Serum Metabolic Fingerprints on Bowl-Shaped Submicroreactor Chip for Chemotherapy Monitoring

Engineering a Bifunctional Smart Nanoplatform Integrating Nanozyme Activity and Self-Assembly for Kidney Cancer Diagnosis and Classification

Accurate diagnosis and classification of kidney cancer are crucial for high-quality healthcare services. However, the current diagnostic platforms remain challenges in the rapid and accurate analysis of large-scale clinical biosamples. Herein, we fabricated a bifunctional smart nanoplatform based on tannic acid-modified gold nanoflowers (TA@AuNFs), integrating nanozyme catalysis for colorimetric sensing and self-assembled nanoarray-assisted LDI-MS analysis. The TA@AuNFs presented peroxidase (POD)- and glucose oxidase-like activity owing to the abundant galloyl residues on the surface of AuNFs. Combined with the colorimetric assay, the TA@AuNF-based sensing nanoplatform was used to directly detect glucose in serum for kidney tumor diagnosis. On the other hand, TA@AuNFs could self-assemble into closely packed and homogeneous two-dimensional (2D) nanoarrays at liquid-liquid interfaces by using Fe3+ as a mediator. The self-assembled TA@AuNFs (SA-TA@AuNFs) arrays were applied to assist the LDI-MS analysis of metabolites, exhibiting high ionization efficiency and excellent MS signal reproducibility. Based on the SA-TA@AuNF array-assisted LDI-MS platform, we successfully extracted metabolic fingerprints from urine samples, achieving early-stage diagnosis of kidney tumor, subtype classification, and discrimination of benign from malignant tumors. Taken together, our developed TA@AuNF-based bifunctional smart nanoplatform showed distinguished potential in clinical disease diagnosis, point-of-care testing, and biomarker discovery.

AIBI Modified Mesoporous Copper Sulfide Nanocomposites for Efficient Non-Oxygen Dependent Free Radicals-Assisted Photothermal Therapy in Uveal Melanoma

Uveal melanoma (UM) is an ocular cancer predominantly affecting adults, characterized by challenging diagnostic outcomes. This research endeavors to develop an innovative multifunctional nanocomposite system sensitive to near-infrared (NIR) radiation, serving as both a non-oxygen free-radical generator and a photothermal agent. The designed system combines azobis isobutyl imidazoline hydrochloride (AIBI) with mesoporous copper sulfide (MCuS) nanoparticles. MCuS harnesses NIR laser energy to induce photothermal therapy, converting light energy into heat to destroy cancer cells. Simultaneously, AIBI is activated by the NIR laser to produce alkyl radicals, which induce DNA damage in remaining cancer cells. This distinctive feature equips the designed system to selectively eliminate cancers in the hypoxic tumor microenvironment. MCuS is also beneficial to scavenge the overexpressed glutathione (GSH) in the tumor microenvironment. GSH generally consumes free radicals and hiders the PDT effect. To enhance control over AIBI release in cancer cells, 1-tetradecyl alcohol (TD), a phase-changing material, is introduced onto the surface of MCuS nanoparticles to create the final AMPT nanoparticle system. In vitro and in vivo experiments confirm the remarkable anti-tumor efficacy of AMPT. Notably, the study introduces an orthotopic tumor model for UM, demonstrating the feasibility of precise and effective targeted treatment within the ocular system.

A Targeted and Responsive Nanoprodrug Delivery System for Synergistic Glioma Chemotherapy

Doxorubicin (DOX) is widely used as a chemotherapeutic agent for both hematologic and solid tumors and is a reasonable candidate for glioma treatment. However, its effectiveness is hindered by significant toxicity and drug resistance. Moreover, the presence of the blood-brain barrier (BBB) brings a crucial challenge to glioma therapy. In response, a GSH-responsive and actively targeted nanoprodrug delivery system (cRGD/PSDOX-Cur@NPs) are developed. In this system, a disulfide bond-bridged DOX prodrug (PEG-SS-DOX) is designed to release specifically in the high glutathione (GSH) tumor environment, markedly reducing the cardiotoxicity associated with DOX. To further address DOX resistance, curcumin, serving as a P-glycoprotein (P-gp) inhibitor, effectively increased cellular DOX concentration. Consequently, cRGD/PSDOX-Cur@NPs exhibited synergistic anti-tumor effects in vitro. Furthermore, in vivo experiments validated the superior BBB penetration and brain-targeting abilities of cRGD/PSDOX-Cur@NPs, showcasing the remarkable potential for treating both subcutaneous and orthotopic gliomas. This research underscores that this nanoprodrug delivery system presents a novel approach to inhibiting glioma while addressing resistance and systemic toxicity.

Optimizing perampanel monotherapy for surgically resected brain tumors

Perampanel (PER) is an antiseizure medication (ASM) with a unique mechanism of action, which was approved in Japan for use in combination therapy in 2016 and as a monotherapy in 2020. It has exerted antitumor effects against several types of tumors in vitro. However, the efficacy of PER monotherapy for seizure control is not well-established in patients with brain tumor. In the present study, 25 patients with brain tumor treated using PER monotherapy at our institution were analyzed and compared with 45 patients treated using the most commonly prescribed ASM, levetiracetam (LEV). The PER group was younger and had a higher frequency of glioma cases. During drug administration, seizures were observed in two patients from the PER group (8.0%) and five patients from the LEV group (11.1%); however, the difference was not significant. The incidence of adverse effects did not significantly differ between the groups (12.0 and 2.2%, respectively). In the PER group, mild liver dysfunction was observed in two patients and drug rash in one. In the LEV group, a drug-induced rash was observed in one patient. PER monotherapy may be safe and effective for seizure treatment or prophylaxis in patients with brain tumor. Further large-scale clinical studies are warranted.

