A Dual and Rapid RPA-CRISPR/Cas12a Method for Simultaneous Detection of Cattle and Soybean-Derived Adulteration in Goat Milk Powder.

The adulteration of goat milk powder occurs frequently; cattle-derived and soybean-derived ingredients are common adulterants in goat milk powder. However, simultaneously and rapidly detecting cattle-derived and soybean-derived components is still a challenge. An efficient, high-throughput screening method for adulteration detection is needed. In this study, a rapid method was developed to detect the adulteration of common cattle-derived and soybean-derived components simultaneously in goat milk powder by combining the CRISPR/Cas12a system with recombinant polymerase amplification (RPA). A dual DNA extraction method was employed. Primers and crRNA for dual detection were designed and screened, and a series of condition optimizations were carried out in this experiment. The optimized assay rapidly detected cattle-derived and soybean-derived components in 40 min. The detection limits of both cattle-derived and soybean-derived components were 1% (w/w) for the mixed adulteration models. The established method was applied to a blind survey of 55 commercially available goat milk powder products. The results revealed that 36.36% of the samples contained cattle-derived or soybean-derived ingredients, which revealed the noticeable adulteration situation in the goat milk powder market. This study realized a fast flow of dual extraction, dual amplification, and dual detection of cattle-derived and soybean-derived components in goat milk powder for the first time. The method developed can be used for high-throughput and high-efficiency on-site primary screening of goat milk powder adulterants, and provides a technical reference for combating food adulteration.

Ultrasensitive Ti3C2Tx@Pt-Based Immunochromatography with Catalytic Amplification and a Dual Signal for the Detection of Chloramphenicol in Animal-Derived Foods.

Herein, a catalytic amplification enhanced dual-signal immunochromatographic assay (ICA) based on Pt nanoparticles (Pt NPs) modified with Ti3C2Tx MXene (Ti3C2Tx@Pt) was first developed for chloramphenicol (CAP) in animal-derived foods. Due to the large specific surface area and abundant active sites of Ti3C2Tx@Pt, they can be loaded with hundreds of Pt NPs to enhance their catalytic activity, resulting in a significant increase in the detection sensitivity; the sensitivity was up to 50-fold more sensitive than the reported ICA for CAP. The LODs of the developed method for milk/chicken/fish were 0.01 µg/kg, the LOQs were 0.03 µg/kg and the recovery rates were 80.5-117.0%, 87.2-118.1% and 92.7-117.9%, with corresponding variations ranging from 3.1 to 9.6%, 6.0 to 12.7% and 6.0 to 13.6%, respectively. The linear range was 0.0125-1.0 µg/kg. The results of the LC-MS/MS confirmation test on 30 real samples had a good correlation with that of our established method (R2 > 0.98), indicating the practical reliability of the established method. The above results indicated that an ICA based on the Ti3C2Tx@Pt nanozyme has excellent potential as a food safety detection tool.

Simple synthesis of flower-like ZnO@Pt composites for dual-mode colorimetric detecting Hg2+ with smartphone and UV-vis.

BACKGROUND: Mercury is one of the most toxic heavy metal contaminants that can be harmful to human health through the food chain. Recently, the colorimetric detection of heavy metals based on nanozyme catalytic activity has received extensive interest due to the simplicity, signal visibility and suitability for in situ detection. However, the majority of these nanozymes that can be utilized for detecting mercury with high synthesis temperature and complicated synthesis methods, which limited their practical application. RESULTS: In this work, flower-like ZnO@Pt composites were simply synthesized at room temperature, the flower-like structure and the high electron mobility of ZnO endow ZnO@Pt with stronger peroxidase-like activity. Consequently, dual-mode (UV-vis and smartphone) colorimetric sensors were designed to detect Hg2+. In UV-vis mode, the Hg2+ concentration linear range was 10-400 nM, and the limit of detection (LOD) was 0.54 nM. In smartphone mode, the Hg2+ concentration linear range was 50-1250 nM, and the LOD was 29.8 nM. A parallel analysis in 3 real water samples was confirmed by ICP-MS, the results showed good correlations (R2 > 0.98), indicating the practical reliability of these sensors. SIGNIFICANCE: The novel flower-like ZnO@Pt composites with high stability, catalytic activity and Hg2+ response were simply synthesized at room temperature, simplifying the synthesis steps and reducing costs. The sensitivity of the developed colorimetric sensor in UV-vis mode was 3-145 times higher than that of the similar methods. The colorimetric sensor in smartphone mode broadened the detection range and improved the portability of Hg2+ detection. Thus, the dual-mode (UV-vis and smartphone) colorimetric sensors providing new detection modes for rapid monitoring of Hg2+ in environmental water.

