Recognition Function Research Articles

Local Brain Network Alterations and Olfactory Impairment in Alzheimer’s Disease: An fMRI and Graph-Based Study

Alzheimer's disease (AD) is associated with the abnormal connection of functional networks. Olfactory impairment occurs in early AD; therefore, exploring alterations in olfactory-related regions is useful for early AD diagnosis. We combined the graph theory of local brain network topology with olfactory performance to analyze the differences in AD brain network characteristics. A total of 23 patients with AD and 18 normal controls were recruited for resting-state functional magnetic resonance imaging (fMRI), clinical neuropsychological examinations and the University of Pennsylvania Smell Identification Test (UPSIT). Between-group differences in the topological properties of the local network were compared. Pearson correlations were explored based on differential brain regions and olfactory performance. Statistical analysis revealed a correlation of the degree of cognitive impairment with olfactory recognition function. Local node topological properties were significantly altered in many local brain regions in the AD group. The nodal clustering coefficients of the bilateral temporal pole: middle temporal gyrus (TPOmid), degree centrality of the left insula (INS.L), degree centrality of the right middle temporal gyrus (MTG.R), and betweenness centrality of the left middle temporal gyrus (MTG.L) were related to olfactory performance. Alterations in local topological properties combined with the olfactory impairment can allow early identification of abnormal olfactory-related regions, facilitating early AD screening.

Doxorubicin-Mediated miR-433 Expression on Exosomes Promotes Bystander Senescence in Multiple Myeloma Cells in a DDR-Independent Manner.

The success of senescence-based anticancer therapies relies on their anti-proliferative power and on their ability to trigger anti-tumor immune responses. Indeed, genotoxic drug-induced senescence increases the expression of NK cell-activating ligands on multiple myeloma (MM) cells, boosting NK cell recognition and effector functions. Senescent cells undergo morphological change and context-dependent functional diversification, acquiring the ability to secrete a vast pool of molecules termed the senescence-associated secretory phenotype (SASP), which affects neighboring cells. Recently, exosomes have been recognized as SASP factors, contributing to modulating a variety of cell functions. In particular, evidence suggests a key role for exosomal microRNAs in influencing many hallmarks of cancer. Herein, we demonstrate that doxorubicin treatment of MM cells leads to the enrichment of miR-433 into exosomes, which in turn induces bystander senescence. Our analysis reveals that the establishment of the senescent phenotype on neighboring MM cells is p53- and p21-independent and is related to CDK-6 down-regulation. Notably, miR-433-dependent senescence does not induce the up-regulation of activating ligands on MM cells. Altogether, our findings highlight the possibility of miR-433-enriched exosomes to reinforce doxorubicin-mediated cellular senescence.

The Use of Oxytocin for the Treatment of Opioid Use Disorder.

Nearly 27 million people have an opioid use disorder (OUD) according to the 2016 Global Burden of Disease study, most of which occur in the US where opioids are a common class of medication used to treat acute and chronic pain. In 2016 alone, more than 60 million patients had at least one prescription for opioids filled or refilled. Over the past decade, prescription rates have risen astronomically and have created an epidemic in the US dubbed the "opioid crisis." In this regard, there has been an increase in overdoses and OUD diagnoses. Several studies have found dysregulation of balance between several neurotransmitters involved in the neural circuitry that subserves several behavioral domains, such as reward recognition, motivation, learning, and memory, affect, stress, and executive function, that contribute to the manifestation of craving. On the horizon is a new treatment approach consisting of the neuropeptide oxytocin, which may be involved in the overlapping mechanisms of stable attachment formation and coping with stress. Through this mechanism, it can shift processing from novelty and reward-seeking to an appreciation of familiarity and thus reduce stress and increase resilience in the face of addiction. It has been hypothesized that there is a connection between the glutaminergic and oxytocinergic systems, making oxytocin a possible therapeutic agent in reducing drug-induced actions seen in OUD patients. This manuscript will review the potential and feasible use of oxytocin in treating OUD.

