An asynchronous response fluorescence sensor combines machine learning theory to qualitatively and quantitatively detect tetracyclines.

Excess use of tetracyclines poses significant health risks arising from animal-derived foods, meaning simple and sensitive methods to detect tetracyclines would be beneficial given current laboratory methods are complex and expensive. Herein, we describe an asynchronous response fluorescence sensor constructed based on Zn-based metal-organic framework and Ru(bpy)32+ (denoted as Ru@Zn-BTEC) for the qualitative and quantitative detection of tetracyclines in foods. Under excitation at 365 nm, the sensor emitted red fluorescence at 609 nm. When tetracyclines were present, these molecules aggregated in the Ru@Zn-BTEC framework, causing green fluorescence emission at 528 nm. The developed sensing system accurately distinguished the different categories of tetracyclines with a classifier accuracy of 94 %. The Ru@Zn-BTEC sensor demonstrated a detection limit of 0.012 µM and satisfactory recovery (87.81 %-113.84 %) for tetracyclines in food samples. This work provides a pathway for constructing asynchronous response fluorescence sensors for food analysis.

Constructing graphene oxide/Au nanoparticle cellulose membranes for SERS detection of mixed pesticide residues in edible chrysanthemum.

Edible chrysanthemum is widely cultivated and used as an important ingredient of medicine, tea and multifunctional food. During the planting of chrysanthemum, pesticides are extensively used for preventing plant diseases and insect pests. To ensure the food safety of edible chrysanthemum, rapid detection methods are urgently needed for on-site inspection. In this study, a graphene oxide/Au nanoparticle (GO/Au NP) cellulose substrate was prepared through layer-by-layer assembly of GO and Au NPs on a mixed cellulose ester membrane. Surface-enhanced Raman spectroscopy (SERS) detection of four types of organophosphorus and organosulfur pesticides was achieved by filtering the extracting solution through the substrate and analysing SERS spectra. Qualitative and semi-quantitative detection of fenthion, phoxim, isocarbophos and thiram was accomplished with the detection limits of 38.01, 8.13, 48.97 and 8.74 ng mL-1, respectively. A spiking experiment further demonstrated the feasibility of this method for rapid and on-site detection of mixed pesticides in chrysanthemum. This study provides a new approach for rapid detection of multiple hazardous substances in flowering and herbal plants.

Impaired influenza A virus replication by the host restriction factor SAMHD1 which inhibited by PA-mediated dephosphorylation of the host transcription factor IRF3.

BACKGROUND: Influenza A virus (IAV) can cause severe and life-threatening illness in humans and animals. Therefore, it is important to search for host antiviral proteins and elucidate their antiviral mechanisms for the development of potential treatments. As a part of human innate immunity, host restriction factors can inhibit the replication of viruses, among which SAM and HD domain containing deoxynucleoside triphosphate triphosphohydrolase 1 (SAMHD1) can restrict the replication of viruses, such as HIV and enterovirus EV71. Viruses also developed countermeasures in the arms race with their hosts. There are few reports about whether SAMHD1 has a restriction effect on IAV. METHODS: To investigate the impact of IAV infection on SAMHD1 expression in A549 cells, we infected A549 cells with a varying multiplicity of infection (MOI) of IAV and collected cell samples at different time points for WB and RT-qPCR analysis to detect viral protein and SAMHD1 levels. The virus replication level in the cell culture supernatant was determined using TCID50 assay. Luciferase assay was used to reveal that H5N1 virus polymerase acidic protein (PA) affected the activity of the SAMHD1 promoter. To assess the antiviral capacity of SAMHD1, we generated a knockdown and overexpressed cell line for detecting H5N1 replication. RESULTS: In this study, we observed that SAMHD1 can restrict the intracellular replication of H5N1 and that the H5N1 viral protein PA can downregulate the expression of SAMHD1 by affecting SAMHD1 transcriptional promoter activity. We also found that SAMHD1's ability to restrict H5N1 is related to phosphorylation at 592-tyrosine. CONCLUSIONS: In conclusion, we found that SAMHD1 may affect the replication of IAVs as a host restriction factor and be countered by PA. Furthermore, SAMHD1 may be a potential target for developing antiviral drugs.

