Identification of ruptured intracranial aneurysms using the aneurysm-specific prediction score in patients with multiple aneurysms with subarachnoid hemorrhages- a Chinese population based external validation study.

BACKGROUND: For patients with aneurysmal subarachnoid hemorrhages (SAHs) and multiple intracranial aneurysms (MIAs), a simple and fast imaging method that can identify ruptured intracranial aneurysms (RIAs) may have great clinical value. We sought to use the aneurysm-specific prediction score to identify RIAs in patients with MIAs and evaluate the aneurysm-specific prediction score. METHODS: Between May 2018 and May 2021, 134 patients with 290 MIAs were retrospectively analyzed. All patients had an SAH due to IA rupture. CT angiography (CTA) was used to assess the maximum diameter, shape, and location of IAs to calculate the aneurysm-specific prediction score. Then, the aneurysm-specific prediction score was applied to RIAs in patients with MIAs. RESULTS: The IAs with the highest aneurysm-specific prediction scores had not ruptured in 17 (12.7%) of the 134 patients with 290 MIAs. The sensitivity, specificity, false omission rate, diagnostic error rate, and diagnostic accuracy of the aneurysm-specific prediction score were higher than those of the maximum diameter, shape, and location of IAs. CONCLUSIONS: The present study suggests that the aneurysm-specific prediction score has high diagnostic accuracy in identifying RIAs in patients with MIAs and SAH, but that it needs further evaluation.

Voltammetric determination of organophosphorus pesticides using a hairpin aptamer immobilized in a graphene oxide-chitosan composite.

An aptasensor is described for electrochemical determination of organophosphorus pesticides (OPPs), specifically of profenofos, phorate, isocarbophos, and omethoate. The method uses a hairpin aptamer as signalling donor. Its 5' and 3' ends were modified with amino groups and the redox probe ferrocene (Fc), respectively. A nanocomposite consisting of graphene oxide and chitosan (GO-chit) was used to immobilize the aptamer via formation of an amide link. Its good conductivity facilitates monitoring of the electrochemical responses. Upon addition of an OPP, it will be bound by the aptamer. This results in an opening of the hairpin structure. Thus, Fc is shifted away from the surface of the electrode. As a result, the impedance increases and the redox signal of Fc decreases. The electrochemical performance, binding capacity and response of the aptasensor for profenofos, phorate, isocarbophos and omethoate were studied. The limits of detection are as low as 0.01, 0.1, 0.01 and 0.1 nM, respectively. Graphical abstract Schematic representation of an electrochemical aptasensor prepared by immobilizing ferrocene (Fc) labeled hairpin aptamer (HP) on the surface of graphene oxide-chitosan (GO-chit) modified electrode, and its application to the determination of organophosphorus pesticides (OPPs) by voltammetry.

Relationships between aneurysmal wall enhancement and conventional risk factors in patients with intracranial aneurysm: A high-resolution MRI study.

BACKGROUND AND PURPOSE: Aneurysmal wall enhancement (AWE) is thought to reflect wall inflammation and is a novel imaging biomarker for intracranial aneurysm (IA) risk evaluation. However, the relationship between AWE and other conventional risk factors (e.g., size) remains unclear. The aim of this study was to investigate the relationship between AWE and other risk factors. MATERIAL AND METHODS: Seventy-six consecutive patients from February 2016 to April 2017 with 88 unruptured IAs were reviewed. Patients and IAs were divided into with AWE and without AWE groups according to high-resolution magnetic resonance imaging (HRMRI) images. In addition to the patients' clinical characteristics, the features of the IAs (e.g., size and aspect ratio (AR)) were evaluated via computed tomography angiography. Multiple logistic regression analysis was used to identify the association between AWE and other risk factors. A receiver operating characteristic curve analysis was performed for the final model to obtain optimal thresholds. RESULTS: IAs with an irregular shape (OR 12.544) and a high AR (OR 32.891) were associated with AWE. The threshold value of the AR was 1.05. CONCLUSIONS: AWE on contrast-enhanced HRMRI was correlated with IAs with an irregular shape and a high AR. AWE may be a marker of instability and even risk of rupture.

Risk factors for ruptured intracranial aneurysms.