Photoelectrocatalytic selective removal of group-targeting thiol-containing heterocyclic pollutants

The removal of a class of toxic thiol-containing heterocyclic pollutants from complex water matrices has great environmental significance. In this study, a novel photoanode (Au/MIL100(Fe)/TiO2) with dual recognition functions was designed for selective group-targeting photoelectrocatalytic removal of thiol-containing heterocyclic pollutants from various aquatic systems. The average degradation and adsorption removal efficiency of 2-mercaptobenzimidazole, 2-mercaptobenzothiazole, and 2-mercaptobenzoxazole were still above 96.7% and 13.5% after selective treatment with Au/MIL100(Fe)/TiO2 even coexisting with 10-fold concentration of macromolecular interferents (sulfide lignin and natural organic matters) and the same concentration of micromolecular structural analogues. While they were below 71.6% and 3.9% after non-selective treatment with TiO2. Targets in the actual system were selectively removed to 0.9 µg L−1, which is 1/10 of that after non-selective treatment. FTIR, XPS and operando electrochemical infrared results proved that the highly specific recognition mechanism was mainly attributable to both the size screening of MIL100(Fe) toward targets and Au-S bond formed between -SH group of targets and Au of Au/MIL100(Fe)/TiO2. •OH are the reactive oxygen species. The degradation mechanism was further investigated via excitation-emission matrix fluorescence spectroscopy and LC-MS. This study provides new guidelines for the selective group-targeting removal of toxic pollutants with characteristic functional groups from complex water matrices.

MOFs-based Fe@YAU-101/GCE electrochemical sensor platform for highly selective detecting trace multiplex heavy metal ions

The construction of sensors with specific recognition functions can easily, sensitively and efficiently detect heavy metal ions, which is a demand in the field of electrochemical sensing and an important topic in the detection of environmental pollutants. An electrochemical sensor based on MOFs composites was developed for sensing of multiplex metal ions. The large surface area, adjustable porosities and channels in MOFs facilitate successful loading of sufficient quantities highly active units. The active units and pore structures of MOFs are regulated and synergetic with each other to enhance the electrochemical activity of MOFs composites. Thus, the selectivity, sensitivity and reproducibility of MOFs composites have been improved. Fortunately, after characterization, Fe@YAU-101/GCE sensor with strong signal was successfully constructed. In the presence of target metal ions in solution, the Fe@YAU-101/GCE can efficiently and synchronously identify Hg2+, Pb2+, and Cd2+. The detection limits (LOD) are 6.67 × 10−10 M(Cd2+), 3.33 × 10−10 M(Pb2+) and 1.33 × 10−8 M (Hg2+), and are superior to the permissible limits set by the National Environmental Protection Agency. The electrochemical sensor is simple without sophisticated instrumentation and testing processes, hence promising for practical applications.

MP66-02 MISINTERPRETATIONS OF SIGNIFICANCE TESTING RESULTS NEAR THE p-VALUE THRESHOLD IN UROLOGIC LITERATURE

You have accessJournal of UrologyCME1 Apr 2023MP66-02 MISINTERPRETATIONS OF SIGNIFICANCE TESTING RESULTS NEAR THE p-VALUE THRESHOLD IN UROLOGIC LITERATURE Pranay Manda, Manish Kuchakulla, Gabrielle Hochu, Pranav Mudiam, Ali Syed, Aayush Shah, Arjun Watane, and Ranjith Ramasamy Pranay MandaPranay Manda More articles by this author , Manish KuchakullaManish Kuchakulla More articles by this author , Gabrielle HochuGabrielle Hochu More articles by this author , Pranav MudiamPranav Mudiam More articles by this author , Ali SyedAli Syed More articles by this author , Aayush ShahAayush Shah More articles by this author , Arjun WataneArjun Watane More articles by this author , and Ranjith RamasamyRanjith Ramasamy More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003329.02AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The outcome of a statistical test is to accept or reject a null hypothesis. Reporting a metric as “trending toward significance” is a misinterpretation of the p-value. Studies highlighting the prevalence of statistical errors in the urologic literature remain scarce. The objective of this study was to evaluate abstracts from 15 urology journals published between the years 2000-2021 and provide a quantitative measure of a common statistical mistake—misconstruing the function of null hypothesis testing by reporting “a trend toward significance.” METHODS: We performed an audit of 15 Urology journals, looking at articles published from January 1st, 2000 to January 1st, 2022. A word recognition function in Microsoft Excel was utilized to identify the use of the word “trend” in the abstracts. Each use of the word “trend” was manually investigated by two authors to determine whether it was improperly used in describing non-statistically significant data as trending toward significance. Statistics and data analysis were performed using Python libraries: pandas, SciPy. Stats, and seaborn. RESULTS: This study included 101,134 abstracts from 15 urology journals. Within those abstracts, the word “trend” was used 2,509 times, 572 uses of which were describing non-statistically significant data as trending toward significance. There was a statistically significant difference in the rate of errors between the 15 journals (p<0.01) (Figure 1). The highest rate of improper use of the word “trend” was found in Bladder Cancer with a rate of 1.6% (p<0.01) of articles. The lowest rate of improper use was found in European Urology with a rate of 0.3% (p<0.01). Our analysis found a moderate correlation between the number of articles published and the number of misuses of the word trend within each journal and across all journals every year (r=0.61 and 0.70 respectively). CONCLUSIONS: The overall rate of p-value misinterpretation never exceeded 2 percent of articles in each journal. There is significance in the difference in misinterpretation rates between the different journals. Authors' utilization of the word “trend” describing non-significant p-values as being near significant should be used with caution. Source of Funding: NA © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e931 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Pranay Manda More articles by this author Manish Kuchakulla More articles by this author Gabrielle Hochu More articles by this author Pranav Mudiam More articles by this author Ali Syed More articles by this author Aayush Shah More articles by this author Arjun Watane More articles by this author Ranjith Ramasamy More articles by this author Expand All Advertisement PDF downloadLoading ...