Anterior forebrain pathway in parrots is necessary for producing learned vocalizations with individual signatures.

Parrots have enormous vocal imitation capacities and produce individually unique vocal signatures. Like songbirds, parrots have a nucleated neural song system with distinct anterior (AFP) and posterior forebrain pathways (PFP). To test if song systems of parrots and songbirds, which diverged over 50 million years ago, have a similar functional organization, we first established a neuroscience-compatible call-and-response behavioral paradigm to elicit learned contact calls in budgerigars (Melopsittacus undulatus). Using variational autoencoder-based machine learning methods, we show that contact calls within affiliated groups converge but that individuals maintain unique acoustic features, or vocal signatures, even after call convergence. Next, we transiently inactivated the outputs of AFP to test if learned vocalizations can be produced by the PFP alone. As in songbirds, AFP inactivation had an immediate effect on vocalizations, consistent with a premotor role. But in contrast to songbirds, where the isolated PFP is sufficient to produce stereotyped and acoustically normal vocalizations, isolation of the budgerigar PFP caused a degradation of call acoustic structure, stereotypy, and individual uniqueness. Thus, the contribution of AFP and the capacity of isolated PFP to produce learned vocalizations have diverged substantially between songbirds and parrots, likely driven by their distinct behavioral ecology and neural connectivity.

Autonomous detection of myocarditis based on the fusion of improved quantum genetic algorithm and adaptive differential evolution optimization back propagation neural network.

Myocarditis is cardiac damage caused by a viral infection. Its result often leads to a variety of arrhythmias. However, rapid and reliable identification of myocarditis has a great impact on early diagnosis, expedited treatment, and improved patient survival rates. Therefore, a novel strategy for the autonomous detection of myocarditis is suggested in this work. First, the improved quantum genetic algorithm (IQGA) is proposed to extract the optimal features of ECG beat and heart rate variability (HRV) from raw ECG signals. Second, the backpropagation neural network (BPNN) is optimized using the adaptive differential evolution (ADE) algorithm to classify various ECG signal types with high accuracy. This study examines analogies among five different ECG signal types: normal, abnormal, myocarditis, myocardial infarction (MI), and prior myocardial infarction (PMI). Additionally, the study uses binary and multiclass classification to group myocarditis with other cardiovascular disorders in order to assess how well the algorithm performs in categorization. The experimental results demonstrate that the combination of IQGA and ADE-BPNN can effectively increase the precision and accuracy of myocarditis autonomous diagnosis. In addition, HRV assesses the method's robustness, and the classification tool can detect viruses in myocarditis patients one week before symptoms worsen. The model can be utilized in intensive care units or wearable monitoring devices and has strong performance in the detection of myocarditis.

Amino-functionalized Al-MOF modulated TpTt-COF with dual-emission for fluorescent and optosmart detecting tetracycline in food samples.

Tetracycline residues in animal-derived food pose serious harm to human health, making it demanded to develop simple and sensitive method for detecting tetracycline. Herein, a dual-emission synchronous response fluorescence probe is reported based on amino-functionalized Al-MOF modulated TpTt-COF (donate as NMT). NMT exhibits excellent dual-emission at 455 and 575 nm under single excitation. Tetracycline is sensitively detected through quenching the dual-emission of NMT. NMT specifically recognizes tetracycline through intermolecular hydrogen bonding between -OH/-NH2 of tetracycline and deprotonated O-/-NH-/CN of NMT. A calibration curve is built between the fluorescence ratio and the tetracycline concentration with a detection limit of 0.014 µmol/L. NMT is employed to detect tetracycline in milk, pork and chicken, and displays satisfactory recoveries of 94.39-105.67%, respectively. The optosmart sensor based on NMT and smartphone has been constructed for visually detecting tetracycline. This method provides routes to construct MOF-COF fluorescence probes and has good prospects in food analysis.

