A enzyme-free fluorescence quenching sensor for amplified detection of kanamycin in milk based on competitive triggering strategies.

In this work, we constructed a FAM fluorescence quenching biosensor based on an aptamer competition recognition and enzyme-free amplification strategy. We design a competing unit consisting of an aptamer chain and a complementary chain, and a catalytic hairpin self-assembly (CHA) unit consisting of two hairpins in which the complementary chain can trigger the catalytic hairpin self-assembly. In the initial state, the aptamer chain is combined with the complementary chain, the catalytic hairpin self-assembly unit is inhibited, the FAM fluorescence group was far away from the BHQ1 quenching group, and the fluorescence is turn-on. In the presence of kanamycin, the aptamer chain recognizes kanamycin and doesn't form double chains, resulting in the free complementary chain triggering hairpin 1 (H1), and then H1 triggering hairpin 2 (H2), FAM fluorophore is close to the BHQ1 quenching group, and the fluorescence is off-on. When H1 and H2 form a cyclic reaction, enzyme-free amplification is achieved and there is significant output of the fluorescence signal. Therefore, the biosensor has good performance in detecting kanamycin, the detection line is 54 nM, the linear range is 54 nM-0.9 µM, and it can achieve highly selective detection of kanamycin. Kanamycin residue may cause serious harm to human health. The high sensitivity detection of kanamycin is urgent, so this project has a great application potential for food detection.

A label free fluorescent aptamer sensor based on the combined action of Graphene oxide and SYBR Green I for the detection of Aflatoxin B1.

Here, based on the characteristics of Graphene oxide(GO) and SYBR Green I(SGI) dye, an enzyme-free and label-free fluorescent biosensor with signal amplification through DNA strand reaction is proposed for the detection of Aflatoxin B1(AFB1) in food safety. Firstly, without the addition of AFB1, the substrate in the system includes a double stranded Apt-S with a long sticky end and two hairpins H1 and H2. Although the complementary pairing of bases may exhibit fluorescence due to the insertion of SGI dyes, the use of GO, which is highly capable of adsorbing single stranded parts and quenching fluorescence, cleverly reduces the background fluorescence. Adding the target AFB1 triggers DNA inter chain reactions, generating a large amount of long double stranded DNA H1-H2, thereby generating strong fluorescence signals under the action of SGI. More importantly, logical theory verification and computer simulation were conducted before biological experiments, providing a theoretical basis for the implementation of the biosensor. After analysis, the fluorescence biosensor exhibits a good linear relationship with AFB1 concentration in the range of 5-50nM, with a detection limit of 0.76nM. It also has good specificity, anti-interference ability, and practical application ability, and has broad application prospects in the field of food safety.

Head and Neck Tumor Segmentation from [18F]F-FDG PET/CT Images Based on 3D Diffusion Model.

Head and neck (H&N) cancers are among the most prevalent types of cancer worldwide, and [18F]F-FDG PET/CT is widely used for H&N cancer management. Recently, the diffusion model has demonstrated remarkable performance in various image-generation tasks. In this work, we proposed a 3D diffusion model to accurately perform H&N tumor segmentation from 3D PET and CT volumes. The 3D diffusion model was developed considering the 3D nature of PET and CT images acquired. During the reverse process, the model utilized a 3D UNet structure and took the concatenation of PET, CT, and Gaussian noise volumes as the network input to generate the tumor mask. Experiments based on the HECKTOR challenge dataset were conducted to evaluate the effectiveness of the proposed diffusion model. Several state-of-the-art techniques based on U-Net and Transformer structures were adopted as the reference methods. Benefits of employing both PET and CT as the network input as well as further extending the diffusion model from 2D to 3D were investigated based on various quantitative metrics and the uncertainty maps generated. Results showed that the proposed 3D diffusion model could generate more accurate segmentation results compared with other methods. Compared to the diffusion model in 2D format, the proposed 3D model yielded superior results. Our experiments also highlighted the advantage of utilizing dual-modality PET and CT data over only single-modality data for H&N tumor segmentation.

