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Cancer is one of the highest causes of death globally, which is believed to be mainly contributed by unhealthy diet. This review illustrated the formation mechanisms, detection methods and mitigation strategies of three well-known carcinogens, acrylamide, polycyclic aromatic hydrocarbons (PAHs) and heterocyclic amines (HCAs). Acrylamide, which is primarily formed through the Maillard reaction, is a Group 2A carcinogen mostly found in carbohydrate-rich food. PAHs (Group 1, 2A, 2B) and HCAs (Group 2A, 2B) are mainly found in meat and meat products. PAHs are formed from the incomplete combustion of carbonaceous materials through pyrosynthesis and pyrolysis processes. The basic pathway of PAH formation is a primary aromatic ring that undergoes numerous molecular growth reactions such as hydrogen abstraction and acetylene addition (HACA). HCAs are characterized as 'thermic' if formed below 300 °C and 'pyrolytic' if formed above 300 °C. These two categories of HCAs have different formation mechanisms. The most common detection method for these compounds is GC-MS, LC-MS and HPLC-MS/MS, although HPLC with fluorescence detection has the best performance. The generation of all the three carcinogens is promoted at high temperatures but reduced by cooking at lower temperatures, using different cooking methods such as boiling, or incorporating antioxidants in foods during cooking. [ABSTRACT FROM AUTHOR]

Leuconostoc citreum is widely utilized across numerous industries due to its beneficial properties. Thus, a detection method for this target species is essential to track the presence of L. citreum in commercial products. We developed a rapid, on-site L. citreum detection method using the loop-mediated isothermal amplification (LAMP) technique in this study. The designed LAMP primer set exhibited high specificity, only targeting the intended species among the 76 tested. Moreover, this assay demonstrated a sensitivity of 2 pg of target DNA. To evaluate the LAMP assay's applicability, we selected 20 varied types of processed products. The results confirmed these products' successful and precise detection of L. citreum within 35 min. Additionally, we used samples spiked with L. citreum to determine the detection limit, revealing L. citreum detection up to 102 or 103 CFU/mL. Thus, the LAMP assay developed herein is a specific, sensitive, precise, and rapid on-site detection method for L. citreum in various processed products. • We developed a rapid on-site detection method for Leuconostoc citreum. • Our novel assay exhibits high sensitivity, detecting as little as 2 pg of target DNA. • We detected L. citreum (up to 102 or 103 CFU/mL) in 20 products within 35 min. [ABSTRACT FROM AUTHOR]

Glutathione (GSH) is a strong antioxidant. However, there was no method to determine the GSH in ready-to-eat edible bird's nest (EBN). A liquid chromatography-mass spectrometry (LC-MS) method was developed for the determination of GSH in ready-to-eat EBN in this study. The method involves extraction by formic acid and methanol, vortex, ultra sonication and analysis using HPLC-MS/MS. The results showed that the linearity was good in the concentration range of 0.05–200 μg/L. The limit of detection and the limit of quantification of the method were 0.1 μg/kg and 1.0 μg/kg. In addition, the recovery was 90.6∼100.4% and the relative standard deviation was 1.2∼2.5%. Moreover, the content of GSH in ready-to-eat EBN produced by different stewing treatment was investigated. It was found that the content of GSH in ready-to-eat EBN increased with the increasing stewing time and temperature. When the stewing temperature was above 110 °C and the stewing time was above 15 min, it was more conducive to the formation of GSH in ready-to-eat EBN. In conclusion, this study provided a new method for the determination of GSH in ready-to-eat EBN, and also opened up a new direction for exploring the nutritional value of ready-to-eat EBN. • A LC–MS method for glutathione quantification in ready-to-eat EBN was developed. • The method showed satisfactory analytical performance for ready-to-eat EBN. • High intensity stewing promoted the conversion and formation of glutathione. • The glutathione was conversed and formed better in commercial ready-to-eat EBN. [ABSTRACT FROM AUTHOR]