PsERF1B-PsMYB10.1-PsbHLH3 module enhances anthocyanin biosynthesis in the flesh-reddening of amber-fleshed plum (cv. Friar) fruit in response to cold storage.

Flesh-reddening usually occurs in the amber-fleshed plum (Prunus salicina Lindl.) fruit during cold storage but not during ambient storage direct after harvest. It is not clear how postharvest cold signal is mediated to regulate the anthocyanin biosynthesis in the forming of flesh-reddening yet. In this study, anthocyanins dramatically accumulated and ethylene produced in the 'Friar' plums during cold storage, in comparison with plums directly stored at ambient temperature. Expression of genes associated with anthocyanin biosynthesis, as well as transcription factors of PsMYB10.1, PsbHLH3, and PsERF1B were strongly stimulated to upregulated in the plums in the period of cold storage. Suppression of ethylene act with 1-methylcyclopropene greatly suppressed flesh-reddening and downregulated the expression of these genes. Transient overexpression and virus-induced gene silencing assays in plum flesh indicated that PsMYB10.1 encodes a positive regulator of anthocyanin accumulation. The transient overexpression of PsERF1B, coupled with PsMYB10.1 and PsbHLH3, could further prompt the anthocyanin biosynthesis in a tobacco leaf system. Results from yeast two-hybrid and luciferase complementation assays verified that PsERF1B directly interacted with PsMYB10.1. PsERF1B and PsMYB10.1 enhanced the activity of the promoter of PsUFGT individually, and the enhancement was prompted by the co-action of PsERF1B and PsMYB10.1. Overall, the stimulation of the PsERF1B-PsMYB10.1-PsbHLH3 module mediated cold signal in the transcriptomic supervision of the anthocyanin biosynthesis in the 'Friar' plums. The results thereby revealed the underlying mechanism of the postharvest alteration of the flesh phenotype of 'Friar' plums subjected to low temperature.

Dopaminergic signals for improved parental behavior.

In this issue of Neuron, Xie et al.1 record and manipulate dopaminergic activity as mice engage in parental care. Dopaminergic prediction error signals previously implicated in food rewards were associated with retrieving isolated pups to the nest, showing that neural mechanisms long associated with reinforcement learning can be repurposed for aspects of parenting.

The E3 ligase RNF5 restricts SARS-CoV-2 replication by targeting its envelope protein for degradation.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a severe global health crisis; its structural protein envelope (E) is critical for viral entry, budding, production, and induction of pathology which makes it a potential target for therapeutics against COVID-19. Here, we find that the E3 ligase RNF5 interacts with and catalyzes ubiquitination of E on the 63rd lysine, leading to its degradation by the ubiquitin-proteasome system (UPS). Importantly, RNF5-induced degradation of E inhibits SARS-CoV-2 replication and the RNF5 pharmacological activator Analog-1 alleviates disease development in a mouse infection model. We also found that RNF5 is distinctively expressed in different age groups and in patients displaying different disease severity, which may be exploited as a prognostic marker for COVID-19. Furthermore, RNF5 recognized the E protein from various SARS-CoV-2 strains and SARS-CoV, suggesting that targeting RNF5 is a broad-spectrum antiviral strategy. Our findings provide novel insights into the role of UPS in antagonizing SARS-CoV-2 replication, which opens new avenues for therapeutic intervention to combat the COVID-19 pandemic.

Genetic Characterization and Pathogenesis of Avian Influenza Virus H3N8 Isolated from Chinese pond heron in China in 2021.

