scholarly journals The Complex Co-infections of Multiple Porcine Diarrhea Viruses in Local Area Based on the Luminex xTAG Multiplex Detection Method

2021 ◽  
Vol 8 ◽  
Author(s):  
Ying Shi ◽  
Benqiang Li ◽  
Jie Tao ◽  
Jinghua Cheng ◽  
Huili Liu
Keyword(s):  
Large Scale ◽  
Detection Method ◽  
Local Area ◽  
Multiple Infections ◽  
Multiplex Detection ◽  
Viral Diarrhea ◽  
Severe Diarrhea ◽  
Infection Pattern ◽  
Etiologic Agents ◽  
Positive Rate

The large-scale outbreaks of severe diarrhea caused by viruses have occurred in pigs since 2010, resulting in great damage to the pig industry. However, multiple infections have contributed to the outbreak of the disease and also resulted in great difficulties in diagnosis and control of the disease. Thus, a Luminex xTAG multiplex detection method, which was more sensitive and specific than general multiplex PCR method, was developed for the detection of 11 viral diarrhea pathogens, including PKoV, PAstV, PEDV, PSaV, PSV, PTV, PDCoV, TGEV, BVDV, PoRV, and PToV. To investigate the prevalence of diarrhea-associated viruses responsible for the outbreaks, a total of 753 porcine stool specimens collected from 9 pig farms in Shanghai during 2015–2018 were tested and the pathogen spectrums and co-infections were analyzed. As a result, PKoV, PAstV and PEDV were most commonly detected viruses in diarrheal pigs with the rate of 38.65% (291/753), 20.32% (153/753), and 15.54% (117/753), respectively. Furthermore, multiple infections were commonly seen, with positive rate of 28.42%. Infection pattern of the viral diarrhea pathogens in a specific farm was changing, and different farms had the various diarrhea infection patterns. A longitudinal investigation showed that PEDV was the key pathogen which was closely related to the death of diarrhea piglets. Other pathogens might play synergistic roles in the pathogenesis of diarrhea disease. Furthermore, the surveillance confirmed that variant enteropathogenic viruses were leading etiologic agents of porcine diarrhea, either mono-infection or co-infections of PKoV were common in pigs in Shanghai, but PEDV was still the key pathogen and multiple pathogens synergistically complicated the infection status, suggesting that controlling porcine diarrhea might be more complex than previously thought. The study provides a better understanding of diarrhea viruses in piglets, which will aid in better preventing and controlling epidemics of viral porcine diarrhea.

scholarly journals The Multiple Infections of Porcine Diarrhea Viruses in Local Area Based on A Luminex xTAG Multiplex Detection Method

2020 ◽  
Author(s):  
Huili liu ◽  
Ying Shi ◽  
Benqiang Li ◽  
Jie Tao ◽  
Jinghua Cheng
Keyword(s):  
Detection Method ◽  
Southern China ◽  
Local Area ◽  
Clinical Samples ◽  
Multiple Infections ◽  
Quantitative Detection ◽  
Multiplex Detection ◽  
Viral Diarrhea ◽  
Infection Pattern ◽  
Pcr Method