BACKGROUND & OBJECTIVES: The treatment of unruptured intracranial aneurysms (IAs) remains controversial; the ability to predict the risk of rupture for an aneurysm would be of clinical value. The aim of this study was to determine and evaluate the predictive value of the risk factors of IA rupture. METHODS: This retrospective study involved 379 consecutive patients with 441 aneurysms between August 2011 and July 2014. Based on clinical data and computed tomography angiography findings, the potential of risk factors to predict the aneurysmal rupture was assessed using statistical methods. RESULTS: Age, hypertension, heart disease, diabetes mellitus, cerebral atherosclerosis, aneurysms located at the internal carotid artery (ICA) and neck width (N) correlated negatively with rupture risk. Aneurysms located at the anterior communicating artery, bifurcation, irregularity, with a daughter sac, aneurysm height, maximum size, aspect ratio (AR), height-to-width ratio and bottleneck factor were significantly and positively correlated with rupture risk. The multivariate logistic regression model revealed that bifurcation aneurysm, irregular aneurysm and high AR increased the rupture risk, while cerebral atherosclerosis, aneurysm located on the ICA and greater N decreased the risk. Receiver operating characteristic analysis of AR curve values differed according to circumstances. INTERPRETATION & CONCLUSIONS: Cerebral atherosclerosis, location in the ICA and larger N were the protective factors against aneurysm rupture, and IAs located at bifurcations, irregular shape and increased AR indicated a greater rupture risk.

MR molecular imaging of tumours using ferritin heavy chain reporter gene expression mediated by the hTERT promoter.

OBJECTIVES: Using the human telomerase reverse transcriptase (hTERT) promoter and the modified ferritin heavy chain (Fth) reporter gene, reporter gene expression for MRI was examined in telomerase positive and negative tumour cells and xenografts. METHODS: Activity of the reporter gene expression vector Lenti-hTERT-Fth1-3FLAG-Puro was compared to constitutive CMV-driven expression and to the untransfected parental control in five tumour cell lines: A549, SKOV3, 293T, U2OS and HPDLF. In vitro, transfected cells were evaluated for FLAG-tagged protein expression, iron accumulation and transverse relaxation. In vivo, tumours transduced by lentiviral vector injection were imaged using T2*WI. Changes in tumour signal intensity were validated by histology. RESULTS: Only telomerase positive tumour cells expressed FLAG-tagged Fth and displayed an increase in R2* above the parental control, with a corresponding change in T2*WI. In addition, only telomerase positive tumours, transduced by injection of the reporter gene expression construct, exhibited a change in signal intensity on T2*WI. Tumour histology verified the expression of FLAG-tagged Fth and iron accumulation in telomerase positive tissue. CONCLUSION: Reporter gene expression for MRI, using the Fth reporter and the hTERT promoter, may be a useful strategy for the non-invasive diagnosis of many types of cancer. KEY POINTS: • Modified heavy chain of ferritin can serve as an MR reporter gene • hTERT promoter can direct the expression of reporter gene in cancer cells • MR reporter imaging mediated by hTERT promoter can be used for cancer diagnosis.

Research progress on preparation methods and sensing applications of molecularly imprinted polymer-aptamer dual recognition elements.

The aptamer (Apt) and the molecularly imprinted polymer (MIP), as effective substitutes for antibodies, have received widespread attention from researchers because of their creation. However, the low stability of Apt in harsh detection environment and the poor specificity of MIP have hindered their development. Therefore, some researchers have attempted to combine MIP with Apt to explore whether the effect of "1 + 1 > 2" can be achieved. Since its first report in 2013, MIP-Apt dual recognition elements have become a highly focused research direction in the fields of biology and chemistry. MIP-Apt dual recognition elements not only possess the high specificity of Apt and the high stability of MIP in harsh detection environment, but also have high sensitivity and affinity. They have been successfully applied in medical diagnosis, food safety, and environmental monitoring fields. This article provides a systematic overview of three preparation methods for MIP-Apt dual recognition elements and their application in eight different types of sensors. It also provides effective insights into the problems and development directions faced by MIP-Apt dual recognition elements.

A simple and effective machine learning model for predicting the stability of intracranial aneurysms using CT angiography.