Early Diagnosis and Prognosis Prediction of Pancreatic Cancer Using Engineered Hybrid Core-Shells in Laser Desorption/Ionization Mass Spectrometry

Effective detection of bio-molecules relies on the precise design and preparation of materials, particularly in laser desorption/ionization mass spectrometry (LDI-MS). Despite significant advancements in substrate materials, the performance of single-structured substrates remains suboptimal for LDI-MS analysis of complex systems. Herein, designer Au@SiO2@ZrO2 core-shell substrates are developed for LDI-MS-based early diagnosis and prognosis of pancreatic cancer (PC). Through controlling Au core size and ZrO2 shell crystallization, signal amplification of metabolites up to 3 orders is not only achieved, but also the synergistic mechanism of the LDI process is revealed. The optimized Au@SiO2@ZrO2 enables a direct record of serum metabolic fingerprints (SMFs) by LDI-MS. Subsequently, SMFs are employed to distinguish early PC (stage I/II) from controls, with an accuracy of 92%. Moreover, a prognostic prediction scoring system is established with enhanced efficacy in predicting PC survival compared to CA19-9 (p < 0.05). This work contributes to material-based cancer diagnosis and prognosis.

Tumor hyperthermia research progress and application prospect in tumoroids (Review)

Tumor hyperthermia is the fifth tumor treatment method after surgery, chemotherapy, radiotherapy and biological therapy, and is also one of the important adjuvant treatment methods for tumors. Hyperthermia can not only directly eliminate tumor cells, but also stimulate the antitumor immune response of the body, and improve the sensitivity of tumor tissues to radiotherapy and chemotherapy. An organoid is a tissue-specific cell cluster formed by 3D culture of various types of cells derived from target organ stem cells, which can reproduce the functions of target organs in vivo. At present, the research models of hepatocellular carcinoma (HCC) in vitro are mainly 2D culture cell line models, and there is no clinical report on tumor hyperthermia using HCC tumoroids. It was hypothesized that this will be a promising research direction.

Fast Label-Free Metabolic Profile Recognition Identifies Phenylketonuria and Subtypes

Phenylketonuria (PKU) is the most common inherited metabolic disease in humans. Clinical screening of newborn heel blood samples for PKU is costly and time-consuming because it requires multiple procedures, like isotope labeling and derivatization, and PKU subtype identification requires an additional urine sample. Delayed diagnosis of PKU, or subtype identification can result in mental disability. Here, plasmonic silver nanoshells are used for laser desorption/ionization mass spectrometry (MS) detection of PKU with label-free assay by recognizing metabolic profile in dried blood spot (DBS) samples. A total of 1100 subjects are recruited and each DBS sample can be processed in seconds. This platform achieves PKU screening with a sensitivity of 0.985 and specificity of 0.995, which is comparable to existing clinical liquid chromatography MS (LC-MS) methods. This method can process 360 samples per hour, compared with the LC-MS method which processes only 30 samples per hour. Moreover, this assay enables precise identification of PKU subtypes without the need for a urine sample. It is demonstrated that this platform enables high-performance and fast, low-cost PKU screening and subtype identification. This approach might be suitable for the detection of other clinically relevant biomarkers in blood or other clinical samples.

Alpha-Emitter Radium-223 Induces STING-Dependent Pyroptosis to Trigger Robust Antitumor Immunity

Radium-223 (223 Ra) is the first-in-class alpha-emitter to mediate tumor eradication, which is commonly thought to kill tumor cells by directly cleaving double-strand DNA. However, the immunogenic characteristics and cell death modalities triggered by 223 Ra remain unclear. Here, it is reported that the 223 Ra irradiation induces the pro-inflammatory damage-associated molecular patterns including calreticulin, HMGB1, and HSP70, hallmarks of tumor immunogenicity. Moreover, therapeutic 223 Ra retards tumor progression by triggering pyroptosis, an immunogenic cell death. Mechanically, 223 Ra-induced DNA damage leads to the activation of stimulator of interferon genes (STING)-mediated DNA sensing pathway, which is critical for NLRP3 inflammasome-dependent pyroptosis and subsequent DCs maturation as well as T cell activation. These findings establish an essential role of STING in mediating alpha-emitter 223 Ra-induced antitumor immunity, which provides the basis for the development of novel cancer therapeutic strategies and combinatory therapy.

Remotely Controllable Supramolecular Nanomedicine for Drug-Resistant Colorectal Cancer Therapy Caused by Fusobacterium nucleatum

Fusobacterium nucleatum (Fn) existing in the community of colorectal cancer (CRC) promotes CRC progression and causes chemotherapy resistance. Despite great efforts that have been made to overcome Fn-induced chemotherapy resistance by co-delivering antibacterial agents and chemotherapeutic drugs, increasing the drug-loading capacity and enabling controlled release of drugs remain challenging. In this study, a novel supramolecular upconversion nanoparticle (SUNP) is constructed by incorporating a positively charged polymer (PAMAM-LA-CD) with Fn inhibition capacity, a negatively charged platinum (IV) oxaliplatin prodrug (OXA-COOH), upconversion nanoparticle (UCNPs) and polyethylene glycol-azobenzene (PEG-Azo) to enhance drug-loading and enable on-demand drug release for drug-resistant CRC treatment. SUNPs exhibit high drug-loading capacity (30.8%) and good structural stability under normal physiological conditions, while disassembled upon exogenous NIR excitation and endogenous azo reductase in the CRC microenvironment to trigger drug release. In vitro and in vivo studies demonstrate that SUNPs presented good biocompatibility and robust performance to overcome chemoresistance, thereby significantly inhibiting Fn-infected cancer cell proliferation. This study leverages multiple dynamic chemical designs to integrate both advantages of drug loading and release in a single system, which provides a promising candidate for precision therapy of bacterial-related drug-resistant cancers.