High-Density Au Anchored to Ti3C2-Based Colorimetric-Fluorescence Dual-Mode Lateral Flow Immunoassay for All-Domain-Enhanced Performance and Signal Intercalibration.

In this work, a novel MXene-Au nanoparticle (Ti3C2@Au) was synthesized with a high molar extinction coefficient, strong fluorescence quenching ability, ultrahigh antibody affinity, high stability, and good dispersibility, and it was used to develop a colorimetric-fluorescence dual-mode lateral flow immunoassay (LFIA). The detection limits of this method for the detection of dexamethasone in milk, beef, and pork were 0.0018, 0.12, and 0.084 µg/kg in the "turn-off" mode (colorimetric signal), and 0.0013, 0.080, and 0.070 µg/kg in the "turn-on" mode (fluorescent signal), respectively, which was up to 231-fold more sensitive compared with that of the reported LFIAs. The recovery rates ranged from 81.1-113.7%, and 89.2-115.4%, with the coefficients of variation ranging from 1.4-15.0%, and 1.9-14.8%, respectively. The results of the LC-MS/MS confirmation test on 30 real samples had a good correlation with that of our established method (R2 > 0.97). This work not only developed novel nanocarriers for antibody-based LFIA but also ensured high-performance detection.

Silicon Hybrid EPDM Composite with High Thermal Protection Performance.

The effects of octaphenylsilsesquioxane (OPS), fumed silica, and silica aerogel on the thermal insulation properties of ethylene propylene diene monomer (EPDM) rubber were studied. On this basis, two kinds of fillers with good performances were selected to study the thermal insulation of an EPDM full-formula system. The results show that the addition of fumed silica or silica aerogel had a positive effect on the thermal insulation performance of EPDM rubber and its composite. A 30 wt% silica aerogel can be well dispersed in the EPDM rubber system and with a lower thermal conductivity compared with fumed silica. EPDM composite with 23.4 wt% fumed silica can produce more char residues at 1000 °C than at 500 °C in a burn-through test and formed the compact and porous char at 1000 °C, which had a lowest thermal conductivity. EPDM composite with fumed silica cannot be burned through 1000 °C burning, and comparison with silica aerogel revealed that it achieved the lowest back temperature and had a temperature of 388 °C after 800 s.

Two new guaiane-type sesquiterpenes from Curcuma wenyujin.

Two new guaiane-type sesquiterpenes, wenyujinolides A (1) and B (2), were isolated from the ethanol extract of Curcuma wenyujin, together with 10 known compounds. Their structures were established by extensive spectroscopic methods (IR, ESIMS, HRESIMS, ECD, 1D and 2D NMR) and comparison of their NMR data with literatures. Compounds 1 and 2 were evaluated for the inhibition of NO production in LPS induced RAW 264.7 macrophages.

Multiplexed SELEX for Sulfonamide Antibiotics Yielding a Group-Specific DNA Aptamer for Biosensors.

The widespread use of sulfonamide (SA) antibiotics in animal husbandry has led to residues of SAs in the environment, causing adverse effects to the ecosystem and a risk of bacterial resistance, which is a potential threat to public health. Therefore, it is highly desirable to develop simple, high-throughput methods that can detect multiple SAs simultaneously. In this study, we isolated aptamers with different specificities based on a multi-SA systematic evolution of ligands by the exponential enrichment (SELEX) strategy using a mixture of sulfadimethoxine (SDM), sulfaquinoxaline (SQX), and sulfamethoxazole (SMZ). Three aptamers were obtained, and one of them showed a similar binding to all tested SAs, with dissociation constant (Kd) ranging from 0.22 to 0.63 µM. For the other two aptamers, one is specific for SQX, and the other is specific for SDM and sulfaclozine. A label-free detection method based on the broad-specificity aptamer was developed for the simultaneous detection of six SAs, with detection of limits ranging from 0.14 to 0.71 µM in a lake water sample. The aptasensor has no binding for other broad-spectrum antibiotics such as ß-lactam antibiotics, quinolones, tetracyclines, and chloramphenicol. This work provides a promising biosensor for rapid, multiresidue, and high-throughput detection of SAs, as well as a shortcut for the preparation of different specific recognition elements required for the detection of broad-spectrum antibiotics.