Background: It is vital to accurately and promptly distinguish unstable from stable intracranial aneurysms (IAs) to facilitate treatment optimization and avoid unnecessary treatment. The aim of this study is to develop a simple and effective predictive model for the clinical evaluation of the stability of IAs. Methods: In total, 1,053 patients with 1,239 IAs were randomly divided the dataset into training (70%) and internal validation (30%) datasets. One hundred and ninety seven patients with 229 IAs from another hospital were evaluated as an external validation dataset. The prediction models were developed using machine learning based on clinical information, manual parameters, and radiomic features. In addition, a simple model for predicting the stability of IAs was developed, and a nomogram was drawn for clinical use. Results: Fourteen machine learning models exhibited excellent classification performance. Logistic regression Model E (clinical information, manual parameters, and radiomic shape features) had the highest AUC of 0.963 (95% CI 0.943-0.980). Compared to manual parameters, radiomic features did not significantly improve the identification of unstable IAs. In the external validation dataset, the simplified model demonstrated excellent performance (AUC = 0.950) using only five manual parameters. Conclusion: Machine learning models have excellent potential in the classification of unstable IAs. The manual parameters from CTA images are sufficient for developing a simple and effective model for identifying unstable IAs.

Rupture risk of intracranial aneurysms: Comparison between small ruptured intracranial aneurysms and large unruptured intracranial aneurysms.

To compare the differences in clinical and morphological features between small ruptured intracranial aneurysms and large unruptured intracranial aneurysms to evaluate the risk factors for the rupture of IAs. The clinical data of 189 consecutive patients with 193 IAs were reviewed. The patients and IAs were divided into ruptured (<5 mm) and unruptured groups (>10 mm). The characteristics of the patients and the intracranial aneurysms (IAs) were compared between the 2 groups, and the risk factors for rupture of IAs were assessed using multiple logistic regression. Patient age (odds ratio [OR], 0.955), IA located at the internal carotid artery (ICA, OR, 0.202), irregular shape (OR, 0.083) and parent vessel diameter (OR, 0.426) were negatively correlated with the risk of IA rupture. IAs located at bifurcations (OR, 6.766) were positively correlated with the risk of IA rupture. In addition to the size of the IAs, regardless of IAs shape, other factors, such as younger age (<63.5 years), location at a bifurcation, IAs located at the ICA and a small parent vessel diameter (<3.25 mm), can influence the risk of IA rupture.

Preparation of dual recognition adsorbents based on molecularly imprinted polymers and aptamer for highly sensitive recognition and enrichment of ochratoxin A.

In light of the significant risks that mycotoxins posed to public health and environmental safety, this research developed an adsorbent MIPs/Apt/AuNPs@ZIF-67 (MA-AZ) utilizing a dual-recognition approach combining molecularly imprinted polymers (MIPs) and aptamer (Apt). This innovative method enabled the effective and highly selective recognition and enrichment of ochratoxin A (OTA). ZIF-67 was utilized as a carrier with a substantial specific surface area, and gold nanoparticles (AuNPs) were loaded on its surface to fix the thiol-modified Apt on the surface of the carrier. Then, an initiator was used to initiate a polymerization reaction, and the generated MIPs coated Apt/AuNPs@ZIF-67, thereby synthesizing the MA-AZ with a "synergistic recognition" effect. The Apt significantly increased the number of recognition sites within the imprinted cavities, and MIPs played roles in identifying targets, fixing and protecting Apt. The combination of the both produced the effect of "1+1>2". The study on the adsorption performance of MA-AZ found that the adsorption capacity of MA-AZ could reach 65.1 mg/g, and the imprinted factor was 5.48. In addition, MA-AZ exhibited excellent stability, specificity, reusability and recovery rate. Thus, this study offers valuable insights for the recognition and enrichment of hazardous substances, and helps to promote the rapid development of safety detection.

Recent progress of the research of metal-organic frameworks-molecularly imprinted polymers (MOFs-MIPs) in food safety detection field.

Food safety is an important cornerstone of protecting human health and life. Therefore, it is of great significance to detect possible pollutants in food sensitively and efficiently. Molecularly imprinted polymers (MIPs) and metal-organic frameworks (MOFs) have been widely used in the adsorption and detection of food pollutants. However, traditional MIPs have problems such as uneven loading of the imprinted cavity and slow mass transfer efficiency. While the adsorption of MOFs has low specificity and cannot accurately identify target molecules. Therefore, some researchers have taken advantage of the high specific recognition abilities of MIPs and the large specific surface areas, high porosity and easy functionalization of MOFs to combine MOFs with MIPs, and have achieved a series of important results in the field of food safety detection. This paper reviews the research progress of the application of MOFs-MIPs in the field of food safety detection from 2019 to 2024. It furnishes researchers interested in this domain with a rapid and comprehensive grasp of the latest research status, it also offers them a chance to anticipate future development trends, thereby supporting the continuous advances of MOFs-MIPs in food safety detection.