[Display omitted] • The process and influencing factors of Listeria monocytogenes biofilm formation have been described. • Qualitative and quantitative techniques to detect L. monocytogenes biofilm have been presented. • This study elaborates the possible mechanisms of biofilm resistance: extracellular polymers, specific physiological adaptations, high genetic variability, and regulation of signaling molecules. • Various strategies and associated challenges in managing L. monocytogenes biofilm along with future prospects for controlling L. monocytogenes biofilm using hurdle techniques have been discussed. Listeria monocytogenes is an important foodborne pathogen that causes listeriosis, a severe and fatal condition. Biofilms are communities of microorganisms nested within a self-secreted extracellular polymeric substance, and they protect L. monocytogenes from environmental stresses. Biofilms, once formed, can lead to the persistence of L. monocytogenes in processing equipment and are therefore considered to be a major concern for the food industry. This paper briefly introduces the recent advancements on biofilm formation characteristics and detection methods, and focuses on analysis of the mechanism of L. monocytogenes biofilm resistance; Moreover, this paper also summarizes and discusses the existing different techniques of L. monocytogenes biofilm control according to the physical, chemical, biological, and combined strategies, to provide a theoretical reference to aid the choice of effective control technology in the food industry. [ABSTRACT FROM AUTHOR]

The self-resonating waterjet has the characteristics of high-frequency pressure oscillation and strong cavitation. Accurately grasping the jet characteristics is a prerequisite for the application research of self-resonating waterjets. The characteristics of the self-resonating waterjet are typically acquired through a test. Traditional test methods primarily include the striking test and signal detection in the nozzle chamber. However, these methods both have the disadvantage of low detection accuracy and the inability to overcome the impact of high ambient pressure. In this article, a detection method for self-resonating waterjet characteristics based on the flow signal in a pipeline was proposed. The pressure sensors were transferred from within the high pressure tank to the outside of the tank and were arranged in the front pipeline outside the tank to avoid the influence of high ambient pressure. Dual-pressure sensors were used to acquire the flow pressure pulse signal, and signal-processing technology was used to effectively suppress noise interference for enhancing the intensity of useful signals and accurately obtaining the pressure fluctuation information of the self-resonating waterjet.The test results show that the spectral characteristics acquired from the flow pressure signal in the pipeline agree with the results obtained from the signal in the chamber and are also consistent with the theoretical calculations. Thus, the pressure oscillation characteristics of the waterjet are fully characterized. Moreover, the acoustic power spectrum obtained from the flow pressure signal in the pipeline is in accordance with the result obtained from the hydrophone in the high pressure tank. Consequently, the cavitation characteristic of the waterjet is well characterized. Therefore, the detection method based on the flow signal in the pipeline is entirely feasible and advanced and provides a new means for the study of the self-resonating waterjet under high ambient pressure.

Abstract Background Purulent meningitis (PM) is a serious life-threatening infection of the central nervous system (CNS) by bacteria or fungi and associated with high mortality and high incidence of CNS sequelae in children. However, the conventional cerebrospinal fluid (CSF) culture method is time-consuming and has a low sensitivity. Methods Our study developed a real-time PCR-based purulent meningitis-TaqMan array card (PM-TAC) that targeted 21 PM-related pathogens and could produce results within 3 h. Primers and probes were adapted from published sources possibly. The performance of them were evaluated and optimized and then they were spotted on TAC. Results The PM-TAC showed a sensitivity and specificity of 95 and 96%, respectively. For all of the 21 targeted pathogens, the PM-TAC assay had a LOD ranging from 5 copies/reaction to 100 copies/reaction, an intra-assay variation of 0.07–4.45%, and an inter-assay variation of 0.11–6.81%. Of the 15 CSF samples collected from patients with PM after empiric antibiotic therapies, the positive rate was 53.3% (8/15) for our PM-TAC assay but was only 13.3% (2/15) for the CSF culture method. Of the 17 CSF samples showing negative CSF culture, the PM-TAC assay identified a case of Neisseria meningitidis infection. Furthermore, all of the 10 CSF samples from patients without CNS infection showed negative for the PM-TAC assay. Conclusions Our PM-TAC assay also demonstrated that the pathogen loads in the CSF samples correlated with the severity of PM. Thus, the PM-TAC may be helpful to improve the prognosis of PM and clinical outcomes from antibiotic therapies.

Inspection of the integrality of components and connecting parts is an important task to maintain safe and stable operation of transmission lines. In view of the fact that the scale difference of the auxiliary component in a connecting part is large and the background environment of the object is complex, a one-stage object detection method based on the enhanced real feature information and the label adaptive allocation is proposed in this study. Based on the anchor-free detection algorithm FCOS, this method is optimized by expanding the real feature information of the adjacent feature layer fusion and the semantic information of the deep feature layer, as well as adaptively assigning the label through the idea of pixel-by-pixel detection. In addition, the grading ring image is sliced in original data to improve the proportion of bolts in the dataset, which can clear the appearance features of small objects and reduce the difficulty of detection. Experimental results show that this method can eliminate the background interference in the GT (ground truth) as much as possible in object detection process, and improve the detection accuracy for objects with a narrow shape and small size. The evaluation index AP (average precision) increased by 4.1%. Further improvement of detection accuracy lays a foundation for the realization of efficient real-time patrol inspection.