Activation of the CA2-ventral CA1 pathway reverses social discrimination dysfunction in Shank3B knockout mice

Mutation or deletion of the SHANK3 gene, which encodes a synaptic scaffolding protein, is linked to autism spectrum disorder and Phelan-McDermid syndrome, conditions associated with social memory impairments. Shank3B knockout mice also exhibit social memory deficits. The CA2 region of the hippocampus integrates numerous inputs and sends a major output to the ventral CA1 (vCA1). Despite finding few differences in excitatory afferents to the CA2 in Shank3B knockout mice, we found that activation of CA2 neurons as well as the CA2-vCA1 pathway restored social recognition function to wildtype levels. vCA1 neuronal oscillations have been linked to social memory, but we observed no differences in these measures between wildtype and Shank3B knockout mice. However, activation of the CA2 enhanced vCA1 theta power in Shank3B knockout mice, concurrent with behavioral improvements. These findings suggest that stimulating adult circuitry in a mouse model with neurodevelopmental impairments can invoke latent social memory function.

Driver Behavior Recognition Based on Neural Networks Theory

The article deals with the problem of driver behavior while driving the vehicle. Driver distraction can lead to serious accidents that threaten human life and public property around the world. Solving the problem of preventing dangerous driving behavior will reduce the risk of getting into an accident in the future. Thus, there is a need for a smart vehicle that will support driver behavior recognition functionality. A possible solution to the problem using an artificial neural network for automatic recognition of driver behavior on a real set of driver behavior data is considered. The high accuracy and efficiency of the developed model recognition is obtained.

An Image Detection–Memory–Recognition Artificial Visual Unit Based on Dual‐Gate Phototransistors

Optoelectronic synapses integrating sensing–memory–processing functions have great advantages in neuromorphic computing for visual information processing and complex learning, recognition, and memory in an energy‐efficient manner. Herein, a light‐induced bidirectional response is demonstrated in the proposed WSe2/MoS2 junction field‐effect transistor (JFET) with an extra Ge back gate. The WSe2/MoS2 JFET exhibits high responsivity and detectivity owing to effective modulation by the top junction and back dielectric gates. The unique bidirectional photoresponse and interfacial state storage properties of the device result in significant synaptic excitatory effects under visible light stimulation and remarkable synaptic inhibitory effects under infrared illumination. Optical storage with visible light and optical erasure with infrared light can be achieved in the device based on its synaptic behavior. The conductance changes under different types of illumination can be used to mimic the weight update in a neural network for image recognition. A high accuracy exceeding 98% was achieved in handwritten digit recognition. This visible and infrared dual‐band phototransistor, which integrates image perception, memory, and recognition functionalities, provides a promising solution for self‐driving, surveillance, computer vision, and biomedical imaging applications.

Human-Machine Interaction via Dual Modes of Voice and Gesture Enabled by Triboelectric Nanogenerator and Machine Learning.

With the development of science and technology, human-machine interaction has brought great benefits to the society. Here, we design a voice and gesture signal translator (VGST), which can translate natural actions into electrical signals and realize efficient communication in human-machine interface. By spraying silk protein on the copper of the device, the VGST can achieve improved output and a wide frequency response of 20-2000 Hz with a high sensitivity of 167 mV/dB, and the resolution of frequency detection can reach 0.1 Hz. By designing its internal structure, its resonant frequency and output voltage can be adjusted. The VGST can be used as a high-fidelity platform to effectively recover recorded music and can also be combined with machine learning algorithms to realize the function of speech recognition with a high accuracy rate of 97%. It also has good antinoise performance to recognize speech correctly even in noisy environments. Meanwhile, in gesture recognition, the triboelectric translator is able to recognize simple hand gestures and to judge the distance between hand and the VGST based on the principle of electrostatic induction. This work demonstrates that triboelectric nanogenerator (TENG) technology can have great application prospects and significant advantages in human-machine interaction and high-fidelity platforms.