Abstract Background Porcine viral diarrhea can cause great damage to the pig industry. However, multiple infections have contributed to the poor control of diarrhea, which has also resulted in great difficulties in determining the main pathogenic factors. Methods A Luminex xTAG multiplex detection method was developed for the detection of 11 viral diarrhea pathogens, which allows for the simultaneous qualitative and quantitative detection of viral diarrhea pathogens in clinical samples. A total of 518 porcine stool specimens were collected from 9 pig herds in Shanghai, China from 2015 to 2017, and the pathogen spectrums and co-infections were analyzed. Results The minimum detection rate of the Luminex xTAG multiplex detection method was at least 10 times higher than the traditional PCR method. Of the 518 diarrhea samples, PEDV was found in 17.57% (91/518), PKoV in 40.35% (209/518), PAstV in 26.64% (138/518), PSV in 15.06% (78/518), PoSaV in 13.13% (68/518), PTV in 5.21% (27/518), PDCoV in 4.83% (25/518), PoRV in 3.28% (17/518), TGEV in 3.09% (16/518), PToV in 1.93% (10/518), and BVDV in 1.74% (9/518), respectively. Furthermore, multiple infections were commonly seen, with positive rate of 35.14%. Infection pattern of the viral diarrheal pathogens in a specific farm was changing, and different farms had the various diarrhea infection patterns. A longitudinal investigation showed that PEDV was still the key pathogen which was closely related to the death of diarrhea piglets. Other pathogens might play synergistic roles in the pathogenesis of diarrhea disease. Conclusions Here we provided a Luminex xTAG multiple detection method for viral diarrhea pathogen infection in clinical, which was more sensitive and specific than general multiplex PCR method. Furthermore, the surveillance confirmed high infection rate of PKoV, but PEDV was still the key pathogen and multiple pathogens synergistically complicated the infection status in southern China, suggesting that controlling porcine diarrhea might be more complex than previously thought. A better understanding of viruses that cause diarrhea in piglets will aid in better preventing and controlling epidemics of viral porcine diarrhea.

scholarly journals Epidemiological analysis of Porcine Viral Diarrhea Pathogens in Local Area

2020 ◽  
Author(s):  
Ying Shi ◽  
Benqiang Li ◽  
Jie Tao ◽  
Jinghua Cheng ◽  
Huili liu
Keyword(s):  
Prevention And Control ◽  
Detection Method ◽  
Multiple Infection ◽  
Clinical Samples ◽  
Quantitative Detection ◽  
Multiplex Detection ◽  
Diarrhea Virus ◽  
Viral Diarrhea ◽  
Pcr Method ◽  
And Control

Abstract Background Porcine viral diarrhea can cause great damage to the pig industry and high mortality to piglets. Furthermore, multiple pathogen infections and synergistic infections commonly existed in clinic. This has resulted in great difficulties in determining the main pathogenic factors, which would delay the prevention and control of diseases. Methods A total of 518 porcine stool specimens were collected from 9 pig herds in Shanghai, China from 2015 to 2017 and used for pathogen detection. A Luminex xTAG multiplex detection method was developed for the detection of 11 viral diarrhea pathogens, which allows for the simultaneous qualitative and quantitative detection of viral diarrhea pathogens in clinical samples. Results The minimum detection rate of the Luminex xTAG multiplex detection method was at least 10 times higher than the traditional PCR method. As a result, 209 (40.3%) were positive for porcine kobuvirus (PKoV), 138 (26.6%) for porcine astrovirus (PAstV), 91 (17.6%) for porcine epidemic diarrhea virus (PEDV), 78 (15.1%) for porcine sapelovirus (PSV), 68 (13.1%) for porcine sapovirus (PoSaV), 27 (5.2%) for porcine teschovirus (PTV), 25 (4.8%) for porcine deltacoronavirus (PDCoV), 17 (3.3%) for porcine rotavirus (PoRV), 16 (3.1%) for transmissible gastroenteritis virus (TGEV), 10 (1.9%) for porcine torovirus (PToV), and 9 (1.7%) for bovine viral diarrhea virus (BVDV), respectively. Furthermore, multiple infection rate of diarrhea sample was 17.57% for dual-infection, 11.58%for triple-infection, 4.63% for quadruple-infection, 0.77% for quintuple-infection, 0.58% for sextuple-infection and septuple-infection, respectively. Infection pattern of the viral diarrheal pathogens was changing, and different farm had the various diarrhea infection patterns, which proved the great importance of epidemiological surveillance and the guidance effect to clinical production. PoSaV, PoRV, PAstV, PToV and PEDV were indicated as the predominant viruses of clinical samples collected in 2017 by the quantitative analysis. Conclusions Here we provide a Luminex xTAG multiple detection method for viral diarrhea pathogen infection in clinical,which was more sensitive and specific than general multiplex PCR method. Furthermore, the surveillance confirmed the complicated infection status in China, which demonstrated the need for continuous surveillance and provided data for the prevention and control of viral diarrhea.