Biosensors for mercury (II) (Hg2+) with high sensitivity are urgently required for food safety, ecosystem protection and disease prevention. In this study, a simple and fast detection method of Hg2+ based on the molecular beacon aptamer was established, according to the principle that Hg2+ could change the structure of the molecular beacon aptamer, resulting in the changed fluorescence intensity. All of the detection conditions were optimized. It was found that an optimal molecular beacon aptamer MB3 showed the optimal response signal in the optimized reaction environment, which was 0.08 μmol/L MB3, 50 mmol/L tris buffer (40 mmol/L NaCl, 10 mmol/L MgCl2, pH 8.1), and a 10 min reaction. Under the optimal detection conditions, the molecular beacon aptamer sensor showed a linear response to Hg2+ concentration within a range from 0.4 to 10 μmol/L and with a detection limit of 0.2254 μmol/L and a precision of 4.9%. The recovery rates of Hg2+ in water samples ranged from 95.00% to 99.25%. The method was convenient and rapid, which could realize the rapid detection of mercury ions in water samples.

With the advancement of image acquisition devices and social networking services, a huge volume of image data is generated. Using different image and video processing applications, these image data are manipulated, and thus, original images get tampered. These tampered images are the prime source of spreading fake news, defaming the personalities and in some cases (when used as evidence) misleading the law bodies. Hence before relying totally on the image data, the authenticity of the image must be verified. Works of the literature are reported for the verification of the authenticity of an image based on noise inconsistency. However, these works suffer from limitations of confusion between edges and noise, post-processing operation for localization and need of prior knowledge about an image. To handle these limitations, a noise inconsistency-based technique has been presented here to detect and localize a false region in an image. This work consists of three major steps of pre-processing, noise estimation and post-processing. For the experimental purpose two, publicly available datasets are used. The result is discussed in terms of precision, recall, accuracy and f1-score on the pixel level. The result of the presented work is also compared with the recent state-of-the-art techniques. The average accuracy of the proposed work on datasets is 91.70%, which is highest among state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

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Piroctone olamine (OCT), as a mild anti-dandruff agent, has been widely used in personal care products. Its anti-dandruff mechanism, including antibacterial action, antioxidant action and percutaneous absorption, was reviewed. The evaluation of the antidandruff effects of OCT by clinical trials and inhibition zone method was summarized. Its safety and mildness were also summarized, including acute toxicity, chronic toxicity, gene mutagenicity, etc. Moreover, the detection methods and application of OCT were described [ABSTRACT FROM AUTHOR]

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Deep neural networks (DNNs) provide superior performance on machine learning tasks such as image recognition, speech recognition, pattern analysis, and intrusion detection. However, an adversarial example, created by adding a little noise to an original sample, can cause misclassification by a DNN. This is a serious threat to the DNN because the added noise is not detected by the human eye. For example, if an attacker modifies a right-turn sign so that it misleads to the left, autonomous vehicles with the DNN will incorrectly classify the modified sign as pointing to the left, but a person will correctly classify the modified sign as pointing to the right. Studies are under way to defend against such adversarial examples. The existing method of defense against adversarial examples requires an additional process such as changing the classifier or modifying input data. In this paper, we propose a new method for detecting adversarial examples that does not invoke any additional process. The proposed scheme can detect adversarial examples by using a pattern feature of the classification scores of adversarial examples. We used MNIST and CIFAR10 as experimental datasets and Tensorflow as a machine learning library. The experimental results show that the proposed method can detect adversarial examples with success rates: 99.05% and 99.9% for the untargeted and targeted cases in MNIST, respectively, and 94.7% and 95.8% for the untargeted and targeted cases in CIFAR10, respectively. [ABSTRACT FROM AUTHOR]

