Modelling a two-dimensional spatial distribution of mycotoxin concentration in bulk commodities to design effective and efficient sample selection strategies

Mycotoxins in agricultural commodities are a hazard to human and animal health. Their heterogeneous spatial distribution in bulk storage or transport makes it particularly difficult to design effective and efficient sampling plans. There has been considerable emphasis on identifying the different sources of uncertainty associated with mycotoxin concentration estimations, but much less on identifying the effect of the spatial location of the sampling points. This study used a two-dimensional statistical modelling approach to produce detailed information on appropriate sampling strategies for surveillance of mycotoxins in raw food commodities. The emphasis was on deoxynivalenol (DON) and ochratoxin A (OTA) in large lots of grain in storage or bulk transport. The aim was to simulate a range of plausible distributions of mycotoxins in grain from a set of parameters characterising the distributions. For this purpose, a model was developed to generate data sets which were repeatedly sampled to investigate the effect that sampling strategy and the number of incremental samples has on determining the statistical properties of mycotoxin concentration. Results showed that, for most sample sizes, a regular grid proved to be more consistent and accurate in the estimation of the mean concentration of DON, which suggests that regular sampling strategies should be preferred to random sampling, where possible. For both strategies, the accuracy of the estimation of the mean concentration increased significantly up to sample sizes of 40-60 (depending on the simulation). The effect of sample size was small when it exceeded 60 points, which suggests that the maximum sample size required is of this order. Similar conclusions about the sample size apply to OTA, although the difference between regular and random sampling was small and probably negligible for most sample sizes

EVALUATION OF LIVER PARENCHYMA AND PERFUSION USING DYNAMIC CONTRAST-ENHANCED COMPUTED TOMOGRAPHY AND CONTRAST-ENHANCED ULTRASONOGRAPHY IN CAPTIVE GREEN IGUANAS (IGUANA IGUANA) UNDER GENERAL ANESTHESIA

Background: Contrast-enhanced diagnostic imaging techniques are considered useful in veterinary and human medicine to evaluate liver perfusion and focal hepatic lesions. Although hepatic diseases are a common occurrence in reptile medicine, there is no reference to the use of contrast-enhanced ultrasound (CEUS) and contrast-enhanced computed tomography (CECT) to evaluate the liver in lizards. Therefore, the aim of this study was to evaluate the pattern of change in echogenicity and attenuation of the liver in green iguanas (Iguana iguana) after administration of specific contrast media. Results: An increase in liver echogenicity and density was evident during CEUS and CECT, respectively. In CEUS, the mean \ub1 SD (median; range) peak enhancement was 19.9% \ub1 7.5 (18.3; 11.7-34.6). Time to peak enhancement was 134.0 \ub1 125.1 (68.4; 59.6-364.5) seconds. During CECT, first visualization of the contrast medium was at 3.6 \ub1 0.5 (4; 3-4) seconds in the aorta, 10.7 \ub1 2.2 (10.5; 7-14) seconds in the hepatic arteries, and 15 \ub1 4.5 (14.5; 10-24) seconds in the liver parenchyma. Time to peak was 14.1 \ub1 3.4 (13; 11-21) and 31 \ub1 9.6 (29; 23-45) seconds in the aorta and the liver parenchyma, respectively. Conclusion: CEUS and dynamic CECT are practical means to determine liver hemodynamics in green iguanas. Distribution of contrast medium in iguana differed from mammals. Specific reference ranges of hepatic perfusion for diagnostic evaluation of the liver in iguanas are necessary since the use of mammalian references may lead the clinician to formulate incorrect diagnostic suspicions

Angiostrongylus dujardini infection in a coconut lorikeet (Trichoglossus haematodus) from a zoological garden in Switzerland.

Angiostrongylus spp. (Metastrongyloidea) can cause severe disease in several animal species and humans. This report describes an infection with Angiostrongylus dujardini in a captive Coconut lorikeet (Trichoglossus haematodus) from a zoo in Switzerland. The bird was reported being attacked by conspecifics, removed from the flock, and hospitalized. It showed lethargy, moderately reduced body condition, and lack of reaction to visual stimuli. Analgesic and antibiotic treatment were initiated but because of worsening of its general condition the bird was euthanized the following day. Necropsy revealed multifocal, subcutaneous hemorrhages, diffusely reddened lungs and a moderately dilated right heart with several intraluminal nematodes embedded in a coagulum. Four worms were collected and microscopically examined. They were identified as adult females, measuring 19-21 mm long x 0.4-0.5 mm wide, with general morphological and morphometric characteristics consistent with angiostrongylid nematodes. In lung sections, multifocal collection of thin-walled embryonated eggs in variable stages of development was observed along with fully developed nematode larvae within the lumina of alveoli and lung vessels. Associated granulomatous infiltrates indicated a severe, multifocal, chronic, granulomatous pneumonia. The diagnosis of A. dujardini infection was formulated by morphological examination of adult and larval stages, supported by molecular analysis (PCR-amplification and sequencing of the ITS2, 5.8S and 28S rDNA flanking regions). This is the first report of A. dujardini infection in an avian species, providing evidence that birds can serve as accidental hosts of this parasite in addition to mammals, and that the parasite can reach maturity and multiply in the avian cardiorespiratory system