Functional evaluation of pure natural edible Ferment: protective function on ulcerative colitis.

Purpose: To investigate the therapeutic efficiency of a novel drink termed "Ferment" in cases of ulcerative colitis (UC) and its influence on the gut microbiota. Method: In this study, we developed a complex of mixed fruit juice and lactic acid bacteria referred to as Ferment. Ferment was fed to mice for 35 days, before inducing UC with Dextran Sulfate Sodium Salt. We subsequently investigated the gut microbiome composition using 16S rRNA sequencing. Result: After Ferment treatment, mouse body weight increased, and animals displayed less diarrhea, reduced frequency of bloody stools, and reduced inflammation in the colon. Beneficial bacteria belonging to Ileibacterium, Akkermansia, and Prevotellacea were enriched in the gut after Ferment treatment, while detrimental organisms including Erysipelatoclostridium, Dubosiella, and Alistipes were reduced. Conclusion: These data place Ferment as a promising dietary candidate for enhancing immunity and protecting against UC.

MXene/Hydrogel-based bioelectronic nose for the direct evaluation of food spoilage in both liquid and gas-phase environments.

Various bioelectronic noses have been recently developed for mimicking human olfactory systems. However, achieving direct monitoring of gas-phase molecules remains a challenge for the development of bioelectronic noses due to the instability of receptor and the limitations of its surrounding microenvironment. Here, we report a MXene/hydrogel-based bioelectronic nose for the sensitive detection of liquid and gaseous hexanal, a signature odorant from spoiled food. In this study, a conducting MXene/hydrogel structure was formed on a sensor via physical adsorption. Then, canine olfactory receptor 5269-embedded nanodiscs (cfOR5269NDs) which could selectively recognize hexanal molecules were embedded in the three-dimensional (3D) MXene/hydrogel structures using glutaraldehyde as a linker. Our MXene/hydrogel-based bioelectronic nose exhibited a high selectivity and sensitivity for monitoring hexanal in both liquid and gas phases. The bioelectronic noses could sensitively detect liquid and gaseous hexanal down to 10-18 M and 6.9 ppm, and they had wide detection ranges of 10-18 - 10-6 M and 6.9-32.9 ppm, respectively. Moreover, our bioelectronic nose allowed us to monitor hexanal levels in fish and milk. In this respect, our MXene/hydrogel-based bioelectronic nose could be a practical strategy for versatile applications such as food spoilage assessments in both liquid and gaseous systems.

Compare deep learning model and conventional logistic regression model for the identification of unstable saccular intracranial aneurysms in computed tomography angiography.

Background: It is crucial to distinguish unstable from stable intracranial aneurysms (IAs) as early as possible to derive optimal clinical decision-making for further treatment or follow-up. The aim of this study was to investigate the value of a deep learning model (DLM) in identifying unstable IAs from computed tomography angiography (CTA) images and to compare its discriminatory ability with that of a conventional logistic regression model (LRM). Methods: From August 2011 to May 2021, a total of 1,049 patients with 681 unstable IAs and 556 stable IAs were retrospectively analyzed. IAs were randomly divided into training (64%), internal validation (16%), and test sets (20%). Convolutional neural network (CNN) analysis and conventional logistic regression (LR) were used to predict which IAs were unstable. The area under the curve (AUC), sensitivity, specificity and accuracy were calculated to evaluate the discriminating ability of the models. One hundred and ninety-seven patients with 229 IAs from Banan Hospital were used for external validation sets. Results: The conventional LRM showed 11 unstable risk factors, including clinical and IA characteristics. The LRM had an AUC of 0.963 [95% confidence interval (CI): 0.941-0.986], a sensitivity, specificity and accuracy on the external validation set of 0.922, 0.906, and 0.913, respectively, in predicting unstable IAs. In predicting unstable IAs, the DLM had an AUC of 0.771 (95% CI: 0.582-0.960), a sensitivity, specificity and accuracy on the external validation set of 0.694, 0.929, and 0.782, respectively. Conclusions: The CNN-based DLM applied to CTA images did not outperform the conventional LRM in predicting unstable IAs. The patient clinical and IA morphological parameters remain critical factors for ensuring IA stability. Further studies are needed to enhance the diagnostic accuracy.