High Bioaffinity Controllable Assembly Nanocarrier UiO-66-NH2@Quantum Dot-Based Immunochromatographic Assay for Simultaneous Detection of Five Mycotoxins in Cereals and Feed.

Herein, the UiO-66-NH2@quantum dot (NU66@QD) was synthesized with excellent fluorescence intensity and biocompatibility, which was used to develop a multiple immunochromatographic assay (ICA) for the detection of aflatoxin B1 (AFB1), fumonisin B1 (FB1), deoxynivalenol (DON), T-2 toxins (T-2), and zearalenone (ZEN) in cereals and feed. Five monoclonal antibodies and NU66@QD were efficiently labeled by a one-step mixed method to form a multiple detection probe. The limits of detection of the proposed NU66@QD-ICA for AFB1/FB1/DON/T-2/ZEN were 0.04/0.28/0.25/0.09/0.08 µg/kg. The recoveries ranged from 82.83-117.44%, with the coefficient of variation from 2.88-11.80%. A parallel analysis in 35 naturally contaminated cereal and feed samples was confirmed by LC-MS/MS, and the results showed a good correlation (R2 > 0.9), indicating the practical reliability of the multiple NU66@QD-ICA. Overall, the introduction of the novel nanomaterial NU66@QD provides a highly sensitive and efficient multiplex detection strategy for the development of ICA.

PathwayTMB: A pathway-based tumor mutational burden analysis method for predicting the clinical outcome of cancer immunotherapy.

Immunotherapy has become one of the most promising therapy methods for cancer, but only a small number of patients are responsive to it, indicating that more effective biomarkers are urgently needed. This study developed a pathway analysis method, named PathwayTMB, to identify genomic mutation pathways that serve as potential biomarkers for predicting the clinical outcome of immunotherapy. PathwayTMB first calculates the patient-specific pathway-based tumor mutational burden (PTMB) to reflect the cumulative extent of mutations for each pathway. It then screens mutated survival benefit-related pathways to construct an immune-related prognostic signature based on PTMB (IPSP). In a melanoma training set, IPSP-high patients presented a longer overall survival and a higher response rate than IPSP-low patients. Moreover, the IPSP showed a superior predictive effect compared with TMB. In addition, the prognostic and predictive value of the IPSP was consistently validated in two independent validation sets. Finally, in a multi-cancer dataset, PathwayTMB also exhibited good performance. Our results indicate that PathwayTMB could identify the mutation pathways for predicting immunotherapeutic survival, and their combination may serve as a potential predictive biomarker for immune checkpoint inhibitor therapy.

Aflatoxin B1 Induces Inflammatory Liver Injury via Gut Microbiota in Mice.

Aflatoxin B1 (AFB1), a potent food-borne hepatocarcinogen, is the most toxic aflatoxin that induces liver injury in humans and animals. Species-specific sensitivities of aflatoxins cannot be fully explained by differences in the metabolism of AFB1 between animal species. The gut microbiota are critical in inflammatory liver injury, but it remains to reveal the role of gut microbiota in AFB1-induced liver injury. Here, mice were gavaged with AFB1 for 28 days. Then, the modulation of gut microbiota, colonic barrier, and liver pyroptosis and inflammation were analyzed. To further verify the direct role of gut microbiota in AFB1-induced liver injury, mice were treated with antibiotic mixtures (ABXs) to deplete the microbiota, and fecal microbiota transplantation (FMT) was conducted. The treatment of AFB1 in mice altered gut microbiota composition, such as increasing the relative abundance of Bacteroides, Parabacteroides, and Lactobacillus, inducing colonic barrier dysfunction and promoting liver pyroptosis. In ABX-treated mice, AFB1 had little effect on the colonic barrier and liver pyroptosis. Notably, after FMT, in which the mice were colonized with gut microbiota from AFB1-treated mice, colonic barrier dysfunction, and liver pyroptosis and inflammation were obliviously identified. We proposed that the gut microbiota directly participated in AFB1-induced liver pyroptosis and inflammation. These results provide new insights into the mechanisms of AFB1 hepatotoxicity and pave a window for new targeted interventions to prevent or reduce AFB1 hepatotoxicity.

Herbicide propisochlor exposure induces intestinal barrier impairment, microbiota dysbiosis and gut pyroptosis.