Myositis-specific autoantibodies (MSAs) are thought to be mutually exclusive in patients with idiopathic inflammatory myopathies (IIM) based on studies with immunoprecipitation-based (IP) detection methods. Recently, detection of multiple MSAs in unique patients is increasingly reported, but the extent of this phenomenon remains unclear. At our centre, we reviewed results from two line immunoassays and one dot immunoassay in 145 IIM patients and 240 controls for the presence of multiple MSAs. Pubmed and Embase were systematically searched for articles mentioning detection of multiple MSAs in IIM patients, published until February 2019. We assessed the frequency, detection method, the precise combinations and clinical phenotypes of participants with multiple MSAs. At our centre, detection of multiple MSAs occurred in 3.4-8.3% of patients with IIM, depending on the assay. However, no cases with full concordance across all three assays were identified. Forty-four articles reported detection of multiple MSAs, representing a total of 133 cases, including four patients with a connective tissue disease other than IIM and two healthy controls. In 101 cases all MSAs were detected using only one detection method: 40 cases with IP-based methods (most frequently used technique) and 61 cases with other assay types. In most cases the phenotype of patients with multiple MSAs matched the predicted presentation associated with one MSA and in few cases the phenotype matched with both MSAs. Detection of multiple MSAs in unique IIM patients is less rare than commonly accepted. Specificity issues of the commercially available multiplex immunoassays may, at least partly, explain the higher frequency compared to IP-based methods. 'True multiple MSA-positive' patients may exist, though they are most likely rare. [ABSTRACT FROM AUTHOR]

Mica is a harmful component in fine aggregate of concrete, and the content of mica is a required detection item of fine aggregate. The detection method of mica content in current national or industry codes is time-consuming, laborious, and artificially influential. Using digital photography and digital technology as tools, and using the physical property differences between mica and fine aggregate, this paper established the one-to-one correspondence between the content of mica in fine aggregate and the memory space value occupied by digital photos. With this one-to-one correspondence, the mica content in fine aggregate could be detected rapidly and effectively. The new method is suitable for the rapid detection of mica content in fine aggregate production or construction enterprises with stable material source. [ABSTRACT FROM AUTHOR]

Copyright of Guangdong Architecture Civil Engineering is the property of Guangdong Architecture Civil Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to monitor the dissolved oxygen saturation in the ecological water environment of coastal cities in real time, it provides a basis for the control of ecological water pollution in coastal cities. Therefore, the detection method of ecological water pollution saturation in coastal cities is studied. First, the process and principle of dissolved oxygen in the water body are solved, and the equilibrium equation of dissolved oxygen is obtained. The Mutual Information-Particle Swarm Optimization-Radial Basis Function (MI-PSO-RBF) saturation detection method is used to detect the dissolved oxygen saturation in the ecological water of coastal cities. This method preprocesses the sampling data of ecological water in coastal cities, uses mutual information theory and dissolved oxygen balance equation, and detects the saturation of ecological water pollution through particle swarm optimization RBF neural network. Experimental results show that this method can effectively detect the saturation of ecological water pollution in coastal cities. The detection accuracy of dissolved oxygen saturation in a research area in Shandong is as high as 99%, and the detection time is less than 40 ms. [ABSTRACT FROM AUTHOR]

For large section members such as cables, there are insufficient methods for circumferential scanning along the cable sections for the detection of corroded broken wires. In this study, a detection method for broken wire damage (BWD) along the circumferential direction of cable based on the principle of self-magnetic flux leakage (SMFL) was proposed. First, the theoretical calculation model and the finite element model of the circumferential magnetic field in the polar coordinate system were established. The analysis results showed that the position of the BWD on the section of cable could be effectively judged by the concave position of the curves of the SMFL in the polar coordinate system. Through the circumferential scanning at different positions, the length of the BWD could be judged by the coordinates of x when the value of index "C" (similarity to circle) approached 1 for the first time in the x − C curves. Finally, the detection experiment for the BWD of a parallel wire bundle was carried out. The experimental results were consistent with the analysis results for the theoretical model and the finite element, and the experimental results verified the correctness of the detection method. [ABSTRACT FROM AUTHOR]

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Copyright of Journal of Agricultural Science & Technology (1008-0864) is the property of Journal of Agricultural Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The JRC COVID-19 In Vitro Diagnostic Devices and Test Methods Database, aimed to collect in a single place all publicly available information on performance of CE-marked in vitro diagnostic medical devices (IVDs) as well as in house laboratory-developed devices and related test methods for COVID-19, is here presented. The database, manually curated and regularly updated, has been developed as a follow-up to the Communication from the European Commission “Guidelines on in vitro diagnostic tests and their performance” of 15 April 2020 and is freely accessible at https://covid-19-diagnostics.jrc.ec.europa.eu/.