Ailanthone induces autophagy and ferroptosis in non‑small cell lung cancer Lewis cells

Ailanthone (AIL), a monomer derived from ailanthus in Chinese medicine, has been demonstrated to have antitumor effects, albeit the underlying mechanism is unknown. Autophagy and ferroptosis are two modes of cell death that have been championed as potential mechanisms implicated in the antitumor effects of various drugs. The present study demonstrated that AIL effectively suppresses the Lewis cell proliferation in non-small cell lung cancer using MTT and colony formation assays. Autophagy and ferroptosis were verified using western blotting, immunofluorescence and ferroptosis detection. Additionally, the findings revealed that regulating the AMPK/mTOR/p70S6k signaling pathway may be the underlying mechanism for the antitumor effect of AIL. The present study established a theoretical foundation for further research into the utilization of AIL as a novel antitumor approach.

Plasmonic Alloys Enhanced Metabolic Fingerprints for the Diagnosis of COPD and Exacerbations

Accurate diagnosis of chronic obstructive pulmonary disease (COPD) and exacerbations by metabolic biomarkers enables individualized treatment. Advanced metabolic detection platforms rely on designed materials. Here, we design mesoporous PdPt alloys to characterize metabolic fingerprints for diagnosing COPD and exacerbations. As a result, the optimized PdPt alloys enable the acquisition of metabolic fingerprints within seconds, requiring only 0.5 μL of native plasma by laser desorption/ionization mass spectrometry owing to the enhanced electric field, photothermal conversion, and photocurrent response. Machine learning decodes metabolic profiles acquired from 431 individuals, achieving a precise diagnosis of COPD with an area under the curve (AUC) of 0.904 and an accurate distinction between stable COPD and acute exacerbations of COPD (AECOPD) with an AUC of 0.951. Notably, eight metabolic biomarkers identified accurately discriminate AECOPD from stable COPD while providing valuable information on disease progress. Our platform will offer an advanced nanoplatform for the management of COPD, complementing standard clinical techniques.

Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring

Liquid biopsy, a novel detection method, has recently become an active research area in clinical cancer owing to its unique advantages. Studies on circulating free DNA, circulating tumor cells, and exosomes obtained by liquid biopsy have shown great advances and they have entered clinical practice as new cancer biomarkers. The metabolism of the body is dynamic as cancer originates and progresses. Metabolic abnormalities caused by cancer can be detected in the blood, sputum, urine, and other biological fluids via systemic or local circulation. A considerable number of recent studies have focused on the roles of metabolic molecules in cancer. The purpose of this review is to provide an overview of metabolic markers from various biological fluids in the latest clinical studies, which may contribute to cancer screening and diagnosis, differentiation of cancer typing, grading and staging, and prediction of therapeutic response and prognosis.

Recent Progress in Phage-Based Nanoplatforms for Tumor Therapy

Nanodrug delivery systems have demonstrated a great potential for tumor therapy with the development of nanotechnology. Nonetheless, traditional drug delivery systems are faced with issues such as complex synthetic procedures, low reproducibility, nonspecific distribution, impenetrability of biological barrier, systemic toxicity, etc. In recent years, phage-based nanoplatforms have attracted increasing attention in tumor treatment for their regular structure, fantastic carrying property, high transduction efficiency and biosafety. Notably, therapeutic or targeting peptides can be expressed on the surface of the phages through phage display technology, enabling the phage vectors to possess multifunctions. As a result, the drug delivery efficiency on tumor will be vastly improved, thereby enhancing the therapeutic efficacy while reducing the side effects on normal tissues. Moreover, phages can overcome the hindrance of biofilm barrier to elicit antitumor effects, which exhibit great advantages compared with traditional synthetic drug delivery systems. Herein, this review not only summarizes the structure and biology of the phages, but also presents their potential as prominent nanoplatforms against tumor in different pathways to inspire the development of effective nanomedicine.

Self-Assembled Hyperbranched Gold Nanoarrays Decode Serum United Urine Metabolic Fingerprints for Kidney Tumor Diagnosis

Serum united urine metabolic analysis comprehensively reveals the disease status for kidney diseases in particular. Thus, the precise and convenient acquisition of metabolic molecular information from united biofluids is vitally important for clinical disease diagnosis and biomarker discovery. Laser desorption/ionization mass spectrometry (LDI-MS) presents various advantages in metabolic analysis; however, there remain challenges in ionization efficiency and MS signal reproducibility. Herein, we constructed a self-assembled hyperbranched black gold nanoarray (HyBrAuNA) assisted LDI-MS platform to profile serum united urine metabolic fingerprints (S-UMFs) for diagnosis of early stage renal cell carcinoma (RCC). The closely packed HyBrAuNA afforded strong electromagnetic field enhancement and high photothermal conversion efficacy, enabling effective ionization of low abundant metabolites for S-UMF collection. With a uniform nanoarray, the platform presented excellent reproducibility to ensure the accuracy of S-UMFs obtained in seconds. When it was combined with automated machine learning analysis of S-UMFs, early stage RCC patients were discriminated from the healthy controls with an area under the curve (AUC) > 0.99. Furthermore, we screened out a panel of 9 metabolites (4 from serum and 5 from urine) and related pathways toward early stage kidney tumor. In view of its high-throughput, fast analytical speed, and low sample consumption, our platform possesses potential in metabolic profiling of united biofluids for disease diagnosis and pathogenic mechanism exploration.