Development and analysis of a universal label-free micro/nano component for three-channel detection of silver ions, mercury ions, and tetracycline.

In this paper, an enzyme-free and label-free fluorescent nanomodule is proposed for rapid, simple and sensitive detection of Ag+, Hg2+ and tetracycline (TC). The strategy is cleverly designed to enable multiple-purpose detection with as little as 31 nt of ssDNA. Both the embedded dye SYBR Green I and the nanomaterial graphene oxide (GO) are able to distinguish single-stranded DNA from double-stranded DNA; thus, the combination of the two instead of using traditional molecular beacon (MB)-labeled fluorophores and quencher groups can effectively reduce the cost of experiments while efficiently reducing the background noise. Performance testing experiments confirmed the stability and selectivity of the platform; the limits of detection (LODs) of Ag+ and Hg2+ were 1.41 nM and 1.79 nM, respectively, and the detection range were within the WHO standards. In addition, only some base sequences in the flexible functional domain of the nanoloop needed to be programmed to build a universal platform, which was feasible using TC as a target. Therefore, the designed nanomodule has the potential to detect various types of targets, such as antibiotics, proteins, and target genes, and has broad application prospects in environmental monitoring, food testing, and disease diagnosis.

Design and Simulation of an Autonomous Molecular Mechanism Using Spatially Localized DNA Computation.

As a well-established technique, DNA synthesis offers interesting possibilities for designing multifunctional nanodevices. The micro-processing system of modern semiconductor circuits is dependent on strategies organized on silicon chips to achieve the speedy transmission of substances or information. Similarly, spatially localized structures allow for fixed DNA molecules in close proximity to each other during the synthesis of molecular circuits, thus providing a different strategy that of opening up a remarkable new area of inquiry for researchers. Herein, the Visual DSD (DNA strand displacement) modeling language was used to design and analyze the spatially organized DNA reaction network. The execution rules depend on the hybridization reaction caused by directional complementary nucleotide sequences. A series of DNA strand displacement calculations were organized on the locally coded travel track, and autonomous movement and addressing operations are gradually realized. The DNA nanodevice operates in this manner follows the embedded "molecular program", which improves the reusability and scalability of the same sequence domain in different contexts. Through the communication between various building blocks, the DNA device-carrying the target molecule moves in a controlled manner along the programmed track. In this way, a variety of molecular functional group transport and specific partition storage can be realized. The simulation results of the visual DSD tool provide qualitative and quantitative proof for the operation of the system.

Potential Universal Engineering Component: Tetracycline Response Nanoswitch Based on Triple Helix-Graphene Oxide.

The overuse of antibiotics can lead to the emergence of drug resistance, preventing many common diseases from being effectively treated. Therefore, based on the special composite platform of P1/graphene oxide (GO) and DNA triple helix, a programmable DNA nanoswitch for the quantitative detection of tetracycline (TC) was designed. The introduction of GO as a quenching agent can effectively reduce the background fluorescence; stabilizing the trigger strand with a triplex structure minimizes errors. It is worth mentioning that the designed model has been verified and analyzed by both computer simulation and biological experiments. NUPACK predicts the combined mode and yield of each strand, while visual DSD flexibly predicts the changes in components over time during the reaction. The feasibility analysis preliminarily confirmed the realizability of the designed model, and the optimal reaction conditions were obtained through optimization, which laid the foundation for the subsequent quantitative detection of TC, while the selective experiments in different systems fully demonstrated that the model had excellent specificity.

Developing a DNA logic gate nanosensing platform for the detection of acetamiprid.