scholarly journals Structural similarity based common library detection method for Android

2021 ◽  
Vol 39 (2) ◽  
pp. 448-453
Author(s):  
Zhiying Mu ◽  
Zhihu Li ◽  
Xiaoyu Li
Keyword(s):  
Large Scale ◽  
Detection Method ◽  
False Positive Rate ◽  
Structural Similarity ◽  
Detection Methods ◽  
Fine Grained ◽  
Real World Applications ◽  
Positive Rate ◽  
Android Applications ◽  
Detection Speed

The correct classifying and filtering of common libraries in Android applications can effectively improve the accuracy of repackaged application detection. However, the existing common library detection methods barely meet the requirement of large-scale app markets due to the low detection speed caused by their classification rules. Aiming at this problem, a structural similarity based common library detection method for Android is presented. The sub-packages with weak association to main package are extracted as common library candidates from the decompiled APK (Android application package) by using PDG (program dependency graph) method. With package structures and API calls being used as features, the classifying of those candidates is accomplished through coarse and fine-grained filtering. The experimental results by using real-world applications as dataset show that the detection speed of the present method is higher while the accuracy and false positive rate are both ensured. The method is proved to be efficient and precise.

Identification of and Correction for Publication Bias: Comment

2019 ◽  
Author(s):  
Amanda Kvarven ◽  
Eirik Strømland ◽  
Magnus Johannesson
Keyword(s):  
Publication Bias ◽  
False Positive ◽  
Large Scale ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Effect Sizes ◽  
Replication Studies ◽  
Moderate Reduction ◽  
Positive Rate ◽  
Meta Analyses

Andrews & Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.

scholarly journals PRATD: A Phased Remote Access Trojan Detection Method with Double-Sided Features

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1894
Author(s):  
Chun Guo ◽  
Zihua Song ◽  
Yuan Ping ◽  
Guowei Shen ◽  
Yuhei Cui ◽  
...  
Keyword(s):  
False Positive ◽  
Detection Method ◽  
False Positive Rate ◽  
True Positive Rate ◽  
Remote Access ◽  
Detection Methods ◽  
Security Threats ◽  
True Positive ◽  
Trojan Detection ◽  
Positive Rate

Remote Access Trojan (RAT) is one of the most terrible security threats that organizations face today. At present, two major RAT detection methods are host-based and network-based detection methods. To complement one another’s strengths, this article proposes a phased RATs detection method by combining double-side features (PRATD). In PRATD, both host-side and network-side features are combined to build detection models, which is conducive to distinguishing the RATs from benign programs because that the RATs not only generate traffic on the network but also leave traces on the host at run time. Besides, PRATD trains two different detection models for the two runtime states of RATs for improving the True Positive Rate (TPR). The experiments on the network and host records collected from five kinds of benign programs and 20 famous RATs show that PRATD can effectively detect RATs, it can achieve a TPR as high as 93.609% with a False Positive Rate (FPR) as low as 0.407% for the known RATs, a TPR 81.928% and FPR 0.185% for the unknown RATs, which suggests it is a competitive candidate for RAT detection.

scholarly journals Modelling Reliability Characteristics of Technical Equipment of Local Area Computer Networks

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 955
Author(s):  
Vasyl Teslyuk ◽  
Andriy Sydor ◽  
Vincent Karovič ◽  
Olena Pavliuk ◽  
Iryna Kazymyra
Keyword(s):  
Large Scale ◽  
Computer Network ◽  
Network Reliability ◽  
Local Area ◽  
Technical Equipment ◽  
Time To Failure ◽  
Reliability Parameters ◽  
Reliability Characteristics ◽  
Global World ◽  
Level 2

