11.00), mortality at six months (RR: 1.42, 95% CI: 0.42 to 4.78) and long-term mortality (RR: 1.22, 95% CI: 0.64 to 2.33). The occurrence of neurological adverse events and most major non-neurological complications was similar in the two groups. The incidence of deep venous thrombosis was lower in the restrictive strategy group (RR: 0.41, 95% CI: 0.18 to 0.91). CONCLUSIONS: Due to the small sample size of current studies, the evidence is insufficiently robust to confirm definitive conclusions for neurocritical patients. Therefore, further investigation is encouraged to define appropriate RBC transfusion thresholds in the neurocritical setting.

Metabolites, Healthy Lifestyle, and Polygenic Risk Score Associated with Upper Gastrointestinal Cancer: Findings from the UK Biobank Study.

Previous metabolomics studies have highlighted the predictive value of metabolites on upper gastrointestinal (UGI) cancer, while most of them ignored the potential effects of lifestyle and genetic risk on plasma metabolites. This study aimed to evaluate the role of lifestyle and genetic risk in the metabolic mechanism of UGI cancer. Differential metabolites of UGI cancer were identified using partial least-squares discriminant analysis and the Wilcoxon test. Then, we calculated the healthy lifestyle index (HLI) score and polygenic risk score (PRS) and divided them into three groups, respectively. A total of 15 metabolites were identified as UGI-cancer-related differential metabolites. The metabolite model (AUC = 0.699) exhibited superior discrimination ability compared to those of the HLI model (AUC = 0.615) and the PRS model (AUC = 0.593). Moreover, subgroup analysis revealed that the metabolite model showed higher discrimination ability for individuals with unhealthy lifestyles compared to that with healthy individuals (AUC = 0.783 vs 0.684). Furthermore, in the genetic risk subgroup analysis, individuals with a genetic predisposition to UGI cancer exhibited the best discriminative performance in the metabolite model (AUC = 0.770). These findings demonstrated the clinical significance of metabolic biomarkers in UGI cancer discrimination, especially in individuals with unhealthy lifestyles and a high genetic risk.

Laboratory Experiments of Hydrocarbon Gas Flooding and Its Influencing Factors on Oil Recovery in a Low Permeability Reservoir with Medium Viscous Oil.

In view of the problems of low liquid production, a high proportion of high water cut wells, and poor development effect in the late stage of water flooding in the special sandstone reservoir of Niuquanhu "low permeability and medium viscosity crude oil", we carried out the research on hydrocarbon gas oil recovery and its influencing factors. First, the influence of different injected gas media on the physical properties of crude oil was analyzed. Second, the core displacement experiments of different gas injection media including CO2, CH4, and hydrocarbon gas were carried out by using the method of oil recovery comparison and optimization. Third, the indoor experimental study on the oil recovery of different influencing factors was carried out by using the method of controlling variables of influencing factors. Finally, the influence degree of different influencing factors on oil recovery was analyzed by a Spearman rank correlation coefficient analysis. The experimental results showed that the oil recovery of hydrocarbon gas is higher than that of CO2 and CH4, which were 57, 51, and 18% respectively. This is mainly because hydrocarbon gas is similar to the components of crude oil and is more easily dissolved in crude oil. The experimental results of influencing factors showed that the higher the content of C2-C4, the higher the oil recovery, and the content of C2-C4 will affect its dissolution with crude oil and its interaction with heavy component crude oil. The larger the permeability ratio, the lower the oil recovery, which was mainly due to the uneven distribution of injected gas in different regions. The higher the permeability, the lower the oil recovery, which was also due to the serious heterogeneity of the low permeability core of Niuquanhu; The results of Spearman rank correlation coefficient analysis based on different influencing factors and oil recovery showed that the order of influence of different factors on oil recovery was C2-C4 content > permeability ratio > permeability > back pressure > gas injection rate. In the development process of hydrocarbon gas injection, we should control the C2-C4 content, back pressure, and injection rate. The research in this study not only provides theoretical support for gas injection enhanced oil recovery technology in "low permeability and medium viscosity crude oil" reservoirs but also provides a new idea for the ranking of influencing factors.

Epidemiological features and a survival nomogram for primary lymphoma of the male genital tract.