This paper reports a novel fluorescence and colorimetric dual-signal-output DNA aptamer based sensor for the detection of acetamiprid residue. Acetamiprid is a new systemic broad-spectrum insecticide with high insecticidal efficiency that is widely used worldwide, but there is a risk of adverse neurological reactions in humans and animals. The dual-mode output principle designed in this paper, consisting of a fluorescence signal and colorimetric signal, is based on the relevant reaction of the special domain of a G-quadruplex, bidding farewell to a classical single-signal output, with a target-recognition cycle used to complete signal amplification through a hybridization chain reaction. Upgraded detection sensitivity and the qualitative and semi-quantitative detection of acetamiprid are achieved based on the fluorescence signal output and visual discrimination observations during colorimetric experiments. This model was applied to the determination of acetamiprid residue in fruits and vegetables. The dual-detection platform further reduced systematic error, with a detection limit of 27.7 pM. When applied in a comparative detection study using three different pesticides, the system shows excellent discrimination specificity and it performs well in actual sample detection and has a fast response time. Designing DNA logic gates that operate in the presence of targets and molecular-switch-based detection platforms also involves the intersection of biology and computational modeling, providing new ideas for biological platforms.

A Biosensor Based on Interchain Reactions for the Detection of Acetamiprid and the Construction of Basic Logic Gates OR and AND.

An enzyme-free and label-free fluorescent DNA aptasensor was constructed with computer assistance based on thermodynamic deviation driving interchain reactions. In this work, in the presence of target acetamiprid, the released trigger strand C-apt could open hairpin Hp1, which in turn triggered the strand displacement reaction and catalyzed the self-assembly of hairpins Hp1 and Hp2, so that the guanine base rich stem in Hp2 was opened. In the presence of K+ and NMM, the G-rich moiety could form a G-quadruplex and emit strong fluorescence at a specific excitation wavelength. The proposed strategy enables sensitive detection of acetamiprid at concentrations as low as 54.3 pM. Most importantly, computer-assisted analysis of the thermodynamic properties of nucleic acid strands and simulation of the reaction process and conditions of the proposed model before conducting biological experiments theoretically proves this strategy feasible and may simplify subsequent biological experiments. In addition, basic molecular logic gates, including OR and AND, were constructed based on this detection principle, and simulation tests and biological experiments were performed. The final results show that this strategy can not only have some applications in the field of food safety and environmental monitoring, but also provide a certain way for the development of molecular logic computing.

A Label-Free Fluorescent AND Logic Gate Aptasensor for Carbohydrate Antigen 15-3 Detection Based on Graphene Oxide.

BACKGROUND: Molecular logic gate always makes use of fluorescent dyes to realize fluorescence signals. The labeling of the fluorophore is relatively expensive, resulting in low yield, and singly labeled impurities affect the affinity between the target and the aptamer. Label-free fluorescent aptamer biosensor strategy has attracted widespread interest due to lower cost and simplicity. OBJECTIVE: Herein, we have designed an AND logic gate fluorescent aptasensor for detecting carbohydrate antigen 15-3(CA15-3) based on label-free fluorescence signal output. MATERIALS AND METHODS: A hairpin DNA probe consists of CA15-3 aptamer and partly anti-CA15- 3 aptamer sequences as a long stem and G-rich sequences of the middle ring as a quadruplexforming oligomer. G-rich sequences can fold into a quadruplex by K+, and then G-quadruplex interacts specifically with N-methylmesoporphyrin IX(NMM), leading to a dramatic increase in fluorescence of NMM. With CA15-3 and NMM as the two inputs, the fluorescence intensity of the NMM is the output signal. Lacking CA15-3 or NMM, there is no significant fluorescence enhancement, and the output of the signal is "0". The fluorescence signal dramatically increases and the output of the signal is "1" only when CA15-3 protein and NMM are added at the same time. RESULTS: This biosensor strategy was observed to possess selectivity and high sensitivity for detecting CA15-3 protein from 10 to 500 U mL-1 and the detection limit was found to be 10 U mL-1, which also showed good reproducibility in spiked human serum. CONCLUSION: In summary, the proposed AND logic gate fluorescent aptasensor could specifically detect CA15-3.