In October 2021, a wild bird-origin H3N8 influenza virus-A/Chinese pond heron/Jiangxi 5-1/2021 (H3N8)-was isolated from Chinese pond heron in China. Phylogenetic and molecular analyses were performed to characterize the genetic origin of the H3N8 strain. Phylogenetic analysis revealed that eight gene segments of this avian influenza virus H3N8 belong to Eurasian lineages. HA gene clustered with avian influenza viruses is circulating in poultry in southern China. The NA gene possibly originated from wild ducks in South Korea and has the highest homology (99.3%) with A/Wild duck/South Korea/KNU2020-104/2020 (H3N8), while other internal genes have a complex and wide range of origins. The HA cleavage site is PEKQTR↓GLF with one basic amino acid, Q226 and T228 at HA preferentially bind to the alpha-2,3-linked sialic acid receptor, non-deletion of the stalk region in the NA gene and no mutations at E627K and D701N of the PB2 protein, indicating that isolate A/Chinese pond heron/Jiangxi 5-1/2021 (H3N8) was a typical avian influenza with low pathogenicity. However, there are some mutations that may increase pathogenicity and transmission in mammals, such as N30D, T215A of M1 protein, and P42S of NS1 protein. In animal studies, A/Chinese pond heron/Jiangxi 5-1/2021 (H3N8) replicates inefficiently in the mouse lung and does not adapt well to the mammalian host. Overall, A/Chinese pond heron/Jiangxi 5-1/2021 (H3N8) is a novel wild bird-origin H3N8 influenza virus reassortant from influenza viruses of poultry and wild birds. This wild bird-origin avian influenza virus is associated with wild birds along the East Asian-Australasian flyway. Therefore, surveillance of avian influenza viruses in wild birds should be strengthened to assess their mutation and pandemic risk in advance.

COVID-19 ground-glass opacity segmentation based on fuzzy c-means clustering and improved random walk algorithm.

Accurate segmentation of ground-glass opacity (GGO) is an important premise for doctors to judge COVID-19. Aiming at the problem of mis-segmentation for GGO segmentation methods, especially the problem of adhesive GGO connected with chest wall or blood vessel, this paper proposes an accurate segmentation of GGO based on fuzzy c-means (FCM) clustering and improved random walk algorithm. The innovation of this paper is to construct a Markov random field (MRF) with adaptive spatial information by using the spatial gravity Model and the spatial structural characteristics, which is introduced into the FCM model to automatically balance the insensitivity to noise and preserve the effectiveness of image edge details to improve the clustering accuracy of image. Then, the coordinate values of nodes and seed points in the image are combined with the spatial distance, and the geodesic distance is added to redefine the weight. According to the edge density of the image, the weight of the grayscale and the spatial feature in the weight function is adaptively calculated. In order to reduce the influence of edge noise on GGO segmentation, an adaptive snowfall model is proposed to preprocess the image, which can suppress the noise without losing the edge information. In this paper, CT images of different types of COVID-19 are selected for segmentation experiments, and the experimental results are compared with the traditional segmentation methods and several SOTA methods. The results suggest that the paper method can be used for the auxiliary diagnosis of COVID-19, so as to improve the work efficiency of doctors.

Two-Photon Calcium Imaging in the Brain of Aedes aegypti Mosquitoes.

Understanding the neural basis of mosquito behavior is critical for designing effective vector control strategies and can potentially shed new light on basic nervous system function. Because mosquitoes are a non-model species, however, functional studies of mosquito nervous systems have long been restricted to electrophysiological recording from peripheral sensory organs such as the antenna. This is now changing with the advent of CRISPR-Cas9 gene editing and the development of other powerful new genetic tools. Transgenic mosquitoes that carry genetically encoded calcium sensors, for example, open the door to optical recording of neural activity with two-photon calcium imaging. Compared with electrophysiology, calcium imaging permits continuous monitoring of neural activity from large populations of neurons, even deep in the brain. When combined with selective neural drivers, it also allows targeted recording from specific neuronal types. Here, we describe a calcium imaging protocol we use in our laboratory to study neural activity in the brain of Aedes aegypti mosquitoes.