Simultaneous Detection of Aldehyde Metabolites by Light-Assisted Ambient Ionization Mass Spectrometry

In the clinic, small-molecule metabolites (SMMs) in blood are highly convincing indicators for disease diagnosis, such as cancer. However, challenges still exist for detection of SMMs due to their low concentration and complicated components in blood. In this work, we report the design of a novel "selenium signature" nanoprobe (Se nanoprobe) for efficient identification of multiple aldehyde metabolites in blood. This Se nanoprobe consists of magnetic nanoparticles that can enrich aldehyde metabolites from a complex environment, functionalized with photosensitive "selenium signature" hydrazide molecules that can react with aldehyde metabolites. Upon irradiation with UV, the aldehyde derivatives can be released from the Se nanoprobe and further sprayed by mass spectrometry through ambient ionization (AIMS). By quantifying the selenium isotope distribution (MS/MS) from the derivatization product, accurate detection of several aldehyde metabolites, including valeraldehyde (Val), heptaldehyde (Hep), 2-furaldehyde (2-Fur), 10-undecenal aldehyde (10-Und), and benzaldehyde (Ben), is realized. This strategy reveals a new solution for quick and accurate cancer diagnosis in the clinic.

Stimuli-Responsive Nanoradiosensitizers for Enhanced Cancer Radiotherapy

Radiotherapy (RT) has been a classical therapeutic method of cancer for several decades. It attracts tremendous attention for the precise and efficient treatment of local tumors with stimuli-responsive nanomaterials, which enhance RT. However, there are few systematic reviews summarizing the newly emerging stimuli-responsive mechanisms and strategies used for tumor radio-sensitization. Hence, this review provides a comprehensive overview of recently reported studies on stimuli-responsive nanomaterials for radio-sensitization. It includes four different approaches for sensitized RT, namely endogenous response, exogenous response, dual stimuli-response, and multi stimuli-response. Endogenous response involves various stimuli such as pH, hypoxia, GSH, and reactive oxygen species (ROS), and enzymes. On the other hand, exogenous response encompasses X-ray, light, and ultrasound. Dual stimuli-response combines pH/enzyme, pH/ultrasound, and ROS/light. Lastly, multi stimuli-response involves the combination of pH/ROS/GSH and X-ray/ROS/GSH. By elaborating on these responsive mechanisms and applying them to clinical RT diagnosis and treatment, these methods can enhance radiosensitive efficiency and minimize damage to surrounding normal tissues. Finally, this review discusses the additional challenges and perspectives related to stimuli-responsive nanomaterials for tumor radio-sensitization.

Heterogeneous MXene Hybrid-Oriented Exosome Isolation and Metabolic Profiling for Early Screening, Subtyping and Follow-up Evaluation of Bladder Cancer

Exosome metabolite-based noninvasive liquid biopsy is an emerging research hotspot that tends to substitute current means in clinics. Nanostructure-based mass spectrometry enables continuous exosome isolation and metabolic profiling with superior analysis speed and high efficiency. Herein, we construct a heterogeneous MXene hybrid that possesses ternary binding sites for exosome capture and outstanding matrix performance for metabolite analysis. Upon optimizing experimental conditions, the average extraction of exosomes and their metabolic patterns from a 60 mL urine sample is completed within 45 s (40 samples per batch for 30 min). According to the exosomal metabolic patterns and the subsequently established biomarker panel, we distinguish early bladder cancer (BCa) from healthy controls with an area under the curve (AUC) value greater than 0.995 in model training and validation sets. As well, we realize subtype classification of BCa in the blind test on metabolic patterns, with an AUC value of 0.867. We also explore the significant biomarkers that are sensitive to follow-up patients, which indeed present reverse change levels compared with pathological progression. This study has the potential to guide the development of the liquid biopsy approach.

Host-Guest Self-Assembled Interfacial Nanoarrays for Precise Metabolic Profiling

Accurate and rapid metabolic profiling of cerebrospinal fluid (CSF) is urgently needed but remains challenging for clinical diagnosis of central nervous system diseases and biomarker discovery. Matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) holds promise for metabolic analysis. Its low signal reproducibility, however, severely restricts acquisition of quantitative MS data in clinical practice. Herein, a multifunctional self-assembled AuNPs array (MSANA)-based LDI-MS platform for direct amino acids analysis and metabolic profiling in patient CSF samples is developed. MSANA featuring a highly ordered and closely packed two-dimensional nanostructure permits capture and direct analysis of aromatic amino acids by LDI-MS with high selectivity and micromolar sensitivity. Meanwhile, the MSANA-based LDI-MS platform exhibits excellent reproducibility (RSD < 10%), largely outperforming the direct matrix spotting approach widely used now (RSD < 44%). The platform is successfully used in metabolic profiling of CSF (1 µL) within minutes for discrimination of medulloblastoma patients from non-tumor controls. Taken together, the MSANA-based LDI-MS platform shows potential clinical values toward large-scale metabolic diagnostics and pathogenic mechanism study.