Propisochlor is a chloroacetamide herbicide causing liver toxicity and suppressing immunity in human and animal. Although the herbicide has been used for years, the effects of propisochlor on intestinal health remain poorly understood. Hence, the impacts of propisochlor in intestinal health and gut microbiota were analyzed by using molecular approach and bacterial 16S rRNA sequencing. The result showed that the intake of propisochlor in mice impaired gut morphology, reduced expression of tight junction proteins, decreased thickness of mucus layer and activated pyroptosis signaling. Moreover, the exposure of propisochlor in mice led to significant alterations in gut microbial diversity and composition, including an increase of Bacteroidetes and a decrease of Firmicutes. The gut microbiota, such as Parabacteroides, Parasutterella, and Bacteroides, demonstrated a strong negative correlation with the intestinal health. These findings suggested that gut microbiota could play a critical role in the propisochlor-induced pyroptosis.

Rapid and Simple Detection of Burkholderia gladioli in Food Matrices Using RPA-CRISPR/Cas12a Method.

Pathogenic variants of Burkholderia gladioli pose a serious threat to human health and food safety, but there is a lack of rapid and sensitive field detection methods for Burkholderia gladioli. In this study, the CRISPR/Cas12a system combined with recombinant enzyme polymerase amplification (RPA) was used to detect Burkholderia gladioli in food. The optimized RPA-CRISPR/Cas12a assay was able to specifically and stably detect Burkholderia gladioli at a constant 37 °C without the assistance of large equipment. The detection limit of the method was evaluated at two aspects, the genomic DNA (gDNA) level and bacterial quantity, of which there were 10-3 ng/µL and 101 CFU/mL, respectively. Three kinds of real food samples were tested. The detection limit for rice noodles, fresh white noodles, and glutinous rice flour samples was 101 CFU/mL, 102 CFU/mL, and 102 CFU/mL, respectively, without any enrichment steps. The whole detection process, including sample pretreatment and DNA extraction, did not exceed one hour. Compared with the qPCR method, the established RPA-CRISPR /Cas12a method was simpler and even more sensitive. Using this method, a visual detection of Burkholderia gladioli that is suitable for field detection can be achieved quickly and easily.

A pathway-based mutation signature to predict the clinical outcomes and response to CTLA-4 inhibitors in melanoma.

Immune checkpoint inhibitor (ICI) therapy has become a powerful clinical strategy for treating melanoma. The relationship between somatic mutations and the clinical benefits of immunotherapy has been widely recognized. However, the gene-based predictive biomarkers are less stable due to the heterogeneity of cancer at the individual gene level. Recent studies have suggested that the accumulation of gene mutations in biological pathways may activate antitumor immune responses. Herein, a novel pathway mutation signature (PMS) was constructed to predict the survival and efficacy of ICI therapy. In a dataset of melanoma patients treated with anti-CTLA-4, we mapped the mutated genes into the pathways and then identified seven significant mutation pathways associated with survival and immunotherapy response, which were used to construct the PMS model. According to the PMS model, the patients in the PMS-high group showed better overall survival (hazard ratio (HR) = 0.37; log-rank test, p < 0.0001) and progression-free survival (HR = 0.52; log-rank test, p = 0.014) than those in the PMS-low group. The PMS-high patients also showed a significantly higher objective response rate to anti-CTLA-4 therapy than the PMS-low patients (Fisher's exact test, p = 0.0055), and the predictive power of the PMS model was superior to that of TMB. Finally, the prognostic and predictive value of the PMS model was validated in two independent validation sets. Our study demonstrated that the PMS model can be considered a potential biomarker to predict the clinical outcomes and response to anti-CTLA-4 therapy in melanoma patients.

DTSEA: A network-based drug target set enrichment analysis method for drug repurposing against COVID-19.