Developing a three-input cascade DNA logic gate based on the biological characteristics of metal ion-GO, combined with analysis and verification.

Due to the limitation of technology, electronic computing is approaching the limit of technology, and new computing tools need to be developed. Here, we build a three-input cascade logic gate based on the advantages of biomolecules, particularly DNA, in the construction of computational logic systems, combined with metal ions and graphene oxide (GO). It is worth mentioning that this study uses a variety of research methods. In addition to the commonly used biological experiments, NUPACK and visual DSD simulation methods are used for analysis, and orthogonal, standardized and other statistical means are used to simplify the experimental process and make the results intuitive. Finally, the designed three-input logic gate is successfully constructed, and it is found that it may have the potential to realize complex computing.

A Label-free "Lock-key" Fluorescence Aptasensing Based on Triplex-helix DNA and G-quadruplex for CA15-3 Detection.

Herein, we designed a label-free fluorescent aptasensor based on triple-helix DNA and G-quadruplex for carbohydrate antigen (CA15-3) detection. The triplex-helix structure can be formed with inserted G-rich DNA (IG) and aptamer DNA (Apt), which like a "lock" to lock the G-rich sequences. The CA15-3 was the "key", which specifically combined with aptamer sequences of Apt, resulting in liberating IG from the triplex-helix "lock". Then, the G-rich sequences of IG were formed into G-quadruplex and specifically interacted with N-methylmesoporphyrin IX (NMM), which greatly enhanced the fluorescence of the solution. However, when the "key" did not exist, the "lock" was fastened and fluorescence intensity did not change. With this proposed method, the concentration of CA15-3 can be effectively detected from 0.01 to 5 U mL-1 with a detection limit (LOD) of 0.01 U mL-1. Furthermore, this proposed biosensor can be applied to spiked human serum with great precision and reproducibility.

Enzyme-free and DNA-based universal platform for the construction of various logic devices based on graphene oxide and G-quadruplex.

In the fields of biocomputing and biomolecular, DNA molecules are applicable to be regarded as data of logical computing platform that uses elaborate logic gates to perform a variety of tasks. Graphene oxide (GO) is a type of novel nanomaterial, which brings new research focus to materials science and biosensors due to its special selectivity and excellent quenching ability. G-quadruplex as a unique DNA structure stimulates the intelligent application of DNA assembly on the strength of its exceptional binding activity. In this paper, we report a universal logic device assisted with GO and G-quadruplex under an enzyme-free condition. Integrated with the quenching ability of GO to the TAMRA (fluorophore, Carboxytetramethylrhodamine) and the enhancement of fluorescence intensity produced by the peculiar binding of G-quadruplex to the NMM (N-methylmesoporphyrin IX), a series of basic binary logic gates (AND. OR. INHIBIT. XOR) have been designed and verified through biological experiments. Given the modularity and programmability of this strategy, two advanced logic gates (half adder and half subtractor) were realized on the basis of the same work platform. The fluorescence signals generated from different input combinations possessed satisfactory results, which provided proof of feasibility. We believe that the proposed universal logical platform that operates at the nanoscale is expected to be utilized for future applications in molecular computing as well as disease diagnosis.

A Non-Enzyme and Non-Label Sensitive Fluorescent Aptasensor Based on Simulation-Assisted and Target-Triggered Hairpin Probe Self-Assembly for Ochratoxin a Detection.