Evaluating the usability of a prototype gesture-controlled illuminative textile

In the field of human-computer interaction (HCI), recent years have witnessed an increasing interest in smart textiles with gesture recognition functions. This paper reports usability evaluations of a prototype gesture-controlled illuminative textile developed by the authors. This is an interactive woven POF textile system with computer vision-enabled mid-air gesture recognition. For the usability test, 25 participants (11 males and 14 females) aged between 19 and 56 (M = 30.85, SD = 10.8) were randomly recruited. The study was conducted by the means of the user experience questionnaire (UEQ) and the system usability scale (SUS). Results show that participants responded positively to our gesture-controlled illuminative textile in terms of its attractiveness, perspicuity and stimulation but were less positive about its efficiency. The results will be used to make targeted improvements to the existing product design.

Automated Guided Vehicle (AGV) Driving System Using Vision Sensor and Color Code

Recently, the use of Automated Guided Vehicles (AGVs) at production sites has been increasing due to industrial development, such as the introduction of smart factories. AGVs utilizing the wired induction method, which is cheaper and faster than the wireless induction method, are mainly used at production sites. However, the wired guidance AGV operation system has the disadvantage of being limited to small-batch or collaboration-based production sites, since it is difficult to change the driving route. In this paper, we propose an AGV line-scan algorithm that can perform route recognition, driving commands, and operation through color-code recognition using an Arduino controller and a low-cost vision sensor, instead of the optical sensor conventionally used for these functions. When the proposed algorithm is applied to the AGV car, the CMUcam 5 Pixy2 camera identifies the driving path to follow by tracking a black line using the Otsu method. In addition, it can be confirmed that the driving command is executed using the proposed color code by applying the color recognition function of the CMUcam 5 Pixy2.

A hybrid discriminant fuzzy DNN with enhanced modularity bat algorithm for speech recognition

In recent years, speech processing resides a major application in the domain of signal processing. Due to the audibility loss of some speech signals, people with hearing impairment have difficulty in understanding speech, which reintroduces a crucial role in speech recognition. Automatic Speech Recognition (ASR) development is a major challenge in research in the case of noise, domain, vocabulary size, and language and speaker variability. Speech recognition system design needs careful attention to challenges or issues like performance and database evaluation, feature extraction methods, speech representations and speech classes. In this paper, HDF-DNN model has been proposed with the hybridization of discriminant fuzzy function and deep neural network for speech recognition. Initially, the speech signals are pre-processed to eliminate the unwanted noise and the features are extracted using Mel Frequency Cepstral Coefficient (MFCC). A hybrid Deep Neural Network and Discriminant Fuzzy Logic is used for assisting hearing-impaired listeners with enhanced speech intelligibility. Both DNN and DF have some problems with parameters to address this problem, Enhanced Modularity function-based Bat Algorithm (EMBA) is used as a powerful optimization tool. The experimental results show that the proposed automatic speech recognition-based hybrid deep learning model is effectively-identifies speech recognition more than the MFCC-CNN, CSVM and Deep auto encoder techniques. The proposed method improves the overall accuracy of 8.31%, 9.71% and 10.25% better than, MFCC-CNN, CSVM and Deep auto encoder respectively.

Selective fluorescent probe for sensitive determination of bisphenol A based on molecularly imprinted polymers decorated carbon dots derived from citric acid and ethylenediamine

Bisphenol A (BPA) is an endocrine disrupting chemical and poses a grave threat to the human health. Herein, a fluorescent probe constructed with molecularly imprinted polymers decorated carbon dots (CDs@MIPs) was proposed for determination of BPA with high selectivity. The CDs@MIPs were constructed using BPA, 4-vinylpyridine and ethylene glycol dimethacrylate as template, functional monomer and cross linker, respectively. The obtained fluorescent probe not only owned a highly selective recognition function derived from MIPs but also displayed an excellent sensitivity for sensing BPA stemmed from CDs. The fluorescence intensity of CDs@MIPs was varied before and after the removal of BPA templates. The fluorescent decrease fraction of the fluorescent probe demonstrates a nice linearity in BPA concentration range of 10–2000 nM (r2 = 0.9998) and the detection limit is as low as 1.5 nM. The fluorescent probe was triumphantly utilized to sense the level of BPA in real aqueous and plastic samples with good results. Moreover, the fluorescent probe offered a wonderful means for fast identification and sensitive detection of BPA from environmental aqueous samples.