Metabolic profiling of urinary exosomes for systemic lupus erythematosus discrimination based on HPL-SEC/MALDI-TOF MS

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease which leads to the formation of immune complex deposits in multiple organs and has heterogeneous clinical manifestations. Currently, exosomes for liquid biopsy have been applied in diagnosis and monitoring of diseases, whereas SLE discrimination based on exosomes at the metabolic level is rarely reported. Herein, we constructed a protocol for metabolomic study of urinary exosomes from SLE patients and healthy controls (HCs) with high efficiency and throughput. Exosomes were first obtained by high-performance liquid size-exclusion chromatography (HPL-SEC), and then metabolic fingerprints of urinary exosomes were extracted by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with high throughput and high efficency. With the statistical analysis by orthogonal partial least-squares discriminant analysis (OPLS-DA) model, SLE patients were efficiently distinguished from HCs, the area under the curve (AUC) of the receiver characteristic curve (ROC) was 1.00, and the accuracy of the unsupervised clustering heatmap was 90.32%. In addition, potential biomarkers and related metabolic pathways were analyzed. This method, with the characteristics of high throughput, high efficiency, and high accuracy, will provide the broad prospect of exosome-driven precision medicine and large-scale screening in clinical applications.

Comprehensive Metabolic Fingerprints Characterize Neuromyelitis Optica Spectrum Disorder by Nanoparticle-Enhanced Laser Desorption/Ionization Mass Spectrometry

Timely screening of neuromyelitis optica spectrum disorder (NMOSD) and differential diagnosis from myelin oligodendrocyte glycoprotein associated disorder (MOGAD) are the keys to improving the quality of life of patients. Metabolic disturbance occurs with the development of NMOSD. Still, advanced tools are required to probe the metabolic phenotype of NMOSD. Here, we developed a fast nanoparticle-enhanced laser desorption/ionization mass spectrometry assay for multiplexing metabolic fingerprints (MFs) from trace plasma and cerebrospinal fluid (CSF) samples in 30 s. Machine learning of the plasma MFs achieved the timely screening of NMOSD from healthy donors with an area under receiver operator characteristic curve (AUROC) of 0.998, and it comprehensively revealed the dysregulated neurotransmitter and energy metabolisms. Combining comprehensive MFs from both plasma and CSF, we constructed an integrated panel for differential diagnosis of NMOSD versus MOGAD with an AUROC of 0.923. This approach demonstrated performance superior to that of human experts in classifying two diseases, especially in antibody assay-limited regions. Together, this approach provides an advanced nanomaterial-based tool for identifying vulnerable populations below the antibody threshold of aquaporin-4 positivity.

Colorectal cancer cell membrane biomimetic ferroferric oxide nanomaterials for homologous bio-imaging and chemotherapy application

The research of nanomaterials for bio-imaging and theranostic are very active nowadays with unprecedented advantages in nanomedicine. Homologous targeting and bio-imaging greatly improve the ability of targeted drug delivery and enhance active targeting and treatment ability of nanomedicine for the tumor. In this work, lycorine hydrochloride (LH) and magnetic iron oxide nanoparticles coated with a colorectal cancer (CRC) cell membrane (LH-Fe3O4@M) were prepared, for homologous targeting, magnetic resonance imaging (MRI), and chemotherapy. Results showed that the LH-Fe3O4@M and Fe3O4@M intensity at HT29 tumor was significantly higher than that Fe3O4@PEG, proving the superior selectivity of cancer cell membrane-camouflaged nanomedicine for homologous tumors and the MRI effect of darkening contrast enhancement were remarkable at HT29 tumor. The LH-Fe3O4@M exhibited excellent chemotherapy effect in CRC models as well as LH alone and achieved a high tumor ablation rate but no damage to normal tissues and cells. Therefore, our biomimetic system achieved a homologous targeting, bio-imaging, and efficient therapeutic effect of CRC.

Construction of Porous Perovskite Oxide Microrods with Au Nanoparticle Anchor for Precise Metabolic Diagnosis of Alzheimer's Disease

Alzheimer's disease (AD) is a progressive illness, and early diagnosis and treatment can help delay its progression. However, clinics still lack high-throughput, low-invasive, precise, and objective diagnostic strategies. Herein, the Au nanoparticles anchored porous perovskite oxide microrods (CTO@Au) with designed superior properties is developed to construct a high-throughput detection platform. Specifically, a single metabolic fingerprinting is obtained from only 30 nL of serum within seconds, enabling the rapid acquisition of 239 × 8 high-quality fingerprints in ≈ 2 h. AD is distinguish from health controls and Parkinson's disease with an area under the curve (AUC) of 1.000. Moreover, eight specific metabolites are identified as a biomarker panel, based on which precise diagnosis of AD is achieved, with an AUC of 1.000 in blind test. The possible relevant pathways and potential mechanism involved in these biomarkers are investigated and discussed. This work provides a high-performance platform for metabolic diagnostic analysis.