Radiomics : the facts and the challenges of image analysis

Radiomics is an emerging translational field of research aiming to extract mineable high-dimensional data from clinical images. The radiomic process can be divided into distinct steps with definable inputs and outputs, such as image acquisition and reconstruction, image segmentation, features extraction and qualification, analysis, and model building. Each step needs careful evaluation for the construction of robust and reliable models to be transferred into clinical practice for the purposes of prognosis, non-invasive disease tracking, and evaluation of disease response to treatment. After the definition of texture parameters (shape features; first-, second-, and higher-order features), we briefly discuss the origin of the term radiomics and the methods for selecting the parameters useful for a radiomic approach, including cluster analysis, principal component analysis, random forest, neural network, linear/logistic regression, and other. Reproducibility and clinical value of parameters should be firstly tested with internal cross-validation and then validated on independent external cohorts. This article summarises the major issues regarding this multi-step process, focussing in particular on challenges of the extraction of radiomic features from data sets provided by computed tomography, positron emission tomography, and magnetic resonance imaging

Association of a CT-based clinical and radiomics score of non-small cell lung cancer (NSCLC) with lymph node status and overall survival

Background: To evaluate whether a model based on radiomic and clinical features may be associated with lymph node (LN) status and overall survival (OS) in lung cancer (LC) patients; to evaluate whether CT reconstruction algorithms may influence the model performance. Methods: patients operated on for LC with a pathological stage up to T3N1 were retrospectively selected and divided into training and validation sets. For the prediction of positive LNs and OS, the Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression model was used; univariable and multivariable logistic regression analysis assessed the association of clinicalradiomic variables and endpoints. All tests were repeated after dividing the groups according to the CT reconstruction algorithm. p-values < 0.05 were considered significant. Results: 270 patients were included and divided into training (n = 180) and validation sets (n = 90). Transfissural extension was significantly associated with positive LNs. For OS prediction, high-and low-risk groups were different according to the radiomics score, also after dividing the two groups according to reconstruction algorithms. Conclusions: a combined clinical\u2013radiomics model was not superior to a single clinical or single radiomics model to predict positive LNs. A radiomics model was able to separate high-risk and low-risk patients for OS; CTs reconstructed with Iterative Reconstructions (IR) algorithm showed the best model performance

Radiation exposure of ovarian cancer patients : contribution of CT examinations performed on different MDCT (16 and 64 slices) scanners and image quality evaluation an observational study

The objective of this study is to compare radiation doses given to ovarian cancer patients by different computed tomographies (CTs) and to evaluate association between doses and subjective and objective image quality.CT examinations included were performed either on a 16-slice CT, equipped with automatic z-axis tube current modulation, or on a 64-slice CT, equipped with z-axis, xy-axis modulation, and adaptive statistical iterative algorithm (ASIR). Evaluation of dose included the following dose descriptors: volumetric CT dose index (CTDIvol), dose length product (DLP), and effective dose (E). Objective image noise was evaluated in abdominal aorta and liver. Subjective image quality was evaluated by assessment of image noise, spatial resolution and diagnostic acceptability.Mean and median CTDIvol, DLP, and E; correlation between CTDIvol and DLP and patients' weight; comparison of objective noise for the 2 scanners; association between dose descriptors and subjective image quality.The 64-slice CT delivered to patients 24.5% lower dose (P\u200a<\u200a0.0001) than 16-slice CT. There was a significant correlation between all dose descriptors (CTDIvol, DLP, E) and weight (P\u200a<\u200a0.0001). Objective noise was comparable for the 2 CT scanners. There was a significant correlation between dose descriptors and image noise for the 64-slice CT, and between dose descriptors and spatial resolution for the 16-slice CT.Current dose reduction systems may reduce radiation dose without significantly affecting image quality and diagnostic acceptability of CT exams

Association of a CT-Based Clinical and Radiomics Score of Non-Small Cell Lung Cancer (NSCLC) with Lymph Node Status and Overall Survival

Background: To evaluate whether a model based on radiomic and clinical features may be associated with lymph node (LN) status and overall survival (OS) in lung cancer (LC) patients; to evaluate whether CT reconstruction algorithms may influence the model performance. Methods: patients operated on for LC with a pathological stage up to T3N1 were retrospectively selected and divided into training and validation sets. For the prediction of positive LNs and OS, the Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression model was used; univariable and multivariable logistic regression analysis assessed the association of clinical-radiomic variables and endpoints. All tests were repeated after dividing the groups according to the CT reconstruction algorithm. p-values &lt; 0.05 were considered significant. Results: 270 patients were included and divided into training (n = 180) and validation sets (n = 90). Transfissural extension was significantly associated with positive LNs. For OS prediction, high- and low-risk groups were different according to the radiomics score, also after dividing the two groups according to reconstruction algorithms. Conclusions: a combined clinical\u2013radiomics model was not superior to a single clinical or single radiomics model to predict positive LNs. A radiomics model was able to separate high-risk and low-risk patients for OS; CTs reconstructed with Iterative Reconstructions (IR) algorithm showed the best model performance

The golden jackal (Canis aureus): A new host for Echinococcus multilocularis and Trichinella britovi in Switzerland.