The Coronavirus Disease 2019 (COVID-19) pandemic is still wreaking havoc worldwide. Therefore, the urgent need for efficient treatments pushes researchers and clinicians into screening effective drugs. Drug repurposing may be a promising and time-saving strategy to identify potential drugs against this disease. Here, we developed a novel computational approach, named Drug Target Set Enrichment Analysis (DTSEA), to identify potent drugs against COVID-19. DTSEA first mapped the disease-related genes into a gene functional interaction network, and then it used a network propagation algorithm to rank all genes in the network by calculating the network proximity of genes to disease-related genes. Finally, an enrichment analysis was performed on drug target sets to prioritize disease-candidate drugs. It was shown that the top three drugs predicted by DTSEA, including Ataluren, Carfilzomib, and Aripiprazole, were significantly enriched in the immune response pathways indicating the potential for use as promising COVID-19 inhibitors. In addition to these drugs, DTSEA also identified several drugs (such as Remdesivir and Olumiant), which have obtained emergency use authorization (EUA) for COVID-19. These results indicated that DTSEA could effectively identify the candidate drugs for COVID-19, which will help to accelerate the development of drugs for COVID-19. We then performed several validations to ensure the reliability and validity of DTSEA, including topological analysis, robustness analysis, and prediction consistency. Collectively, DTSEA successfully predicted candidate drugs against COVID-19 with high accuracy and reliability, thus making it a formidable tool to identify potential drugs for a specific disease and facilitate further investigation.

Crystal Engineering of TiO2 for Enhanced Catalytic Oxidation of 1,2-Dichloroethane on a Pt/TiO2 Catalyst.

Crystal engineering of metal oxide supports represents an emerging strategy to improve the catalytic performance of noble metal catalysts in catalytic oxidation of chlorinated volatile organic compounds (CVOCs). Herein, Pt catalysts on a TiO2 support with different crystal phases (rutile, anatase, and mixed phase (P25)) were prepared for catalytic oxidation of 1,2-dichloroethane (DCE). The Pt catalyst on P25-TiO2 (Pt/TiO2-P) showed optimal activity, selectivity, and stability, even under high-space velocity and humidity conditions. Due to the strong interaction between Pt and P25-TiO2 originating from the more lattice defects of TiO2, the Pt/TiO2-P catalyst possessed stable Pt0 and Pt2+ species during DCE oxidation and superior redox property, resulting in high activity and stability. Furthermore, the Pt/TiO2-P catalyst possessed abundant hydroxyl groups, which prompted the removal of chlorine species in the form of HCl and significantly decreased the selectivity of vinyl chloride (VC) as the main byproduct. On the other hand, the Pt/TiO2-P catalyst exhibited a different reaction path, in which the hydroxyl groups on its surface activated DCE to form VC and enolic species, besides the lattice oxygen of TiO2 for the Pt catalysts on rutile and anatase TiO2. This work provides guidance for the rational design of catalysts for CVOCs.

iATMEcell: identification of abnormal tumor microenvironment cells to predict the clinical outcomes in cancer based on cell-cell crosstalk network.

Interactions between Tumor microenvironment (TME) cells shape the unique growth environment, sustaining tumor growth and causing the immune escape of tumor cells. Nonetheless, no studies have reported a systematic analysis of cellular interactions in the identification of cancer-related TME cells. Here, we proposed a novel network-based computational method, named as iATMEcell, to identify the abnormal TME cells associated with the biological outcome of interest based on a cell-cell crosstalk network. In the method, iATMEcell first manually collected TME cell types from multiple published studies and obtained their corresponding gene signatures. Then, a weighted cell-cell crosstalk network was constructed in the context of a specific cancer bulk tissue transcriptome data, where the weight between cells reflects both their biological function similarity and the transcriptional dysregulated activities of gene signatures shared by them. Finally, it used a network propagation algorithm to identify significantly dysregulated TME cells. Using the cancer genome atlas (TCGA) Bladder Urothelial Carcinoma training set and two independent validation sets, we illustrated that iATMEcell could identify significant abnormal cells associated with patient survival and immunotherapy response. iATMEcell was further applied to a pan-cancer analysis, which revealed that four common abnormal immune cells play important roles in the patient prognosis across multiple cancer types. Collectively, we demonstrated that iATMEcell could identify potentially abnormal TME cells based on a cell-cell crosstalk network, which provided a new insight into understanding the effect of TME cells in cancer. iATMEcell is developed as an R package, which is freely available on GitHub (https://github.com/hanjunwei-lab/iATMEcell).

Two kinds of lateral flow immunoassays based on multifunctional magnetic prussian blue nanoenzyme and colloidal gold for the detection of 38 ß-agonists in swine urine and pork.