The monitoring and control of mycotoxins has caused widespread concern due to their adverse effects on human health. In this research, a simple, sensitive and non-label fluorescent aptasensor has been reported for mycotoxin ochratoxin A (OTA) detection based on high selectivity of aptamers and amplification of non-enzyme hybridization chain reaction (HCR). After the introduction of OTA, the aptamer portion of hairpin probe H1 will combine with OTA to form OTA-aptamer complexes. Subsequently, the remainder of the opened H1 will act as an initiator for the HCR between the two hairpin probes, causing H1 and H2 to be sequentially opened and assembled into continuous DNA duplexes embedded with numerous G-quadruplexes, leading to a significant enhancement in fluorescence signal after binding with N-methyl-mesoporphyrin IX (NMM). The proposed sensing strategy can detect OTA with concentration as low as 4.9 pM. Besides, satisfactory results have also been obtained in the tests of actual samples. More importantly, the thermodynamic properties of nucleic acid chains in the monitoring platform were analyzed and the reaction processes and conditions were simulated before carrying out biological experiments, which theoretically proved the feasibility and simplified subsequent experimental operations. Therefore, the proposed method possess a certain application value in terms of monitoring mycotoxins in food samples and improving the quality control of food security.

An Enzyme- and Label-Free Fluorescence Aptasensor for Detection of Thrombin Based on Graphene Oxide and G-Quadruplex.

An enzyme- and label-free aptamer-based assay is described for the determination of thrombin. A DNA strand (S) consisting of two parts was designed, where the first (Sa) is the thrombin-binding aptamer and the second (Se) is a G-quadruplex. In the absence of thrombin, Sa is readily adsorbed by graphene oxide (GO), which has a preference for ss-DNA rather than for ds-DNA. Upon the addition of the N-methyl-mesoporphyrin IX (NMM), its fluorescence (with excitation/emission at 399/610 nm) is quenched by GO. In contrast, in the presence of thrombin, the aptamer will bind thrombin, and thus, be separated from GO. As a result, fluorescence will be enhanced. The increase is linear in the 0.37 µM to 50 µM thrombin concentration range, and the detection limit is 0.37 nM. The method is highly selective over other proteins, cost-effective, and simple. In our perception, it represents a universal detection scheme that may be applied to other targets according to the proper choice of the aptamer sequence and formation of a suitable aptamer-target pair.

Probe computing model based on small molecular switch.

BACKGROUND: DNA is a promising candidate for the construction of biological devices due to its unique properties, including structural simplicity, convenient synthesis, high flexibility, and predictable behavior. And DNA has been widely used to construct the advanced logic devices. RESULTS: Herein, a molecular probe apparatus was constructed based on DNA molecular computing to perform fluorescent quenching and fluorescent signal recovery, with an ' ON/OFF' switching function. In this study, firstly, we program the streptavidin-mediated fluorescent quenching apparatus based on short-distance strand migration. The variation of fluorescent signal is acted as output. Then DNAzyme as a switching controller was involved to regulate the fluorescent signal increase. Finally, on this base, a cascade DNA logic gate consists of two logic AND operations was developed to enrich probe machine. CONCLUSION: The designed probe computing model can be implemented with readout of fluorescence intensity, and exhibits great potential applications in the field of bioimaging as well as disease diagnosis.

Design, synthesis, evaluation and molecular modeling study of 4-N-phenylaminoquinolines for Alzheimer disease treatment.

Dual binding site acetylcholinesterase (AChE) inhibitors and butyrylcholinesterase (BChE) inhibitors have recently emerged as two classes of new anti-Alzheimer agents to positively modify the disease's course. In this work, a new series of 4-N-phenylaminoquinolines was synthesized and evaluated for their abilities to inhibit AChE and BChE. Compound 11b showed significant inhibitory activities on AChE and BChE with IC50 values of 0.86 and 2.65 µM, respectively, a lot better than that of reference drug galanthamine. Furthermore, docking study showed that compound 11b interacted simultaneously not only with active and peripheral sites of AChE, but also with all five regions of BChE active site. These findings suggest that these derivatives could be regarded as promising starting points for further drug discovery developments.

A Label-free and Universal Platform for the Construction of Various Logic Circuits Based on Graphene Oxide and G-Quadruplex Structure.