The diagnosis of virus infection can facilitate the effective control of plant viral diseases. To date, serological and molecular methods for the detection of virus infection have been widely used, but these methods have disadvantages if applied for broad-range and large-scale detection. Here, we investigated the effect of infection of several different plant RNA and DNA viruses such as cucumber mosaic virus (CMV), tobacco mosaic virus (TMV), potato virus X (PVX), potato virus Y (PVY) and apple geminivirus on starch content in leaves of Nicotiana benthamiana. Analysis showed that virus infection at an early stage was generally associated with a reduction in starch accumulation. Notably, a reduction in starch accumulation was readily apparent even with a very low virus accumulation detected by RT-PCR. Furthermore, we also observed that the infection of three latent viruses in propagative apple materials was associated with a reduction in starch accumulation levels. Analysis of transcriptional expression showed that some genes encoding enzymes involved in starch biosynthesis were downregulated at the early stage of CMV, TMV, PVX and PVY infections, suggesting that virus infection interferes with starch biosynthesis in plants. Our findings suggest that assessing starch accumulation levels potentially serve as a broad-range indicator for the presence of virus infection.

This study presents a real-time monitoring technique for radioactive substances that meets safety management needs. We studied the accumulation characteristics of radiation response signals of monolithic active pixel sensors (MAPSs) based on their response and discrimination ability to gamma (γ) photon or neutron radiation. The radiation status of the radioactive substances was determined by monitoring the accumulation data of radiation responses. As per the results, Am-Be and 252Cf radiation response signals are primarily concentrated in the range of 0–70 pixels. Response signals of 60Co and 137Cs γ-ray were concentrated in two regions; there was a peak in the region with a pixel value of less than 50, and a plateau in the region with a pixel value of more than 75. Therefore, the results are able to discriminate between spectra. Furthermore, we designed a radioactivity monitoring system that is able to examine multiple radioactive materials. Its working principle is that a change in the accumulation of radioactivity monitoring data indicates a radiation change during the last accumulation cycle. This study provides vital technical support for the long-term supervision of radioactive substances.

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Fractional Fourier transform (FrFT) is a useful tool to detect linear frequency modulated (LFM) signal. However, the detection performance of the FrFT-based method will deteriorate drastically in underwater multi-path environment. This paper proposes a novel method based on time-reversal and fractional Fourier transform (TR-FrFT) to solve this problem. We make use of the focusing ability of time-reversal to mitigate the influence of multi-path, and then improve the detection performance of FrFT. Simulated results show that, compared to FrFT, the difference between peak value and maximum pseudo-peak value of the signal processed by TR-FrFT is improved by 8.75 dB. Lake experiments results indicate that, the difference between peak value and maximum pseudo-peak value of the signal processed by TR-FrFT is improved by 7.6 dB. The detection performance curves of FrFT and TR-FrFT detectors with simulated data and lake experiments data verify the effectiveness of proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cervical cancer is a cell disease in the cervix that develops out of control in the female body. The cervix links the vagina (birth canal) with the upper section of the uterus, which can only be found in the female body. This is the second leading cause of death among women around the world. However, cervical cancer is currently one of the most preventable cancers if early detection is identified. The effect of unidentified cancer may increase the risk of death when the cell disease spreads to other parts of the female anatomy (metastasize). The Papanicolaou test is a cervical cancer screening technique used to identify potentially precancerous and cancerous cells in women's cervix. In this paper, a few popular detection method was applying and experimented on pap smear images. A few image quality assessment (IQA) was obtained in order to determine the best of detection method. The nucleus detection will help pathologists to diagnosis in early stages of cancer. The early detection is very important stage in order to reduce the cancer incidence and mortality. The method that needs to be invented in this study is the detection method. Image detection is the process of partitioning the image into multiple regions. The detection method is object detection and recognition as well as the boundary in images. The segmented Pap Smear image is one of the detection tools with many different methods that generated different results from different issues. The solution was by analysing different existing detection methods in order to compare the dissimilar performance of existing processes. The precision of the system performance needs to be improved in order to invent a new method. As predicted from the result, the innovative construction method must be proposed and compared in order to find accurate, comprehensive measures and proper sampling procedures by the features of the selection method. [ABSTRACT FROM AUTHOR]