Development of a molecularly imprinted electrochemiluminescence sensor based on bifunctional bilayer structured ZIF-8-based magnetic particles for dopamine sensing

A bilayer-structured ZIF-8 composite with dual functions of sensing and recognition was synthesized, with ZIF-8 serving as an electrochemiluminescence (ECL) probe carrier and molecularly imprinted membrane to construct a molecularly imprinted electrochemiluminescence sensor. The inner layer was a ZIF-8 layer loaded with a luminescent probe, which was obtained by the reaction of zinc ions with 2-methylimidazole on the magnetic [email protected]2O4 surface in the presence of Ru(bpy)32+, the composite magnetic particle is marked as ZIF(Ru)/[email protected]2O4. The outer layer was a layer with recognition function using ZIF-8 as an imprinted membrane, which was obtained by a layer-by-layer self-assembly method on the surface of ZIF(Ru)/[email protected]2O4 with dopamine (DA) as a template molecule, which was marked as ZIF(MIP)/ZIF(Ru)/[email protected]2O4. After eluting the template molecules, the composite particle was immobilized on the surface of a magnetically controlled glassy carbon electrode (MGCE) to obtain a molecular imprinting (MIP) modified electrode. When dopamine molecules were re-adsorbed by the MIP, a charge/energy transfer between dopamine and Ru(bpy)32+ occurred. It subsequently led to the quenching of electrochemiluminescence, which was used as the basis for the detection of dopamine by a molecularly imprinted electrochemiluminescence sensor. When the dopamine concentration was in the range of 1.0 × 10−14 ∼ 5.0 × 10−10 mol/L, the ECL intensity change of the sensor and the dopamine concentration had a good linear relationship, and the detection limit was 4.8 × 10−15 mol/L. The molecularly imprinted electrochemiluminescence sensor was successfully applied to the detection of dopamine in human serum samples.

Incorporating Driving Style Recognition Into MPC for Energy Management of Plug-In Hybrid Electric Buses

Vehicle fuel economy is greatly influenced by the driver’s driving style. To achieve remarkable promotion in the fuel economy, a novel predictive energy management strategy (EMS) with strong adaptability to driving styles is presented for plug-in hybrid electric buses (PHEBs) in this article. First, a combined unsupervised and supervised algorithm for the driving style identification is devised based on instant driving conditions. In the algorithm, a multidimensional Gaussian distribution (MGD)-based analysis on factors influencing driver’s driving style provides valuable inputs for local mean <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> nearest neighbor (LMKNN) algorithm, and outstanding regression ability of the LMKNN returns exact recognition result and then incorporating the driving style recognition function into the model predictive control (MPC) to formulate a driver-oriented predictive EMS, where estimate distribution and particle swarm optimization (ED-PSO) algorithm is introduced to obtain optimal control sequence over a receding horizon. Finally, simulation validations in the MATLAB/Simulink environment show that the total cost of the proposed strategy is decreased by 12.53% compared to the charge-depleting and charge-sustaining (CD-CS) method, without sacrificing the real-time applicability.

Solid‐phase microextraction and cuticular hydrocarbon differences related to reproductive activity in juniper bark borer Semanotus bifasciatus Motschulsky

AbstractCuticular hydrocarbons of Cerambycidae species can function as signals for sex recognition. Little is known about the copulatory signals of the juniper bark borer Semanotus bifasciatus, a major economic threat to Platycladus orientalis Franco in China. Here, we investigated the cuticular hydrocarbons of both sexes of S. bifasciatus to determine the chemically mediated mating signals using the solid‐phase microextraction (SPME) technique with carbowax/divinylbenzene fibers (CAR/DVB) and then analyzed by coupled gas chromatography‐mass spectrometry (GC‐MS). A series of aliphatic saturated straight‐chain n‐alkanes (n‐C23 to n‐C28), internally branched monomethylalkanes at carbons 3, 11, or 13, and dimethylalkanes were identified, which showed no qualitative differences in either sex and were similar in the samples with SPME fiber extraction and those with hexane extraction. The bioassay showed that 11‐methylpentacosane (11‐MeC25), 11‐methylhexacosane (11‐MeC26), and 11‐methylheptacosane (11‐MeC27) have sex‐specific recognition functions that triggered more mating attempts at a female‐specific ratio of 100:4:60 than at a male‐specific ratio of 100:85:50. In addition, the female‐specific ratio of 11‐methylalkanes can elicit about 70% of male mating attempts within about 60 s, whereas live females elicit about 98% of male mating attempts within 25 s. The discrepancy in the initiation of mating attempts by synthetic mixtures and live females suggests that the methyl isomers 3‐MeC25, 3‐MeC27, and/or 11,15‐diMeC27 may also be involved in the mating behavior of S. bifasciatus. These results suggest that 11‐MeC25, 11‐MeC26, and 11‐MeC27 constitute the contact sex pheromone of S. bifasciatus, with the presence or absence of 11‐MeC26 in particular playing an important role in mate recognition by males.