Due to structual polymorphism, excellent binding activity and functional significances in biological regulation, G-quadruplex has become the focus of research as an innovated module for analytical chemistry and biomedicine. Meanwhile, in the biosensor fields, new nanomaterial graphene oxide (GO) has also received extensive attention due to its brilliant physical and chemical properties. Herein, we propose a non-label and enzyme-free logic operation platform based on G-quadruplex structure and GO instead of any expensive modification. Taking advantage of the quenching ability of GO to AgNCs and the fluorescence enhancement of NMM (N-methylmesoporphyrin IX) mediated by the split G-quadruplex, a series of binary logic gates (AND, OR, INHIBIT, XOR) have been constructed and verified by biological experiments. Subsequently, two combinatorial logic gates were successfully realized conceptually on the basis of the same BGG platform, including half adder and half subtractor. Taken together, such a universal platform has great potential in applications, such as biocomputing, bio-imaging and disease diagnosis, which cultivate a new view for future biological research.

Label-free optical biosensor for target detection based on simulation-assisted catalyzed hairpin assembly.

The development of efficient and convenient strategy without involving enzyme or complex nanomaterial for the micro molecules detection has profound meaning in the diagnosis of diseases. Herein, taking the advantages of the strong affinity of aptamer and catalyzed hairpin assembly, we develop a new non-label optical amplified strategy for thrombin detection in this work. To support both biological inquiry and technological innovation, thermodynamic models are introduced to predict the minimum energy secondary structure of interacting nucleic acid strands and calculate the partition function and equilibrium concentration for complexes in our system. Then, the thermodynamics properties of interacting DNA strands and the reactions of toehold strand displacement-driven assembly have been simulated, validating the feasibility of the theory and optimizing the follow-up lab tests. Following that, our strategy for thrombin detection is proved to be feasible and effective in biological experiment. Taken together, such a biosensor has a good potential in bioactive molecules detection and disease diagnosis for future biological research.

A Multifunctional Molecular Probe for Detecting Hg2+ and Ag⁺ Based on Ion-Mediated Base Mismatch.

In this paper, a multifunctional biosensing platform for sensitively detecting Hg2+ and Ag⁺, based on ion-mediated base mismatch, fluorescent labeling, and strand displacement, is introduced. The sensor can also be used as an OR logic gate, the multifunctional design of sensors is realized. Firstly, orthogonal experiments with three factors and three levels were carried out on the designed sensor, and preliminary optimization of conditions was performed for subsequent experiments. Next, the designed sensor was tested the specificity and target selectivity under the optimized conditions, and the application to actual environmental samples further verified the feasibility. Generally, this is a convenient, fast, stable, and low-cost method that provides a variety of ideas and an experimental basis for subsequent research.

Single-image-based nonuniformity correction of uncooled long-wave infrared detectors: a deep-learning approach.

Fixed-pattern noise (FPN), which is caused by the nonuniform opto-electronic responses of microbolometer focal-plane-array (FPA) optoelectronics, imposes a challenging problem in infrared imaging systems. In this paper, we successfully demonstrate that a better single-image-based non-uniformity correction (NUC) operator can be directly learned from a large number of simulated training images instead of being handcrafted as before. Our proposed training scheme, which is based on convolutional neural networks (CNNs) and a column FPN simulation module, gives rise to a powerful technique to reconstruct the noise-free infrared image from its corresponding noisy observation. Specifically, a comprehensive column FPN model is utilized to depict the nonlinear characteristics of column amplifiers in the readout circuit of FPA. A large number of high-fidelity training images are simulated based on this model and the end-to-end residual deep network is capable of learning the intrinsic difference between undesirable FPN and original image details. Therefore, column FPN can be accurately estimated and further subtracted from the raw infrared images to obtain NUC results. Comparative results with state-of-the-art single-image-based NUC methods, using real-captured noisy infrared images, demonstrate that our proposed deep-learning-based approach delivers better performances of FPN removal, detail preservation, and artifact suppression.