Copyright of Acta Edulis Fungi is the property of Acta Edulis Fungi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Tea Science is the property of Journal of Tea Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Modern Laboratory Medicine is the property of Journal of Modern Laboratory Medicine Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Preventive Veterinary Medicine / Zhongguo Yufang Shouyi Xuebao is the property of Chinese Journal of Preventive Veterinary Medicine Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Bladder cancer (BC) is the tenth most prevalent malignancy globally, presenting significant clinical and societal challenges because of its high incidence, rapid progression, and frequent recurrence. Presently, cystoscopy and urine cytology serve as the established diagnostic methods for BC. However, their efficacy is limited by their invasive nature and low sensitivity. Therefore, the development of highly specific biomarkers and effective non-invasive detection strategies is imperative for achieving a precise and timely diagnosis of BC, as well as for facilitating an optimal tumor treatment and an improved prognosis. microRNAs (miRNAs), short noncoding RNA molecules spanning around 20-25 nucleotides, are implicated in the regulation of diverse carcinogenic pathways. Substantially altered miRNAs form robust functional regulatory networks that exert a notable influence on the tumorigenesis and progression of BC. Investigations into aberrant miRNAs derived from blood, urine, or extracellular vesicles indicate their potential roles as diagnostic biomarkers and prognostic indicators in BC, enabling miRNAs to monitor the progression and predict the recurrence of the disease. Simultaneously, the investigation centered on miRNA as a potential therapeutic agent presents a novel approach for the treatment of BC. This review comprehensively analyzes biological roles of miRNAs in tumorigenesis and progression, and systematically summarizes their potential as diagnostic and prognostic biomarkers, as well as therapeutic targets for BC. Additionally, we evaluate the progress made in laboratory techniques within this field and discuss the prospects.

Levan, a β-(2,6)-linked fructose polymer, exhibits diverse properties that impart versatility, rendering it a highly sought-after biopolymer with various industrial applications. Levan can be produced by various microorganisms using sucrose, food industry byproducts and agricultural wastes. Microbial levan represents the most potent cost-effective process for commercial-scale levan production. This study reviews the optimization of levan production by understanding its biosynthesis, physicochemical properties and the fermentation process. In addition, genetic and protein engineering for its increased production and emerging methods for its detection are introduced and discussed. All of these comprehensive studies could serve as powerful tools to optimize levan production and broaden its applications across various industries., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Background and Aim: Feline coronavirus (FCoV), feline panleukopenia virus (FPV), and feline leukemia virus (FeLV) are prevalent throughout China and significantly threaten cat health. These viruses cause similar manifestations and pathological damage. Rapid and accurate diagnosis depends on detection in the laboratory. This study aimed to establish a reliable and rapid method for accurate detection of FCoV, FPV, and FeLV so that a definite diagnosis can be made and effective measures can be taken to prevent and control viral infection., Materials and Methods: We designed three pairs of specific primers and probes for the detection of FCoV 5' untranslated region, FPV viral protein 2, and FeLV pol genes. Recombinant plasmid constructs were generated for use as standard plasmid constructs. Optimal reaction conditions, including primer and probe concentrations, reaction cycles, and annealing temperatures, were obtained on the basis of optimization tests. One-step triplex real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was successfully established to simultaneously detect FCoV, FPV, and FeLV. The specificity, sensitivity, and repeatability of the assay were analyzed, and its applicability was validated by testing 1175 clinical samples., Results: One-step triplex RT-qPCR had a high degree of specificity only for the detection of FCoV, FPV, and FeLV; it had high sensitivity with limits of detection of 139.904, 143.099, and 152.079 copies/reaction for p-FCoV, p-FPV, and p-FeLV standard plasmid constructs, respectively, and it had reliable repeatability with 0.06%-0.87% intra-assay coefficients of variations. A total of 1175 clinical samples were examined for FCoV, FPV, and FeLV using triplex RT-qPCR, and the FCoV, FPV, and FeLV positivity rates were 18.47%, 19.91%, and 47.57%, respectively. The clinical sensitivity and specificity of one-step triplex RT-qPCR were 93.07% and 97.99%, respectively., Conclusion: We developed a rapid and reliable one-step triplex RT-qPCR method for the detection of FCoV, FPV, and FeLV, which could be used as a diagnostic tool for clinical monitoring and diagnosis., Competing Interests: The authors declare that they have no competing interests., (Copyright: © He, et al.)

