A Comparative Study Into Procedures for Postmortem Inspection for Finishing Pigs

1992 ◽  
Vol 55 (8) ◽  
pp. 620-626 ◽  
Author(s):  
T. H. M. HARBERS ◽  
J. F. M. SMEETS ◽  
J. A. J. FABER ◽  
J. M. A. SNIJDERS ◽  
J. G. VAN LOGTESTIJN

A postmortem meat inspection system based primarily on visual inspection without palpation or incision was compared with regular meat inspection procedures based on European Community (EC) regulations, which consists of visual inspection, palpation, and incision of organs. Two experiments included 31,682 finishing pigs. Three inspection procedures were followed: visual, i.e., an inspection without manipulation of the carcass; regular, i.e., based on EC regulations; and extra, i.e., based on EC regulations with more time allowed for the inspection. The reproducibility and accuracy of the visual and regular inspection methods were compared with those of the extra inspection. Twelve postmortem abnormalities and four additional findings were compared. The reproducibility of the visual inspection, measured with Cohen's kappa (CK), was poor to fair (CK from 0.14 to 0.64), and the regular inspection also had a poor to fair reproducibility (CK from 0.24 to 0.73). The specificity and sensitivity of the visual and regular inspection methods did not differ significantly for most of the abnormalities and additional findings. The sensitivity was low (range 0–76%) and the number of false-negative findings was sometimes high. It can be concluded that many abnormalities and additional findings are detected equally well by visual and regular postmortem inspection procedures. It is concluded that since both inspection procedures are far from perfect, risk assessment should be performed.

2021 ◽  
Author(s):  
Shaymaa A. Abdelmalek ◽  
Karim Shokry ◽  
Wafy Hamed ◽  
Mohammed Abdelnalser ◽  
Ashraf Aboubakr ◽  
...  

Molecular diagnosis of helicobacters by PCR is simpler, more accurate, and feasible compared to other diagnostic methods. Validity and accuracy are highly dependent on the PCR primer design, diffusion time, and mutation rate of helicobacters. This study aimed to design 16srRNA -specific primers for Helicobacter spp. and H. pylori . Application of comparative statistical analysis of the diagnostic utility of the most available 16srRNA genus-specific primers. The new primers were designed using bioinformatics tools (MAFFT MSA and Gblocks command line). A comparative study was applied on nine genus-specific 16srRNA primers in comparison to the ConsH using Insilco and laboratory evaluation. The results demonstrated that the best specificity and sensitivity of the primers designed for this study compared to other primers. The comparative study revealed that the heminested outer/inner primers were the worst. Although H276,16srRNA(a), HeliS/Heli-nest, and Hcom had acceptable diagnostic utility, false positive and false negative results were obtained. Specificity testing on clinical samples indicated a surprising result; that H. pylori was not the sole enemy that we were looking for, but the NPH should be considered as a real risk prognostic for gastric diseases, consequently, a specific diagnosis and treatment should be developed. This study concluded that our designed primers were the most specific and sensitive in comparison with other primers. in addition, Insilco evaluation is not accurate enough for primer assessment and that the laboratory evaluation is mandatory.


2010 ◽  
Vol 36 (5) ◽  
pp. 984-989
Author(s):  
Zhe ZHAO ◽  
Chun-Hua REN ◽  
Xiao JIANG ◽  
Lü-Ping ZHANG ◽  
Juan FENG ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Joshua M. Levy ◽  
Jennifer K. Frediani ◽  
Erika A. Tyburski ◽  
Anna Wood ◽  
Janet Figueroa ◽  
...  

AbstractThe impact of repeated sample collection on COVID-19 test performance is unknown. The FDA and CDC currently recommend the primary collection of diagnostic samples to minimize the perceived risk of false-negative findings. We therefore evaluated the association between repeated sample collection and test performance among 325 symptomatic patients undergoing COVID-19 testing in Atlanta, GA. High concordance was found between consecutively collected mid-turbinate samples with both molecular (n = 74, 100% concordance) and antigen-based (n = 147, 97% concordance, kappa = 0.95, CI = 0.88–1.00) diagnostic assays. Repeated sample collection does not decrease COVID-19 test performance, demonstrating that multiple samples can be collected for assay validation and clinical diagnosis.


2021 ◽  
Vol 1048 (1) ◽  
pp. 012015
Author(s):  
Dieuthuy Pham ◽  
Minhtuan Ha ◽  
Changyan Xiao

1991 ◽  
Author(s):  
Tetsuo Koezuka ◽  
Yoshikazu Kakinoki ◽  
Shinji Hashinami ◽  
Masato Nakashima

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lukman E. Mansuri ◽  
D.A. Patel

PurposeHeritage is the latent part of a sustainable built environment. Conservation and preservation of heritage is one of the United Nations' (UN) sustainable development goals. Many social and natural factors seriously threaten heritage structures by deteriorating and damaging the original. Therefore, regular visual inspection of heritage structures is necessary for their conservation and preservation. Conventional inspection practice relies on manual inspection, which takes more time and human resources. The inspection system seeks an innovative approach that should be cheaper, faster, safer and less prone to human error than manual inspection. Therefore, this study aims to develop an automatic system of visual inspection for the built heritage.Design/methodology/approachThe artificial intelligence-based automatic defect detection system is developed using the faster R-CNN (faster region-based convolutional neural network) model of object detection to build an automatic visual inspection system. From the English and Dutch cemeteries of Surat (India), images of heritage structures were captured by digital camera to prepare the image data set. This image data set was used for training, validation and testing to develop the automatic defect detection model. While validating this model, its optimum detection accuracy is recorded as 91.58% to detect three types of defects: “spalling,” “exposed bricks” and “cracks.”FindingsThis study develops the model of automatic web-based visual inspection systems for the heritage structures using the faster R-CNN. Then it demonstrates detection of defects of spalling, exposed bricks and cracks existing in the heritage structures. Comparison of conventional (manual) and developed automatic inspection systems reveals that the developed automatic system requires less time and staff. Therefore, the routine inspection can be faster, cheaper, safer and more accurate than the conventional inspection method.Practical implicationsThe study presented here can improve inspecting the built heritages by reducing inspection time and cost, eliminating chances of human errors and accidents and having accurate and consistent information. This study attempts to ensure the sustainability of the built heritage.Originality/valueFor ensuring the sustainability of built heritage, this study presents the artificial intelligence-based methodology for the development of an automatic visual inspection system. The automatic web-based visual inspection system for the built heritage has not been reported in previous studies so far.


2018 ◽  
Vol 14 (1) ◽  
Author(s):  
Sergio Ghidini ◽  
Emanuela Zanardi ◽  
Pierluigi Aldo Di Ciccio ◽  
Silvio Borrello ◽  
Giancarlo Belluzi ◽  
...  

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