A deep-learning-based framework for identifying and localizing multiple abnormalities and assessing cardiomegaly in chest X-ray.

Accurate identification and localization of multiple abnormalities are crucial steps in the interpretation of chest X-rays (CXRs); however, the lack of a large CXR dataset with bounding boxes severely constrains accurate localization research based on deep learning. We created a large CXR dataset named CXR-AL14, containing 165,988 CXRs and 253,844 bounding boxes. On the basis of this dataset, a deep-learning-based framework was developed to identify and localize 14 common abnormalities and calculate the cardiothoracic ratio (CTR) simultaneously. The mean average precision values obtained by the model for 14 abnormalities reached 0.572-0.631 with an intersection-over-union threshold of 0.5, and the intraclass correlation coefficient of the CTR algorithm exceeded 0.95 on the held-out, multicentre and prospective test datasets. This framework shows an excellent performance, good generalization ability and strong clinical applicability, which is superior to senior radiologists and suitable for routine clinical settings.

Clear cell tumor of the lung: a case report and literature review.

Clear cell tumor of the lung is a rare and benign pulmonary tumor; only sporadic cases have been reported. Here, we report the case of a 38-year-old man with recurrent cough, blood-streaked sputum and left chest pain. A chest computed tomography scan showed a round, homogeneous pulmonary mass in the left lower lobe, which exhibited intense heterogeneous enhancement in the arterial phase and homogeneous in the delay phase after injecting a contrast agent. The patient underwent a fine-needle aspiration biopsy and was diagnosed as having a benign clear cell tumor of the lung. The clinical presentation and radiographic investigation of this tumor are summarized in this paper to recognize this rare disease. Interestingly, we found some differences with previously reported cases.

Effects of genes required for exopolysaccharides biosynthesis in Lacticaseibacillus paracasei S-NB on cell surface characteristics and probiotic properties.

The cell surface of lactic acid bacteria (LAB) plays an essential role in cell-cell and cell-host interactions. Exopolysaccharides (EPSs) are produced on the cell surface of LAB or in the surrounding medium and are considered to be in favor of the strain- specific probiotic surface characteristics. In this work, the structure features of EPS from Lacticaseibacillus paracasei S-NB were analyzed preliminarily, and the genes involved in EPS biosynthesis of S-NB strain were hypothesized and annotated, and their role in phenotypic characteristics were demonstrated by gene deletion analysis. Four mutant strains with deletion of crucial genes involved in EPS synthesis were analyzed for strain characteristics that are closely related to their ability to interact with the host intestinal epithelium cells, including strain surface characteristics and viability under the gastrointestinal stress conditions (both acid and bile stress). Furthermore, the adherence and immunomodulatory properties of wild-type S-NB and its mutant strains were compared using Caco-2 and RAW 264.7 cell lines, respectively. Taken together, the results indicated the importance of genes associated with EPS biosynthesis in L. paracasei S-NB as a determinant in strain surface characteristics and cell-host interaction, especially for S-NB_2176 (responsible for EPS polymerization) and S-NB_2175 (responsible for CpsD/CapB family tyrosine-protein kinase).

Novel Broad-Spectrum Aptamer Used to Build Fe-Co Nanoporous Carbon Highly Sensitive Sensing Platform for the Detection of Multiple Organophosphorus Pesticides.

In this work, broad-spectrum aptamers for organophosphorus pesticides (OPs) were obtained by alternate target systematic evolution of ligands by exponential enrichment screening. The secondary and tertiary structure analyses of the aptamer inferred that the neck-loop structure formed a G-triplex structure with the target. In addition, optimization of the sheared aptamer resulted in a stronger affinity (Kd = 86.74 nM), which was increased by 2 orders of magnitude compared to similar aptamers. A novel electrochemical biosensor was prepared by modifying an aptamer labeled with an electroactive substance (methylene blue) on the surface of nanoporous carbon containing Fe-Co (Fe-Co/NPC). When a target bound to the aptamer, a G-triplex structure was formed close to the electrode surface. The aptamer phosphate backbone labeled with methylene blue enhanced the electron-transfer efficiency and resulted in signal changes. The biosensor exhibited an excellent sensitivity (7.32 fM) and a wide detection range (1 × 10-13 to 1 × 10-3 M) for OPs under optimal conditions, enabling simultaneous detection of multiple OPs in vegetables.