Technical systems in the modern global world are rapidly evolving and improving. In most cases, these are large-scale multi-level systems and one of the problems that arises in the design process of such systems is to determine their reliability. Accordingly, in the paper, a mathematical model based on the Weibull distribution has been developed for determining a computer network reliability. In order to simplify calculating the reliability characteristics, the system is considered to be a hierarchical one, ramified to level 2, with bypass through the level. The developed model allows us to define the following parameters: the probability distribution of the count of working output elements, the availability function of the system, the duration of the system’s stay in each of its working states, and the duration of the system’s stay in the prescribed availability condition. The accuracy of the developed model is high. It can be used to determine the reliability parameters of the large, hierarchical, ramified systems. The research results of modelling a local area computer network are presented. In particular, we obtained the following best option for connecting workstations: 4 of them are connected to the main hub, and the rest (16) are connected to the second level hub, with a time to failure of 4818 h.

scholarly journals Efficient Detection of Large-Scale Multimedia Network Information Data Anomalies Based on the Rule-Extracting Matrix Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Jie Zhao
Keyword(s):  
Large Scale ◽  
False Positive Rate ◽  
Detection Accuracy ◽  
Network Information ◽  
Matrix Algorithm ◽  
Efficient Detection ◽  
Sample Data ◽  
Multimedia Social Networks ◽  
Positive Rate ◽  
Rule Extracting

With the continuous development of multimedia social networks, online public opinion information is becoming more and more popular. The rule extraction matrix algorithm can effectively improve the probability of information data to be tested. The network information data abnormality detection is realized through the probability calculation, and the prior probability is calculated, to realize the detection of abnormally high network data. Practical results show that the rule-extracting matrix algorithm can effectively control the false positive rate of sample data, the detection accuracy is improved, and it has efficient detection performance.

scholarly journals Ovarian fibrosarcoma: A single-institution experience and a review of the literature

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Ting-Ting Sun ◽  
Ning-Hai Cheng ◽  
Dong-Yan Cao ◽  
Peng Peng
Keyword(s):  
Large Scale ◽  
Pelvic Mass ◽  
Final Diagnosis ◽  
College Hospital ◽  
Ki 67 ◽  
Nccn Guidelines ◽  
Surgical Methods ◽  
Initial Symptoms ◽  
Positive Rate ◽  
Low Incidence

AbstractOvarian fibrosarcoma is an extremely rare and malignant sex cord-stromal tumor. Due to its low incidence and poor prognosis, until now, very few cases have been reported, and most of the reported cases have been sporadic. Therefore, the treatments and prognostic factors of ovarian fibrosarcoma are still debatable. Here, we report 5 cases of ovarian fibrosarcoma that presented at Peking Union Medical College Hospital over the past 20 years. The 5 patients were 41, 51, 54, 76, and 76 years of age when initial symptoms of pelvic mass or pain appeared. On ultrasound, this disease usually manifests as unilateral pelvic masses, within which uneven echo enhancement and some blood flow signals are observed. No significant increase was observed in the levels of preoperative tumor markers, such as serum CA125 and sex hormones. The final diagnosis depends on postoperative histopathological results since these tumors are easily misdiagnosed when intraoperative frozen sections are used for examination. Pathologic examinations showed that the tumor cells were spindle-shaped with moderate to severe atypia and high mitotic counts. The immunohistochemistry profile is not specific, but the positive rate of Ki-67 was consistent with the degree of malignancy and the prognosis of patients with this tumor. In addition, the tumor may also be positive for Vimentin, α-inhibin, SMA, estrogen receptor and progesterone receptor. Significant differences were observed in the surgical methods used, and no unified chemotherapy regimen has been established. The overall survival was > 15, >7, > 6, <1, and < 1 year for each patient. After reviewing the literature, evidence-based large-scale case studies were lacking. For treatments, complete cytoreductive surgery plus regimens typically used against malignant sex cord-stromal tumors, as described in the NCCN guidelines, are recommended. Due to its low incidence, both multicenter clinical studies and molecular studies are required to provide gynecologists with a better understanding and guidance for future management of patients with ovarian fibrosarcoma.

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