Porcine respiratory coronavirus (PRCoV), porcine reproductive and respiratory syndrome virus (PRRSV), swine influenza virus (SIV), and pseudorabies virus (PRV) are significant viruses causing respiratory diseases in pigs. Sick pigs exhibit similar clinical symptoms such as fever, cough, runny nose, and dyspnea, making it very difficult to accurately differentially diagnose these diseases on site. In this study, a quadruplex one-step reverse-transcription real-time quantitative PCR (RT-qPCR) for the detection of PRCoV, PRRSV, SIV, and PRV was established. The assay showed strong specificity, high sensitivity, and good repeatability. It could detect only PRCoV, PRRSV, SIV, and PRV, without cross-reactions with TGEV, PEDV, PRoV, ASFV, FMDV, PCV2, PDCoV, and CSFV. The limits of detection (LODs) for PRCoV, PRRSV, SIV, and PRV were 129.594, 133.205, 139.791, and 136.600 copies/reaction, respectively. The intra-assay and inter-assay coefficients of variation (CVs) ranged from 0.29% to 1.89%. The established quadruplex RT-qPCR was used to test 4909 clinical specimens, which were collected in Guangxi Province, China, from July 2022 to September 2023. PRCoV, PRRSV, SIV, and PRV showed positivity rates of 1.36%, 10.17%, 4.87%, and 0.84%, respectively. In addition, the previously reported RT-qPCR was also used to test these specimens, and the agreement between these methods was higher than 99.43%. The established quadruplex RT-qPCR can accurately detect these four porcine respiratory viruses simultaneously, providing an accurate and reliable detection technique for clinical diagnosis.

Carbapenem-resistant Gram-negative bacterial infections are a major public health threat due to the limited therapeutic options available. The introduction of the new β-lactam/β-lactamase inhibitors (BL/BLIs) has, however, altered the treatment options for such pathogens. Thus, four new BL/BLI combinations-namely, ceftazidime/avibactam, meropenem/vaborbactam, imipenem/relebactam, and ceftolozane/tazobactam-have been approved for infections attributed to carbapenem-resistant Enterobacterales species and Pseudomonas aeruginosa . Nevertheless, although these antimicrobials are increasingly being used in place of other drugs such as polymyxins, their optimal clinical use is still challenging. Furthermore, there is evidence that resistance to these agents might be increasing, so urgent measures should be taken to ensure their continued effectiveness. Therefore, clinical laboratories play an important role in the judicious use of these new antimicrobial combinations by detecting and characterizing carbapenem resistance, resolving the presence and type of carbapenemase production, and accurately determining the minimum inhibitor concentrations (MICs) for BL/BLIs. These three targets must be met to ensure optimal BL/BLIs use and prevent unnecessary exposure that could lead to the development of resistance. At the same time, laboratories must ensure that results are interpreted in a timely manner to avoid delays in appropriate treatment that might be detrimental to patient safety. Thus, we herein present an overview of the indications and current applications of the new antimicrobial combinations and explore the diagnostic limitations regarding both carbapenem resistance detection and the interpretation of MIC results. Moreover, we suggest the use of alternative narrower-spectrum antibiotics based on susceptibility testing and present data regarding the effect of synergies between BL/BLIs and other antimicrobials. Finally, in order to address the absence of a standardized approach to using the novel BL/BLIs, we propose a diagnostic and therapeutic algorithm, which can be modified based on local epidemiological criteria. This framework could also be expanded to incorporate other new antimicrobials, such as cefiderocol, or currently unavailable BL/BLIs such as aztreonam/avibactam and cefepime/taniborbactam.

Power converter faults represent about 12% of electrical system faults. More than 31% of these converter faults are caused by the transistors in the converters. These transistor failures are classified into open‐gate and short‐gate faults. A fault diagnostic and tolerant control system is proposed in this study for an open‐gate fault of a three‐phase voltage‐source inverter (VSI). The system under study is an induction motor fed by a VSI. The diagnostic technique uses a detection method of positive and negative sequence components, which requires only the measurement of motor currents. The diagnostic signals are derived from the negative sequence components of the motor currents. These signals are then compared using logic functions to trigger the tolerant control. In the case of an open‐gate fault, the tolerant system converts the inverter topology from six switches to four switches where the faulty inverter leg is disconnected. The proposed control method was evaluated under steady‐state and transient conditions through simulation and experiments. The results confirm an effective and reliable performance of the motor under an open‐gate fault. [ABSTRACT FROM AUTHOR]

In order to accurately detect the false data injection attack for node voltage in the cyber-physical power system, an attack detection method based on recurrent neural network (RNN) is proposed in this paper. The features of voltage data of power topology nodes and the construction method of attack vector are studied. Based on the fast regression algorithm, the best strategy for the data integrity attack of the specific node voltage is solved. The RNN is used to reconstruct time series of the node voltage, and set the threshold of error between the input data and the output data. Then, by calculating whether the error between the reconstructed output data and the original input data exceeds the threshold, it is determined whether the system has suffered data integrity attack. Finally, the feasibility and effectiveness of the detection method proposed in this paper were verified by simulated attack experiments. [ABSTRACT FROM AUTHOR]