Hollow multishelled heterostructures with enhanced performance for laser desorption/ionization mass spectrometry based metabolic diagnosis

High-performance metabolic diagnosis-based laser desorption/ionization mass spectrometry (LDI-MS) improves the precision diagnosis of diseases and subsequent treatment. Inorganic matrices are promising for the detection of metabolites by LDI-MS, while the structure and component impacts of the matrices on the LDI process are still under investigation. Here, we designed a multiple-shelled ZnMn2O4/(Co, Mn)(Co, Mn)2O4 (ZMO/CMO) as the matrix from calcined MOF-on-MOF for detecting metabolites in LDI-MS and clarified the synergistic impacts of multiple-shells and the heterostructure on LDI efficiency. The ZMO/CMO heterostructure allowed 3-5 fold signal enhancement compared with ZMO and CMO with the same morphology. Furthermore, the ZMO/CMO heterostructure with a triple-shelled hollow structure displayed a 3-fold signal enhancement compared to its nanoparticle counterpart. Taken together, the triple-shelled hollow ZMO/CMO exhibits 102-fold signal enhancement compared to the commercial matrix products (e.g., DHB and DHAP), allowing for sensitive metabolic profiling in bio-detection. We directly extracted metabolic patterns by the optimized triple-shelled hollow ZMO/CMO particle-assisted LDI-MS within 1 s using 100 nL of serum and used machine learning as the readout to distinguish hepatocellular carcinoma from healthy controls with the area under the curve value of 0.984. Our approach guides us in matrix design for LDI-MS metabolic analysis and drives the development of a nanomaterial-based LDI-MS platform toward precision diagnosis.

Efficient Metabolic Fingerprinting of Follicular Fluid Encodes Ovarian Reserve and Fertility

Ovarian reserve (OR) and fertility are critical in women's healthcare. Clinical methods for encoding OR and fertility rely on the combination of tests, which cannot serve as a multi-functional platform with limited information from specific biofluids. Herein, metabolic fingerprinting of follicular fluid (MFFF) from follicles is performed, using particle-assisted laser desorption/ionization mass spectrometry (PALDI-MS) to encode OR and fertility. PALDI-MS allows efficient MFFF, showing fast speed (≈30 s), high sensitivity (≈60 fmol), and desirable reproducibility (coefficients of variation <15%). Further, machine learning of MFFF is applied to diagnose diminished OR (area under the curve of 0.929) and identify high-quality oocytes/embryos (p < 0.05) by a single PALDI-MS test. Meanwhile, metabolic biomarkers from MFFF are identified, which also determine oocyte/embryo quality (p < 0.05) from the sampling follicles toward fertility prediction in clinics. This approach offers a powerful platform in women's healthcare, not limited to OR and fertility.

Bovine Omasum-Inspired Interfacial Carbon-Based Nanocomposite for Saliva Metabolic Screening of Gastric Cancer

Gastric cancer is one of the most common malignant digestive cancers, and its diagnostic has still faced challenges based on metabolic analysis due to complex sample pretreatment and low metabolite abundance. In this study, inspired by the structure of bovine omasum, we in situ synthesized a novel interfacial carbon-based nanocomposite of graphene supported nickel nanoparticles-encapsulated in the nitrogen-doped carbon nanotube (Ni/N-CNT/rGO), which was served as a novel matrix with enhanced ionization efficiency for the matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) saliva metabolic analysis of gastric cancer. Benefiting from its high sp² graphitic degree, large surface area, strong UV absorption, and rich active sites, Ni/N-CNT/rGO matrix exhibited excellent performances of reproducibility, coverage, salt-tolerance, sensitivity, and adsorption ability in MALDI-TOF MS. The differential scanning calorimetry (DSC) and thermal conversion behaviors explained the highly efficient LDI mechanism. Based on saliva metabolic fingerprints, Ni/N-CNT/rGO assisted LDI MS with cross-validation analysis could successfully distinguish gastric cancer patients from healthy controls through the screening of four potential biomarkers with an accuracy of 92.50%, specificity of 88.03%, and sensitivity of 97.12%. This work provided a fast and sensitive MS sensing platform for the metabolomics characterization of gastric cancer and might have potential value for precision medicine in the future.

Diagnosis of Parkinson's Disease via the Metabolic Fingerprint in Saliva by Deep Learning

Parkinson's disease (PD) is the second cause of the neurodegenerative disorder, affecting over 6 million people worldwide. The World Health Organization estimated that population aging will cause global PD prevalence to double in the coming 30 years. Optimal management of PD shall start at diagnosis and requires both a timely and accurate method. Conventional PD diagnosis needs observations and clinical signs assessment, which are time-consuming and low-throughput. A lack of body fluid diagnostic biomarkers for PD has been a significant challenge, although substantial progress has been made in genetic and imaging marker development. Herein, a platform that noninvasively collects saliva metabolic fingerprinting (SMF) by nanoparticle-enhanced laser desorption-ionization mass spectrometry with high-reproducibility and high-throughput, using ultra-small sample volume (down to 10 nL), is developed. Further, excellent diagnostic performance is achieved with an area-under-the-curve of 0.8496 (95% CI: 0.7393-0.8625) by constructing deep learning model from 312 participants. In conclusion, an alternative solution is provided for the molecular diagnostics of PD with SMF and metabolic biomarker screening for therapeutic intervention.

Nanometer Resolution Mass Spectro-Microtomography for In-Depth Anatomical Profiling of Single Cells

Visually identifying the molecular changes in single cells is of great importance for unraveling fundamental cellular functions as well as disease mechanisms. Herein, we demonstrated a mass spectro-microtomography with an optimal voxel resolution of ∼300 × 300 × 25 nm³, which enables three-dimensional tomography of chemical substances in single cells. This mass imaging method allows for the distinguishment of abundant endogenous and exogenous molecules in subcellular structures. Combined with statistical analysis, we demonstrated this method for spatial metabolomics analysis of drug distribution and subsequent molecular damages caused by intracellular drug action. More interestingly, thanks to the nanoprecision ablation depth (∼12 nm), we realized metabolomics profiling of cell membrane without the interference of cytoplasm and improved the distinction of cancer cells from normal cells. Our current method holds great potential to be a powerful tool for spatially resolved single-cell metabolomics analysis of chemical components during complex biological processes.