Herein, novel multifunctional magnetic prussian blue nanoenzymes (MPBNs) and colloidal gold (CG) were synthesized and used to develop two kinds of lateral flow immunoassays (LFIAs) for the detection of 38 ß-agonists. Since MPBNs has a unique three-in-one function of colorimetric magnetic catalytic activities, the signal intensity and coupling ratio are 2 and 8-fold higher than that of the CG. The cut-off values of the CG-LFIA and MPBNs-LFIA for swine urine and pork are 5/5 and 0.3/0.5 µg/kg, the limits of detection are 0.19/0.29 and 0.02/0.03 µg/kg, respectively. The sensitivity of MPBNs-LFIA is 10-fold higher than that of CG-LFIA, and up to 200-fold higher than that of the reported LFIAs. The recoveries of the LFIAs are 80.0%-116.7%, with coefficients of variation of 1.4%-14.3%. Our study proved that the MPBNs have more advantages than CG, and can offer a promising signal label for ultrasensitive immunoassay techniques.

The Proactive Effects of Built Environment on Rural Community Resilience: Evidence from China Family Panel Studies.

Rural community resilience (RCR) is crucial to rural sustainable development in the context of rural decline globally. Previous studies seem to underestimate the role of the built environment (BE) in the proactive aspect of RCR (P-RCR), that is, a rural community's ability to cope with change proactively. This study explores BE's effects on P-RCR with a holistic framework involving objective BE (OBE), perceived BE (PBE), place attachment (PA) and P-RCR, using structural equation modeling (SEM) based on a sample of 7528 rural respondents from eastern, central and western China. The results are as follows: (1) Both OBE (population density and accessibility) and PBE (perceptions of facilities, surrounding environment and safety) can significantly affect P-RCR in terms of social, economic and environmental dimensions. (2) In all regions, PBE's impacts were consistent and positive on social and economic dimensions at both the individual and community levels (except the community-level economic dimension in western regions), but negative on the individual-level environmental dimension; OBE's impacts were varied among regions. (3) In certain regions, PA and PBE were mediators in the BE-P-RCR relationship. This study can help researchers to construct a more detailed picture of the BE-P-RCR relationship and identify BE-related factors that contribute to P-RCR enhancement.

An Ultrasensitive Lateral Flow Immunoassay Based on Metal-Organic Framework-Decorated Polydopamine for Multiple Sulfonylureas Adulteration in Functional Foods.

Herein, an ultrasensitive lateral flow immunoassay (LFIA), based on metal-organic framework-decorated polydopamine (PCN-224@PDA) was first established to detect multiple sulfonylureas (SUs) in functional foods. The PCN-224@PDA was synthesized using the one-pot hydrothermal method and covalently coupled with SUs antibodies, and the coupling rate was up to 91.8%. The detection limits of the developed PCN-224@PDA-LFIA for multiple SUs in functional teas and capsules were 0.22-3.72 µg/kg and 0.40-3.71 µg/kg, and quantification limits were 0.75-8.19 µg/kg and 1.03-9.08 µg/kg, respectively. The analytical sensitivity was 128-fold higher than that of similar methods reported so far. The recovery rates ranged from 83.8 to 119.0%, with coefficients of variation of 7.6-14.4%. The parallel analysis of 20 real samples by LC-MS/MS confirmed the reliability of the proposed method. Therefore, our work offers novel, ultrasensitive, and rapid technical support for on-site monitoring of SUs in functional foods.

Facile immunochromatographic assay based on metal-organic framework-decorated polydopamine for the determination of hydrochlorothiazide adulteration in functional foods.

Herein, a novel immunochromatographic assay (ICA) based on metal-organic framework-decorated polydopamine (MOF@PDA) was firstly developed for the determination of hydrochlorothiazide (HCTZ) adulteration in functional foods. The coupling rate of MOF@PDA carrier to HCTZ antibody was as high as 91.7 %. The detection limits of the developed MOF@PDA-ICA in functional tablets and capsules were 5.93 and 4.72 µg/kg, the linear ranges were 11.2-91.91 µg/kg and 9.11-86.78 µg/kg, respectively. The sensitivity was 27-fold higher than that of the reported ICA. The recovery was 82.5-116.6 %, and coefficient of variation was 6.9-14.2 %. The results can be achieved and analyzed in 8 min with the smartphone-based detection device. The parallel tests of 23 commercial functional tablets and capsules showed that the results of the MOF@PDA-ICA were consistent with that of the LC-MS/MS (R2 > 0.99). Therefore, our method is facile, sensitive, portable, and can provide a reliable technical mean for the detection of HCTZ adulteration in functional foods.