In order to realise the fast detection of ships in synthetic aperture radar (SAR) images, a detection method combining visual saliency and a cascade convolutional neural network (CNN) is proposed. First, based on visual saliency, a multiscale spectral residual model is designed for realising the fast detection of ship candidate regions. Then, a cascaded CNN is designed, which consists of two convolution networks, namely, the front‐end shallow CNN, which is used to quickly exclude obvious non‐ship candidates and classify the ship candidates according to the ship orientation, and the back‐end deep CNN, which is used to detect high‐probability candidate regions with rotatable boundary boxes. The whole structure can realise the fast detection and precise positioning of ships with an arbitrary orientation. Finally, the authors conduct detailed experiments on the SAR ship image dataset. The experimental results show that the proposed method can effectively improve the detection accuracy of ships, ensuring the detection efficiency in SAR images. [ABSTRACT FROM AUTHOR]

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With increasing complications of canine parvovirus infection cases, disease diagnosis and treatment have become more difficult. In this study, specificity primers for the conserved region of the VP2 gene of canine parvovirus 2 (CPV-2) were synthesized and evaluated. An improved polymerase cross-linking spiral reaction (PCLSR) method for early and rapid diagnosis of CPV-2 was established. The results showed that the amplification reaction was optimal when run at 62°C for 50 min and could be used to detect CPV-2 without any cross-reactions with other pathogens of canine infectious diseases. Reaction results were directly judged by the naked eyes, with the positive amplification tube shown as luminous yellow and the negative tube as bright purple. Compared with the previously reported polymerase spiral reaction (PSR) method for CPV-2 detection, this reaction was performed using improved primer pairs and a better dye identification method (using an indicator comprising phenol red and cresol red). The detection limit of PCLSR was 3.9 × 101 copies using gel electrophoresis or a visible dye. The positive rate of 132 clinical samples was 42.42%, which was identically the same as that of the PSR method and slightly higher than that of the colloidal gold strip method (39.39%). The newly developed CPV-PCLSR assay shows the advantage of rapid visualization of results and offers a convenient and rapid method for early CPV-2 diagnosis with higher sensitivity and specificity than the established methods.

Circular RNAs (circRNAs) are considered as functional biomolecules with tissue/development-specific expression patterns. Generally, a single gene may generate multiple circRNA variants by alternative splicing, which contain different combinations of exons and/or introns. Due to the low abundance of circRNAs as well as overlapped with their linear counterparts, circRNA enrichment protocol is needed prior to sequencing. Compared with numerous algorithms, which use back-splicing reads for detection and functional characterization of circRNAs, original bioinformatic analyzing tools have been developed to large-scale determination of full-length circRNAs and accurate quantification. This review provides insights into the complexity of circRNA biogenesis and surveys the recent progresses in the experimental and bioinformatic methodologies that focus on accurately full-length circRNAs identification.

In this paper, we examine rates of careless responding and reactions towards detection methods (i.e., attention check item and instruction) in an experimental setting based on two different samples. First, we use a quota sample (with monetary incentive), a central data source for internet-based surveys in sociological and political research. Second, we include a voluntary opt-in panel (without monetary incentive) well suited to conduct survey experiments (e.g., factorial surveys). Respondents’ reactions towards the detection items are analyzed by objective, non-reactive indicators (i.e., break-off, item nonresponse, and measurement quality), and two self-report scales. Our reaction analyses reveal that the detection methods that we applied are not only well suited to identify careless respondents but also exert a motivational rather than demotivating influence on respondents’ answer behavior and, hence, contribute to data quality.

As buildings wear out, external wall tiles or attachments will usually fall off, sometimes causing human injuries. At present, the method employed for middle-high rise buildings is mainly the method of visual inspection. The inspection results in using this method are affected by the factors of subjectivity, safety and cost. This study aims to provide a lowercost and more efficient evaluation method for inspecting the status of buildings’ external walls. This proposed method implements Forward Looking Infrared (FLIR) technology and high-resolution photographic equipment on Unmanned Aerial Vehicle (UAV) which can improve the image recording of the detection process, as well as the overall visual detection technology, and solve the existing visual detection problem of inspectors. Also, the images detected by visual inspection and UAV high-resolution video are used to develop a suitable visual evaluation process and test table for external walls. Through the test results of several cases, the deterioration status and needs for maintenance are taken into account according to the degree of performance indicators. The findings of the study is that the proposed mechanism is more efficient and lower cost for the detection of external walls or ancillary structures’ abnormal status, which is easy to use in practice.