Hydrogel-based Bioelectronic Tongue for the Evaluation of Umami Taste in Fermented Fish.

Bioelectronic tongues based on umami taste receptors have recently been reported for versatile applications such as food analyses. However, their practical applications are still limited, partly due to their limited stability and non-specific responses in real sample environments. Herein, we have developed a hydrogel-based bioelectronic tongue for the sensitive assessment of umami intensity in fish extract samples. In this study, the T1R1 venus flytrap of an umami taste receptor was immobilized on the gold floating electrodes of a carbon nanotube-based field-effect transistor. A polyacrylamide conducting hydrogel film was further hybridized on the sensor surface via physical adsorption, which could provide a good physiological environment to maintain the activity of receptors due to its excellent hydrophilicity and biocompatibility. The bioelectronic tongue with a receptor-embedded hydrogel structure showed a sensitive detection of umami substances down to 1 fM, and it also had a wide detection range of 10-15-10-2 M for monosodium glutamate and disodium inosinate, which covers the human taste threshold. More importantly, the proposed sensor could significantly reduce the non-specific binding of non-target molecules to a carbon nanotube channel as well as exhibit long-term stability, enabling sensitive detection of umami substances even in fish extract samples. Our hydrogel-based bioelectronic tongue provides a promising platform for future applications such as the flavor evaluation of foods and beverages.

A Prospective Follow-up Study on Risk Factors to Predict the Progression of Unruptured Intracranial Aneurysms on Enhanced HR-MRI.

RATIONALE AND OBJECTIVES: To prospectively investigate the potential correlation between qualitative and quantitative assessment of aneurysm wall enhancement (AWE) on initial enhanced high-resolution magnetic resonance imaging (HR-MRI) and aneurysm progression during follow-up. MATERIALS AND METHODS: From June 2016 to January 2021, we prospectively recruited patients with unruptured intracranial aneurysms (UIAs) for enhanced HR-MRI examination. The patients' demographic and clinical data and aneurysm characteristics, including AWE features, were collected and analyzed. Follow-up images were compared to evaluate IA progression. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify the risk factors associated with aneurysm progression. RESULTS: Seventy-seven patients with 95 UIAs met our research criteria, and the median follow-up time was 15.7 months. Progression was observed in 18 aneurysms; the remaining 77 remained stable. Progressive UIAs were larger in size, more frequently displayed obvious AWE and showed a higher enhancement ratio (ER) than nonprogressive UIAs. Multivariate Cox regression analysis showed that both ER (hazard ratio, 6.304, p < 0.001) and aneurysm size (hazard ratio, 1.343, p = 0.014) were independent risk factors for aneurysm progression. The combination of ER and aneurysm size had an area under the curve of 0.920 for the prediction of aneurysm progression, with a sensitivity of 88.9% and specificity of 87.0%. CONCLUSION: A higher ER value of the aneurysm wall and a larger aneurysm size on initial HR-MRI may predict an increased risk of aneurysm progression, which suggests that closer monitoring by imaging or preventive intervention may be required for the clinical management of these aneurysms.

Portable electrochemiluminescence detection system based on silicon photomultiplier single photon detector and aptasensor for the detection of tetracycline in milk.

In this work, a portable electrochemiluminescence (ECL) detection system based on silicon photomultiplier (SiPM) single photon detector was proposed for the detection of ECL signals on a screen-printed electrode (SPE). This instrument innovatively used SiPM single photon detector to detect the ECL signal, which solved friability and bloat caused by the high operating voltage and the limitation of detection components in the traditional ECL detection instrument. This detection instrument showed excellent electrochemical and ECL detection performance. On this basis, an aptasensor based on silver (core)-gold (shell) bimetallic nanoparticles (Ag@AuNPs) was constructed for the detection of tetracycline (TET) in milk on SPE. Here, Ag@AuNPs had a significant effect in enhancing luminol ECL signal and immobilizing aptamer. The concentration of TET was detected according to the changes of the ECL signal intensity of the detection instrument. This instrument exhibited an excellent linearity ranging from 0.01 ng/mL to 1,000 ng/mL for the detection of TET, and a limit of detection (LOD) was 0.0053 ng/mL. The developed portable ECL detection instrument provides a new platform for the detection of small molecule contaminants.