Primary lymphoma of the male genital tract (PLMGT) is rare, and data on its epidemiology and prognosis are lacking. Our study aimed to estimate the incidence and develop a predictive nomogram for PLMGT. We pooled the incidence and survival data of PLMGT over the last 20 years from the Surveillance, Epidemiology, and End Results (SEER) database. Incidence rates were calculated by year of diagnosis, age, race, and histology. Independent prognostic factors selected by Cox regression analysis were used to develop a nomogram for predicting overall survival (OS). Our study enrolled 1312 patients with PLMGT. The overall incidence rate of PLMGT was 0.437/1,000,000 during 2000-2019. OS was associated with age, marital status, histological subtype, Ann Arbor stage, and therapeutic strategy, which were used to construct nomograms to predict 1-, 3-, and 5-year OS rates. Receiver operating characteristic curves, calibration plots, and decision curve analysis showed good performance of the nomogram. Based on the total score of each patient from the nomogram, the patients were clustered into three risk groups, and the risk stratification model was more successful in predicting clinical outcomes than the traditional Ann Arbor staging system. The incidence rate of PLMGT has remained relatively stable over the past two decades. For the OS of patients with PLMGT, we established a novel predictive nomogram involving all independent risk factors obtained from the SEER database and developed a corresponding risk classification system that showed better predictive performance than the Ann Arbor staging system.

Entry point of machine learning in axial spondyloarthritis.

Axial spondyloarthritis (axSpA) is a globally prevalent and challenging autoimmune disease. Characterised by insidious onset and slow progression, the absence of specific clinical manifestations and biomarkers often leads to misdiagnosis, thereby complicating early detection and diagnosis of axSpA. Furthermore, the high heterogeneity of axSpA, its complex pathogenesis and the lack of specific drugs means that traditional classification standards and treatment guidelines struggle to meet the demands of personalised treatment. Recently, machine learning (ML) has seen rapid advancements in the medical field. By integrating large-scale data with diverse algorithms and using multidimensional data, such as patient medical records, laboratory examinations, radiological data, drug usage and molecular biology information, ML can be modelled based on real-world clinical issues. This enables the diagnosis, stratification, therapeutic efficacy prediction and prognostic evaluation of axSpA, positioning it as an emerging research topic. This study explored the application and progression of ML in the diagnosis and therapy of axSpA from five perspectives: early diagnosis, stratification, disease monitoring, drug efficacy evaluation and comorbidity prediction. This study aimed to provide a novel direction for exploring rational diagnostic and therapeutic strategies for axSpA.

Gut microbiome for predicting immune checkpoint blockade-associated adverse events.

BACKGROUND: The impact of the gut microbiome on the initiation and intensity of immune-related adverse events (irAEs) prompted by immune checkpoint inhibitors (ICIs) is widely acknowledged. Nevertheless, there is inconsistency in the gut microbial associations with irAEs reported across various studies. METHODS: We performed a comprehensive analysis leveraging a dataset that included published microbiome data (n = 317) and in-house generated data from 16S rRNA and shotgun metagenome samples of irAEs (n = 115). We utilized a machine learning-based approach, specifically the Random Forest (RF) algorithm, to construct a microbiome-based classifier capable of distinguishing between non-irAEs and irAEs. Additionally, we conducted a comprehensive analysis, integrating transcriptome and metagenome profiling, to explore potential underlying mechanisms. RESULTS: We identified specific microbial species capable of distinguishing between patients experiencing irAEs and non-irAEs. The RF classifier, developed using 14 microbial features, demonstrated robust discriminatory power between non-irAEs and irAEs (AUC = 0.88). Moreover, the predictive score from our classifier exhibited significant discriminative capability for identifying non-irAEs in two independent cohorts. Our functional analysis revealed that the altered microbiome in non-irAEs was characterized by an increased menaquinone biosynthesis, accompanied by elevated expression of rate-limiting enzymes menH and menC. Targeted metabolomics analysis further highlighted a notably higher abundance of menaquinone in the serum of patients who did not develop irAEs compared to the irAEs group. CONCLUSIONS: Our study underscores the potential of microbial biomarkers for predicting the onset of irAEs and highlights menaquinone, a metabolite derived from the microbiome community, as a possible selective therapeutic agent for modulating the occurrence of irAEs.

PAFAH2 suppresses synchronized ferroptosis to ameliorate acute kidney injury.

Synchronized ferroptosis contributes to nephron loss in acute kidney injury (AKI). However, the propagation signals and the underlying mechanisms of the synchronized ferroptosis for renal tubular injury remain unresolved. Here we report that platelet-activating factor (PAF) and PAF-like phospholipids (PAF-LPLs) mediated synchronized ferroptosis and contributed to AKI. The emergence of PAF and PAF-LPLs in ferroptosis caused the instability of biomembranes and signaled the cell death of neighboring cells. This cascade could be suppressed by PAF-acetylhydrolase (II) (PAFAH2) or by addition of antibodies against PAF. Genetic knockout or pharmacological inhibition of PAFAH2 increased PAF production, augmented synchronized ferroptosis and exacerbated ischemia/reperfusion (I/R)-induced AKI. Notably, intravenous administration of wild-type PAFAH2 protein, but not its enzymatically inactive mutants, prevented synchronized tubular cell death, nephron loss and AKI. Our findings offer an insight into the mechanisms of synchronized ferroptosis and suggest a possibility for the preventive intervention of AKI.