GCaMP Imaging in Mosquitoes: Central Nervous System.

Mosquitoes spread dengue, Zika, malaria, and other pathogens to hundreds of millions of people every year. A better understanding of mosquito behavior and its underlying neural mechanisms may lead to new control strategies, but such an understanding requires the development of tools and approaches for exploring the nervous system of key vector species. For example, we can now image neural activity in mosquito brains using genetically encoded calcium sensors like GCaMP. Compared with other types of neural recording, GCaMP imaging has the advantage of allowing one to record from many neurons simultaneously and/or to record from specific neuronal types. Successful implementation requires careful consideration of many factors, including the choice of microscope and how to make the brains of experimental animals visible and stable while minimizing damage. Here, we elaborate on these points and provide a concise introduction to GCaMP imaging in the mosquito central nervous system.

Recent advances in simultaneous detection strategies for multi-mycotoxins in foods.

Mycotoxin contamination has become a challenge in the field of food safety testing, given the increasing emphasis on food safety in recent years. Mycotoxins are widely distributed, in heavily polluted areas. Food contamination with these toxins is difficult to prevent and control. Mycotoxins, as are small-molecule toxic metabolites produced by several species belonging to the genera Aspergillus, Fusarium, and Penicillium growing in food. They are considered teratogenic, carcinogenic, and mutagenic to humans and animals. Food systems are often simultaneously contaminated with multiple mycotoxins. Due to the additive or synergistic toxicological effects caused by the co-existence of multiple mycotoxins, their individual detection requires reliable, accurate, and high-throughput techniques. Currently available, methods for the detection of multiple mycotoxins are mainly based on chromatography, spectroscopy (colorimetry, fluorescence, and surface-enhanced Raman scattering), and electrochemistry. This review provides a comprehensive overview of advances in the multiple detection methods of mycotoxins during the recent 5 years. The principles and features of these techniques are described. The practical applications and challenges associated with assays for multiple detection methods of mycotoxins are summarized. The potential for future development and application is discussed in an effort, to provide standards of references for further research.

Mosquito brains encode unique features of human odour to drive host seeking.

A globally invasive form of the mosquito Aedes aegypti specializes in biting humans, making it an efficient disease vector1. Host-seeking female mosquitoes strongly prefer human odour over the odour of animals2,3, but exactly how they distinguish between the two is not known. Vertebrate odours are complex blends of volatile chemicals with many shared components4-7, making discrimination an interesting sensory coding challenge. Here we show that human and animal odours evoke activity in distinct combinations of olfactory glomeruli within the Ae. aegypti antennal lobe. One glomerulus in particular is strongly activated by human odour but responds weakly, or not at all, to animal odour. This human-sensitive glomerulus is selectively tuned to the long-chain aldehydes decanal and undecanal, which we show are consistently enriched in human odour and which probably originate from unique human skin lipids. Using synthetic blends, we further demonstrate that signalling in the human-sensitive glomerulus significantly enhances long-range host-seeking behaviour in a wind tunnel, recapitulating preference for human over animal odours. Our research suggests that animal brains may distil complex odour stimuli of innate biological relevance into simple neural codes and reveals targets for the design of next-generation mosquito-control strategies.

Chemokine PF4 Inhibits EV71 and CA16 Infections at the Entry Stage.