Designed Concave Octahedron Heterostructures Decode Distinct Metabolic Patterns of Epithelial Ovarian Tumors

Epithelial ovarian cancer (EOC) is a polyfactorial process associated with alterations in metabolic pathways. A high-performance screening tool for EOC is in high demand to improve prognostic outcome but is still missing. Here, a concave octahedron Mn₂ O₃ /(Co,Mn)(Co,Mn)₂ O₄ (MO/CMO) composite with a heterojunction, rough surface, hollow interior, and sharp corners is developed to record metabolic patterns of ovarian tumors by laser desorption/ionization mass spectrometry (LDI-MS). The MO/CMO composites with multiple physical effects induce enhanced light absorption, preferred charge transfer, increased photothermal conversion, and selective trapping of small molecules. The MO/CMO shows ≈2-5-fold signal enhancement compared to mono- or dual-enhancement counterparts, and ≈10-48-fold compared to the commercialized products. Subsequently, serum metabolic fingerprints of ovarian tumors are revealed by MO/CMO-assisted LDI-MS, achieving high reproducibility of direct serum detection without treatment. Furthermore, machine learning of the metabolic fingerprints distinguishes malignant ovarian tumors from benign controls with the area under the curve value of 0.987. Finally, seven metabolites associated with the progression of ovarian tumors are screened as potential biomarkers. The approach guides the future depiction of the state-of-the-art matrix for intensive MS detection and accelerates the growth of nanomaterials-based platforms toward precision diagnosis scenarios.

Tryptophan capped gold-silver bimetallic nanoclusters-based turn-off fluorescence sensor for the determination of histamine

Tryptophan capped gold-silver bimetallic nanoclusters (Trp-Au/Ag BNCs) based turn-off fluorescence sensor has been developed for the simple and rapid determination of histamine. Sensor parameters such as the effect of solvent, irradiation time etc. were optimized and further studies were done using these results. Fluorescence quenching of BNCs happens with the incremental addition of histamine. This might be due to the aggregation of BNCs induced by the electrostatic force of attraction between the negatively charged BNCs and amino functional groups of histamine. The sensor showed good sensitivity for the determination of histamine with a linear range of 8.5 × 10^-5 M to 4.0 × 10^-6 M and a limit of detection (LOD) of 9.0 × 10^-7 M. Practical utility of the proposed sensor has been proved through spike recovery analysis in synthetic physiological fluids.

Hollow Core-Shell Metal Oxide Heterojunctions for the Urinary Metabolic Fingerprint-Based Noninvasive Diagnostic Strategy

Urine is a preferred object for noninvasive diagnostic strategies. Urinary metabolic analysis is speculatively regarded as an ideal tool for screening diseases closely related to the genitourinary system in view of the intimate relationship between metabolomics and phenotype. Herein, we propose a urinary metabolic fingerprint-based noninvasive diagnostic strategy by designing hollow core-shell metal oxide heterojunctions (denoted as MOHs). With outstanding light absorption and electron-hole separation ability, MOHs aid in the extraction of high-performance urine metabolic fingerprints. Coupled with optimized machine learning algorithms, we establish a metabolic marker panel for accurate diagnosis of prostate cancer (PCa), which is the most common malignant tumor of the male genitourinary system, achieving accuracies of 84.72 and 83.33% in the discovery and validation sets, respectively. Furthermore, metabolite variations and related pathway analyses confirm the credibility and change correlation of key metabolic features in PCa. This work tends to advance the noninvasive diagnostic strategy toward clinical realities.

Ratiometric electrochemical OR gate assay for NSCLC-derived exosomes

Non-small cell lung cancer (NSCLC) is the most common pathological type of LC and ranks as the leading cause of cancer deaths. Circulating exosomes have emerged as a valuable biomarker for the diagnosis of NSCLC, while the performance of current electrochemical assays for exosome detection is constrained by unsatisfactory sensitivity and specificity. Here we integrated a ratiometric biosensor with an OR logic gate to form an assay for surface protein profiling of exosomes from clinical serum samples. By using the specific aptamers for recognition of clinically validated biomarkers (EpCAM and CEA), the assay enabled ultrasensitive detection of trace levels of NSCLC-derived exosomes in complex serum samples (15.1 particles μL^-1 within a linear range of 10²-10⁸ particles μL^-1). The assay outperformed the analysis of six serum biomarkers for the accurate diagnosis, staging, and prognosis of NSCLC, displaying a diagnostic sensitivity of 93.3% even at an early stage (Stage I). The assay provides an advanced tool for exosome quantification and facilitates exosome-based liquid biopsies for cancer management in clinics.

Tirapazamine-loaded UiO-66/Cu for ultrasound-mediated promotion of chemodynamic therapy cascade hypoxia-activated anticancer therapy

Chemodynamic therapy (CDT), an emerging oncology treatment, has received considerable attention owing to its high selectivity, less aggressiveness, and endogenous stimulation. However, the complex intra-tumor environment limits the therapeutic effect. In this study, Cu⁺ was directly doped into the structure of the UiO-66 matrix using an in situ one-pot oil bath method. The as-formed UiO-66/Cu possessed a large surface area, making it feasible to modify folic acid (FA) and carry more chemotherapeutic agents like tirapazamine (TPZ), thus forming UiO-66/Cu-FA-TPZ nanoplatforms. For CDT, the nanoplatform catalyzed the cyclic generation of the highly oxidizing hydroxyl radical (·OH) from H₂O₂. Particularly, low-frequency ultrasound enhanced the curative effect. Notably, in a tumor, a severe hypoxic environment and ultrasound can activate more TPZ for safe and efficient chemotherapy, achieving synergistic and hypoxia-activated tumor treatment with a low risk of side effects. Moreover, the nanoplatform exhibits computed tomography imaging functions for combined diagnosis and treatment. Our designed nanoplatform overcomes the dilemma of insufficient efficacy from conventional therapy attributed to a hypoxic environment, expecting to guide the design of future treatment regimens for hypoxic tumors.