Dual Tumor-Selective ß-Carboline-Based Fluorescent Probe for High-Contrast/Rapid Diagnosis of Clinical Tumor Tissues.

Given that precise/rapid intraoperative tumor margin identification is still challenging, novel fluorescent probes HY and HYM, based on acidic tumor microenvironment (TME) activation and organic anion transporting polypeptide (OATPs)-mediated selective uptake, were constructed and synthesized. Both of them possessed acidic pH-activatable and reversible fluorescence as well as large Stokes shift. Compared with HY, HYM had a higher (over 9-fold) enhancement in fluorescence with pH ranging from 7.6 to 4.0, and the fluorescence quantum yield of HYM (ΦF = 0.49) at pH = 4.0 was 8-fold stronger than that (ΦF = 0.06) at pH = 7.4. Mechanism research demonstrated that acidic TME-induced protonation of the pyridine N atom on ß-carbolines accounted for the pH-sensitive fluorescence by influencing the intramolecular charge transfer (ICT) effect. Furthermore, HYM selectively lit up cancer cells and tumor tissues not only by "off-on" fluorescence but also by OATPs (overexpressed on cancer cells)-mediated cancer cellular internalization, offering dual tumor selectivity for precise visualization of tumor mass and intraoperative guidance upon in situ spraying. Most importantly, HYM enabled rapid and high-contrast (tumor-to-normal tissue ratios > 6) human tumor margin identification in clinical tumor tissues by simple spraying within 6 min, being promising for aiding in clinical surgical resection.

Construction of an acute myeloid leukemia prognostic model based on m6A-related efferocytosis-related genes.

Background: One of the most prevalent hematological system cancers is acute myeloid leukemia (AML). Efferocytosis-related genes (ERGs) and N6-methyladenosine (m6A) have an important significance in the progression of cancer, and the metastasis of tumors. Methods: The AML-related data were collected from The Cancer Genome Atlas (TCGA; TCGA-AML) database and Gene Expression Omnibus (GEO; GSE9476, GSE71014, and GSE13159) database. The "limma" R package and Venn diagram were adopted to identify differentially expressed ERGs (DE-ERGs). The m6A related-DE-ERGs were obtained by Spearman analysis. Subsequently, univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) were used to construct an m6A related-ERGs risk signature for AML patients. The possibility of immunotherapy for AML was explored. The pRRophetic package was adopted to calculate the IC50 of drugs for the treatment of AML. Finally, the expression of characterized genes was validated by quantitative reverse transcription-PCR (qRT-PCR). Results: Based on m6A related-DE-ERGs, a prognostic model with four characteristic genes (UCP2, DOCK1, SLC14A1, and SLC25A1) was constructed. The risk score of model was significantly associated with the immune microenvironment of AML, with four immune cell types, 14 immune checkpoints, 20 HLA family genes and, immunophenoscore (IPS) all showing differences between the high- and low-risk groups. A total of 56 drugs were predicted to differ between the two groups, of which Erlotinib, Dasatinib, BI.2536, and bortezomib have been reported to be associated with AML treatment. The qRT-PCR results showed that the expression trends of DOCK1, SLC14A1 and SLC25A1 were consistent with the bioinformatics analysis. Conclusion: In summary, 4 m6A related- ERGs were identified and the corresponding prognostic model was constructed for AML patients. This prognostic model effectively stratified the risk of AML patients.

Untargeted serum metabolomics reveals potential biomarkers and metabolic pathways associated with the progression of gastroesophageal cancer.

