Spatial distribution modulation of mixed building blocks in metal-organic frameworks

MOF-mediated dual energy transfer nanoprobe integrated with exonuclease III amplification strategy for highly sensitive detection of DNA

Accurate quantitative detection of DNA is an advanced strategy in various fields (such as disease diagnosis and environmental monitoring), but the classical DNA detection method usually suffers from low sensitivity, expensive thermal cyclers, or strict annealing conditions. Herein, a MOF-ERA platform for ultrasensitive HBV-DNA detection is constructed by integrating metal-organic framework (MOF)-mediated double energy transfer nanoprobe with exonuclease III (Exo III)-assisted target recycling amplification. The proposed double energy transfer containing a donor and two receptors is simply composed of MOFs (UiO-66-NH2, a well-studied MOF) modified with a signal probe formed by the hybridization of carboxyuorescein (FAM)-labeled DNA (FDNA) and black hole quencher (BHQ1)-terminated DNA (QDNA), resulting in low fluorescence signal. After the addition of HBV-DNA, Exo III degradation to FDNA is activated, leading to the liberation of the numerous FAM molecules, followed by the generation of a significant fluorescence signal owing to the negligible binding of MOFs with free FAM molecules. The results certify that the MOF-ERA platform can be successfully used to assay HBV-DNA in the range of 1.0-25.0 nM with a detection limit of 97.2 pM, which is lower than that without BHQ1 or Exo III. The proposed method with the superiorities of low background signal and high selectivity holds promise for early disease diagnosis and clinical biomedicine applications.

Machine learning guided tuning charge distribution by composition in MOFs for oxygen evolution reaction

Traditional design/optimization of metal-organic frameworks (MOFs) is time-consuming and labor-intensive. In this study, we utilize machine learning (ML) to accelerate the synthesis of MOFs. We have built a library of over 900 MOFs with different metal salts, solvent ratios, reaction durations and temperatures, and utilize zeta potentials as target variables for ML training. A total of four ML models have been used to train the collected dataset and assess their convergence performances, where Random Forest Regression (RFR) and Gradient Boosting Regression (GBR) models show strong correlation and accurate predictions. We then predicted two kinds of MOFs from RFR and GBR models. Remarkably, the experimentally data of the synthesized MOFs closely matched the predicted results, and these MOFs exhibited excellent electrocatalytic performances for oxygen evolution. This study would have general implications in the utilization of machine learning for accelerating the synthesis of MOFs for diverse applications.

Metal-Organic Framework-DNA Bio-Barcodes Amplified CRISPR/Cas12a Assay for Ultrasensitive Detection of Protein Biomarkers

CRISPR/Cas12a shows excellent potential in disease diagnostics. However, insensitive signal conversion strategies hindered its application in detecting protein biomarkers. Here, we report a metal-organic framework (MOF)-based DNA bio-barcode integrated with the CRISPR/Cas12a system for ultrasensitive detection of protein biomarkers. In this work, zirconium-based MOF nanoparticles were comodified with antibodies and bio-barcode phosphorylated DNA as an efficient signal converter, which not only recognized the protein biomarker to form the sandwich complex but also released the bio-barcode DNA activators after MOF dissociation to activate the trans-cleavage activity of Cas12a. Due to the obvious advantages, including numerous loaded oligonucleotides, a convenient release process, and the nontoxic release reagent, this MOF-DNA bio-barcode strategy could amplify the CRISPR/Cas12a system to achieve simple and highly sensitive detection of tumor protein biomarkers with detection limits of 0.03 pg/mL (PSA) and 0.1 pg/mL (CEA), respectively. Furthermore, this platform could detect PSA directly in clinical serum samples, offering a powerful tool for early disease diagnosis.

Defined metal atom aggregates precisely incorporated into metal-organic frameworks

Nanosized metal aggregates (MAs), including metal nanoparticles (NPs) and nanoclusters (NCs), are often the active species in numerous applications. In order to maintain the active form of MAs in "use", they need to be anchored and stabilised, preventing agglomeration. In this context, metal-organic frameworks (MOFs), which exhibit a unique combination of properties, are of particular interest as a tunable and porous matrix to host MAs. A high degree of control in the synthesis towards atom-efficient and application-oriented MA@MOF composites is required to derive specific structure-property relationships and in turn to enable design of functions on the molecular level. Due to the versatility of MA@MOF (derived) materials, their applications are not limited to the obvious field of catalysis, but increasingly include 'out of the box' applications, for example medical diagnostics and theranostics, as well as specialised (bio-)sensoring techniques. This review focuses on recent advances in the controlled synthesis of MA@MOF materials en route to atom-precise MAs. The main synthetic strategies, namely 'ship-in-bottle', 'bottle-around-ship', and approaches to achieve novel hierarchical MA@MOF structures are highlighted and discussed while identifying their potential as well as their limitations. Hereby, an overview of standard characterisation methods that enable a systematic analysis procedure and state-of-art techniques that localise MA within MOF cavities are provided. While the perspectives of MA@MOF materials in general have been reviewed various times in the recent past, few atom-precise MAs inside MOFs have been reported so far, opening opportunities for future investigation.

Lipid Membrane-Wrapped Zeolitic Imidazolate Framework-8 for Synergistic Chemotherapy and Photothermal Therapy to Target Prostate Cancer

Endocrine therapy is often used for advanced prostate cancer. However, with cancer progress, prostate cancer gradually resistant to hormone which lead to serious threatens to life of patients. Herein, a multifunctional synergistic core–shell nanoplatform is reported for improving the therapeutic effect of chemotherapy for advanced or metastatic prostate cancer, and reducing the risk of leakage of chemotherapy drugs. Particularly, Zeolitic imidazolate framework-8 (ZIF-8) is chosen as inner core to load doxorubicin, and the of liposomes which are embedded with IR780 iodide are used as outer shell, and further modified with target ligand that binds to luteinizing hormone releasing hormone receptor. The prepared nanocarrier exhibit satisfactory photothermal effect under near infrared laser irradiation, and the temperature increases to 60.8 °C within 6 min. Meanwhile, the elevated temperature accelerates the degradation of lipid shell, releasing ZIF-8 core to acidic microenvironment of tumor, and resulting in the release of doxorubicin. Moreover, in vivo and in vitro studies have shown the ZIF-D@ALIP core–shell nanoparticles can achieve targeted drug delivery, pH and NIR dual stimuli-responsive drug release, as well as chemotherapy and photothermal therapy synergistically on the tumor site. In addition, the problem of premature leakage and changes in the physicochemical properties of anticancer drugs are avoided under the protection of the outer shell structure. Therefore, the core–shell nanostructure proposes a new lipid membrane coating strategy to promote the effective targeting of prostate cancer cells or tissues and provides some insights in clinical treatment for advanced prostate cancer.