Construction of a ternary component chip with enhanced desorption efficiency for laser desorption/ionization mass spectrometry based metabolic fingerprinting

Introduction: In vitro metabolic fingerprinting encodes diverse diseases for clinical practice, while tedious sample pretreatment in bio-samples has largely hindered its universal application. Designed materials are highly demanded to construct diagnostic tools for high-throughput metabolic information extraction. Results: Herein, a ternary component chip composed of mesoporous silica substrate, plasmonic matrix, and perfluoroalkyl initiator is constructed for direct metabolic fingerprinting of biofluids by laser desorption/ionization mass spectrometry. Method: The performance of the designed chip is optimized in terms of silica pore size, gold sputtering time, and initiator loading parameter. The optimized chip can be coupled with microarrays to realize fast, high-throughput (∼second/sample), and microscaled (∼1 μL) sample analysis in human urine without any enrichment or purification. On-chip urine fingerprints further allow for differentiation between kidney stone patients and healthy controls. Discussion: Given the fast, high throughput, and easy operation, our approach brings a new dimension to designing nano-material-based chips for high-performance metabolic analysis and large-scale diagnostic use.

Integrative Serum Metabolic Fingerprints Based Multi-Modal Platforms for Lung Adenocarcinoma Early Detection and Pulmonary Nodule Classification

Identification of novel non-invasive biomarkers is critical for the early diagnosis of lung adenocarcinoma (LUAD), especially for the accurate classification of pulmonary nodule. Here, a multiplexed assay is developed on an optimized nanoparticle-based laser desorption/ionization mass spectrometry platform for the sensitive and selective detection of serum metabolic fingerprints (SMFs). Integrative SMFs based multi-modal platforms are constructed for the early detection of LUAD and the classification of pulmonary nodule. The dual modal model, metabolic fingerprints with protein tumor marker neural network (MP-NN), integrating SMFs with protein tumor marker carcinoembryonic antigen (CEA) via deep learning, shows superior performance compared with the single modal model Met-NN (p < 0.001). Based on MP-NN, the tri modal model MPI-RF integrating SMFs, tumor marker CEA, and image features via random forest demonstrates significantly higher performance than the clinical models (Mayo Clinic and Veterans Affairs) and the image artificial intelligence in pulmonary nodule classification (p < 0.001). The developed platforms would be promising tools for LUAD screening and pulmonary nodule management, paving the conceptual and practical foundation for the clinical application of omics tools.

Optically active polymer particles with programmable surface microstructures constructed using chiral helical polyacetylene

Micro/nanoparticles with surface microstructures have attracted tremendous attention due to their fascinating structures and properties. Herein, we present the first strategy for producing optically active polymer particles with varying surface microstructures via a template surface modification process in which achiral particles act as the template and helical substituted polyacetylene acts as the chiral component. To prepare the designed chiral-functionalized particles, template particles were first reacted with propargylamine to produce alkynylated template particles. The alkynylated templates further participated in the polymerization of chiral alkyne monomers through a surface grafting precipitation polymerization approach, resulting in achiral particles with surface microstructures covalently bonded with a chiral helical polymer. SEM images ascertain the production of chiral-functionalized particles showing various shapes (jar-like, golf ball-like, and raspberry-like particles). Furthermore, CD and UV-vis absorption spectra demonstrate that the grafted polyacetylene chains adopt a predominantly single-handed helical conformation, thereby affording composite particles with optical activity. Using the established protocol, numerous advanced chiral-functionalized micro/nanostructures are expected to be designed and constructed.

Multilevel Hollow Phenolic Resin Nanoreactors with Precise Metal Nanoparticles Spatial Location toward Promising Heterogeneous Hydrogenations

Hollow nanostructures with fascinating properties have inspired numerous interests in broad research fields. Cell-mimicking complex hollow architectures with precise active components distributions are particularly important, while their synthesis remains highly challenging. Herein, a "top-down" chemical surgery strategy is introduced to engrave the 3-aminophenol formaldehyde resin (APF) spheres at nanoscale. Undergoing the cleavage of (Ar)CN bonds with ethanol as chemical scissors and subsequent repolymerization process, the Solid APF transform to multilevel hollow architecture with precise nanospatial distribution of organic functional groups (e.g., hydroxymethyl and amine). The transformation is tracked by electron microscopy and solid-state nuclear magnetic resonance techniques, the category and dosage of alcohol are pivotal for constructing multilevel hollow structures. Moreover, it is demonstrated the evolution of nanostructures accompanied with unique organic microenvironments is able to accurately confine multiple gold (Au) nanoparticles, leading to the formation of pomegranate-like particles. Through selectively depositing palladium (Pd) nanoparticles onto the outer shell, bimetallic Au@APF@Pd catalysts are formed, which exhibit excellent hydrogenation performance with turnover frequency (TOF) value up to 11257 h^-1 . This work provides an effective method for precisely manipulating the nanostructure and composition of polymers at nanoscale and sheds light on the design of catalysts with precise spatial active components.