BACKGROUND: Previous metabolic studies in upper digestive cancer have mostly been limited to cross-sectional study designs, which hinders the ability to effectively predict outcomes in the early stage of cancer. This study aims to identify key metabolites and metabolic pathways associated with the multistage progression of epithelial cancer and to explore their predictive value for gastroesophageal cancer (GEC) formation and for the early screening of esophageal squamous cell carcinoma (ESCC). METHODS: A case-cohort study within the 7-year prospective Esophageal Cancer Screening Cohort of Shandong Province included 77 GEC cases and 77 sub-cohort individuals. Untargeted metabolic analysis was performed in serum samples. Metabolites, with FDR q value < 0.05 and variable importance in projection (VIP) > 1, were selected as differential metabolites to predict GEC formation using Random Forest (RF) models. Subsequently, we evaluated the predictive performance of these differential metabolites for the early screening of ESCC. RESULTS: We found a distinct metabolic profile alteration in GEC cases compared to the sub-cohort, and identified eight differential metabolites. Pathway analyses showed dysregulation in D-glutamine and D-glutamate metabolism, nitrogen metabolism, primary bile acid biosynthesis, and steroid hormone biosynthesis in GEC patients. A panel of eight differential metabolites showed good predictive performance for GEC formation, with an area under the receiver operating characteristic curve (AUC) of 0.893 (95% CI = 0.816-0.951). Furthermore, four of the GEC pathological progression-related metabolites were validated in the early screening of ESCC, with an AUC of 0.761 (95% CI = 0.716-0.805). CONCLUSIONS: These findings indicated a panel of metabolites might be an alternative approach to predict GEC formation, and therefore have the potential to mitigate the risk of cancer progression at the early stage of GEC.

Multi-kingdom gut microbiota analyses define bacterial-fungal interplay and microbial markers of pan-cancer immunotherapy across cohorts.

The effect of gut bacteria on the response to immune checkpoint inhibitors (ICIs) has been studied, but the relationship between fungi and ICI responses is not fully understood. Herein, 862 fecal metagenomes from 9 different cohorts were integrated for the identification of differentially abundant fungi and subsequent construction of random forest (RF) models to predict ICI responses. Fungal markers demonstrate excellent performance, with an average area under the curve (AUC) of 0.87. Their performance improves even further, reaching an average AUC of 0.89 when combined with bacterial markers. Higher enrichment of exhausted T cells is detected in responders, as predicted by fungal markers. Multi-kingdom network and functional analysis reveal that the fungus Schizosaccharomyces octosporus may ferment starch into short-chain fatty acids in responders. This study provides a fungal profile of the ICI response and the identification of multi-kingdom microbial markers with good performance that may improve the overall applicability of ICI therapy.

In Situ Preparation of Polyamine-Derived Ru Cluster@N-Doped Porous Carbon Nanoplates for Hydrogen Evolution over Wide pH Ranges.

Efficient and low-cost electrocatalysts for the hydrogen evolution reaction (HER) are required for producing hydrogen energy through water splitting. Carbon materials as HER catalyst supports are explored widely since the strong metal-support interactions are generally believed to be active and stable toward HER. Herein, we report N-doped porous carbon materials as novel substrates to stabilize the cluster metal sites through the Ru(III) polyamine complexes, which play an important role not only in efficient electron transfer but also in the increasing utilization of metallic active sites. Meanwhile, due to the strong metal-support interactions driven by Ru(III) polyamine complexes, the obtained Ru cluster with a mass loading of 3% on N-doped porous carbon nanoplates (Ru cluster@NCs) exhibits robust stability for HER at a constant voltage, proving to be a promising candidate catalyst for HER. Density functional theory calculations further indicate that the Gibbs free energy (ΔG) of adsorbed H* of Ru cluster@NCs is much closer to zero compared to Ru@(10%)NCs and Pt/C(20%), thus Ru cluster@NCs facilitate the HER process.

Precise tumor delineation in clinical tissues using a novel acidic tumor microenvironment activatable near-infrared fluorescent contrast agent.

Tumor selective near-infrared (NIR) fluorescent contrast agents has the potential to greatly enhance the efficiency and precision of tumor surgery by enabling real-time tumor margin identification for tumor resection guided by imaging. However, the development of these agents is still challenging. In this study, based on the acidic tumor microenvironment (TME), we designed and synthesized a novel pH-sensitive NIR fluorescent contrast agent OBD from ß-carboline. The fluorescence quantum yield of OBD exhibited a notable increase at pH 3.6, approximately 12-fold higher compared to its value at pH 7.4. After cellular uptake, OBD lighted up the cancer cells with high specificity and accumulated in the mitochondria. Spraying OBD emitted selective fluorescence in xenograft tumor tissues with tumor-to-normal tissue ratios (TNR) as high as 11.18, implying successful image-guided surgery. Furthermore, OBD was also shown to track metastasis in spray mode. After simple topical spray, OBD rapidly and precisely visualized the tumor margins of clinical colon and liver tissues with TNR over 4.2. Therefore, the small-molecule fluorescent contrast agent OBD has promising clinical applications in tumor identification during surgery.