Bimetallic MOF synergy molecularly imprinted ratiometric electrochemical sensor based on MXene decorated with polythionine for ultra-sensitive sensing of catechol

Dual-signal ratiometric molecularly imprinted polymer (MIP) electrochemical sensors with bimetallic active sites and high-efficiency catalytic activity were fabricated for the sensing of catechol (CC) with high selectivity and sensitivity. The amino-functionalization bimetallic organic framework materials (Fe@Ti-MOF-NH2), coupled with two-dimensional layered titanium carbide (MXene) co-modified glassy carbon electrode provides an expanded surface while amplifying the output signal through the electropolymerization immobilization of polythionine (pTHi) and MIP. The oxidation of CC and pTHi were presented as the response signal and the internal reference signal. The oxidation peak current at +0.42 V rose with increased concentration of CC, while the peak currents of pTHi at −0.20 V remained constant. Compared to the common single-signal sensing system, this one (MIP/pTHi/MXene/Fe@Ti-MOF-NH2/GCE), a novel ratiometric MIP electrochemical sensor exhibited two segments wide dynamic range of 1.0–300 μM (R2 = 0.9924) and 300–4000 μM (R2 = 0.9912), as well as an ultralow detection limit of 0.54 μM (S/N = 3). Due to the specific recognition function of MIPs and the advantages of built-in correction of pTHi, the prepared surface imprinting sensor presented an excellent performance in selectivity and reproducibility. Besides, this sensor possessed superior anti-interference ability with ions and biomolecules, excellent reproducibility, repeatability, and acceptable stability. Furthermore, the proposed sensing system exhibits high specific recognition in the determination of environmental matrices and biological fluids in real samples with satisfactory results. Therefore, this signal-enhanced ratiometric MIP electrochemical sensing strategy can accurately and selectively analyze and detect other substances.

A novel Aptamer-induced CHA amplification strategy for ultrasensitive detection of Staphylococcus aureus and NIR-triggered photothermal bactericidal Activity based on aptamer-modified magnetic Fe3O4@AuNRs

The development of multifunctional biosensors integrating recognition and therapeutic functions is critical for ensuring food safety and preventing foodborne diseases. Herein, an integrated design strategy was demonstrated to establish an innovative Fe3O4 @AuNRs-aptasensor for efficient detecting Staphylococcus aureus (S. aureus), which could enrich and photothermally eliminate bacteria under the radiation of near-infrared light irradiation (NIR). The detection assay relies on the binding of aptamer to Fe3O4 @AuNRs (Fe3O4 @ AuNRs-aptasensor) to induce the release of c-aptamer (c-Apt) in the presence of S. aureus, thereby triggering catalytic hairpin assembly (CHA) reaction and restoring the fluorescence of the reporter. The developed biosensor achieved direct, ultrasensitive, and specificity detection of S. aureus with a linear response ranging from 102 to 106 CFU/mL and a detection limit of 101 CFU/mL under optimal conditions. Furthermore, the aptasensor can be applied for the detection of S. aureus in milk with recoveries of 90.3–95.6% at the concentration between 1.0 × 102 and 1.0 × 104 CFU/mL. Additionally, Fe3O4 @AuNRs-aptasensor shows high photothermal sterilization performance under NIR irradiation. The study emphasizes the combination of high sensitivity base on molecular detection and photothermal antibacterial activity of novel nanomaterials activated by NIR light to design multifunctional probe, which show great potential for application in food analysis and early foodborne disease diagnosis.

An empirical study on analysis window functions for text-independent speaker recognition

An empirical study on analysis window functions for text-independent speaker recognition