Platelet factor 4 (PF4) or the CXC chemokine CXCL4 is the most abundant protein within the α-granules of platelets. Previous studies found that PF4 regulates infections of several viruses, including HIV-1, H1N1, hepatitis C virus (HCV), and dengue virus. Here, we show that PF4 is an inhibitor of enterovirus A71 (EV71) and coxsackievirus A16 (CA16) infections. The secreted form of PF4 from transfected cells or soluble purified PF4 from Escherichia coli, even lacking signal peptide affected secretion, obviously inhibited the propagation of EV71 and CA16. Mechanistically, we demonstrated that PF4 blocked the entry of the virus into the host cells by interactions with VP3 proteins of EV71/CA16 and the interaction with SCARB2 receptor-mediated EV71 and CA16 endocytosis. As expected, the incubation of anti-PF4 antibody with PF4 blocked PF4 inhibition on EV71 and CA16 infections further supported the above conclusion. Importantly, pretreatment of EV71 viruses with PF4 significantly protected the neonatal mice from EV71 lethal challenge and promoted the survival rate of infected mice. PF4 derived from natural platelets by EV71/CA16 activation also presented strong inhibition on EV71 and CA16. In summary, our study identified a new host factor against EV71 and CA16 infections, providing a novel strategy for EV71 and CA16 treatment. IMPORTANCE The virus's life cycle starts with binding to cell surface receptors, resulting in receptor-mediated endocytosis. Targeting the entry of the virus into target cells is an effective strategy to develop a novel drug. EV71 and CA16 are the major pathogens that cause hand, foot, and mouth disease (HFMD) outbreaks worldwide since 2008. However, the treatment of EV71 and CA16 infections is mainly symptomatic because there is no approved drug. Therefore, the underlying pathogenesis of EV71/CA16 and the interaction between host-EV71/CA16 need to be further investigated to develop an inhibitor. Here, we identified PF4 as a potent entry inhibitor of EV71 and CA16 via binding to VP3 proteins of EV71 and CA16 or binding to receptor SCARB2. In the EV71 infection model, PF4 protected mice from EV71 lethal challenge and promoted the survival rate of EV71-infected mice. Our study suggests that PF4 represents a potential candidate host factor for anti-EV71 and CA16 infections.

Asymptomatic COVID-19 CT image denoising method based on wavelet transform combined with improved PSO.

The quality of asymptomatic corona virus disease 2019 (COVID-19) computed tomography (CT) image is reduced due to interference from Gaussian noise, which affects the subsequent image processing. Aiming at the problem that asymptomatic COVID-19 CT image often have small flake ground-glass shadow in the early lesions, and the density is low, which is easily confused with noise. A denoising method of wavelet transform with shrinkage factor is proposed. The threshold decreases with the increase of decomposition scale, and it reduces the misjudgment of signal points. In the advanced stage, the range of lesions increases, with consolidation and fibrosis in different sizes, which have similar gray value to the CT images of suspected cases. Aiming at the problems of low contrast and fuzzy boundary in the traditional wavelet transform, the threshold function based on the optimization of parameters combined with the improved particle swam optimization (PSO) is proposed, so that the parameters of wavelet threshold function can change adaptively according to the lung lobe and ground-glass lesions with fewer iterations. The simulation results show that the paper method is significantly better than other algorithms in peak signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR) and mean absolute error (MSE). For example, aiming at the early asymptomatic COVID-19, compared with the comparison methods, the PSNR under the proposed method has increased by about 5 dB, the MSE has been greatly reduced, and the SNR has increased by about 6.1 dB. It can be seen that the denoising effect under the proposed method is the best.

Quantitative analysis of blended corn-olive oil based on Raman spectroscopy and one-dimensional convolutional neural network.

Blended vegetable oil is a vital product in the vegetable oil market, and quantifying high-value vegetable oil is of great significance to protect the rights and interests of consumers. In this study, we established a one-dimensional convolutional neural network (1D CNN) quantitative identification model based on Raman spectra to identify the amount of olive oil in a corn-olive oil blend. The results show that the 1D CNN model based on 315 extended average Raman spectra can quantitatively identify the content of olive oil, with R2p and RMSEP values of 0.9908 and 0.7183 respectively. Compared with partial least squares regression (PLSR) and support vector regression (SVR), although the index is not optimal, it provides a new analytical method for the quantitative identification of vegetable oil.