INTRODUCTION The golden jackal (Canis aureus) is a wild canid new to Switzerland. It is an officially monitored species and all deceased individuals are submitted for post-mortem examination to collect baseline health data. This includes parasitological examinations, with an emphasis on zoonotic, reportable infections, such as those caused by Trichinella spp. or Echinococcus spp. From 2016 to 2021, five golden jackals originating from four Swiss cantons were submitted for full post-mortem examination. In one case only organ samples were available, and therefore parasitological examination was not possible. Parasite stages recovered during necropsy, as well as by routine coproscopical techniques, were morphologically identified. Taeniid eggs and adult tapeworms were processed for molecular species identification. Additionally, tongue and diaphragm were analysed for Trichinella spp. by the artificial digestion technique followed by multiplex-PCR in positive cases. Of the four jackals investigated for parasites, hookworm eggs were detected in one animal, both adult worms and eggs of Echinococcus multilocularis were present in another case, and one animal was free of parasites. Eggs of E. multilocularis as well as eggs of Toxocara canis and sporocysts of Sarcocystis sp. were detected in the intestinal content, and Trichinella britovi larvae were found in the muscle samples of the last case. The health monitoring programme in place for protected carnivores in Switzerland allowed us to add the golden jackal to the list of hosts for the endemic zoonotic parasites E. multilocularis and T. britovi in this country. Hunters, farmers, and other persons who could come in contact with golden jackals should be aware of the associated health risk and handle faeces and carcasses with caution

Observational Study Design in Veterinary Pathology, Part 2: Methodology

Observational studies are a basis for much of our knowledge of veterinary pathology, yet considerations for conducting pathology-based observational studies are not readily available. In part 1 of this series, we offered advice on planning and carrying out an observational study. Part 2 of the series focuses on methodology. Our general recommendations are to consider using already-validated methods, published guidelines, data from primary sources, and quantitative analyses. We discuss 3 common methods in pathology research—histopathologic scoring, immunohistochemistry, and polymerase chain reaction—to illustrate principles of method validation. Some aspects of quality control include use of clear objective grading criteria, validation of key reagents, assessing sample quality, determining specificity and sensitivity, use of technical and biologic negative and positive controls, blinding of investigators, approaches to minimizing operator-dependent variation, measuring technical variation, and consistency in analysis of the different study groups. We close by discussing approaches to increasing the rigor of observational studies by corroborating results with complementary methods, using sufficiently large numbers of study subjects, consideration of the data in light of similar published studies, replicating the results in a second study population, and critical analysis of the study findings

Implicit trust in clinical decision-making by multidisciplinary teams

In clinical practice, decision-making is not performed by individual knowers but by an assemblage of people and instruments in which no one member has full access to every piece of evidence. This is due to decision making teams consisting of members with different kinds of expertise, as well as to organisational and time constraints. This raises important questions for the epistemology of medicine, which is inherently social in this kind of setting, and implies epistemic dependence on others. Trust in these contexts is a highly complex social practice, involving different forms of relationships between trust and reasons for trust: based on reasons, and not based on reasons; based on reasons that are easily accessible to reflection and others that are not. In this paper, we focus on what it means to have reasons to trust colleagues in an established clinical team, collectively supporting or carrying out every day clinical decision-making. We show two important points about these reasons, firstly, they are not sought or given in advance of a situation of epistemic dependence, but are established within these situations; secondly they are implicit in the sense of being contained or nested within other actions that are not directly about trusting another person. The processes of establishing these reasons are directly about accomplishing a task, and indirectly about trusting someone else’s expertise or competence. These processes establish a space of reasons within which what it means to have reasons for trust, or not, gains a meaning and traction in these team-work settings. Based on a qualitative study of decision-making in image assisted diagnosis and treatment of a complex disease called pulmonary hypertension (PH), we show how an intersubjective framework, or ‘space of reasons’ is established through team members forging together a common way of identifying and dealing with evidence. In dealing with images as a central diagnostic tool, this also involves a common way of looking at the images, a common mode or style of perception. These frameworks are developed through many iterations of adjusting and calibrating interpretations in relation to those of others, establishing what counts as evidence, and ranking different kinds of evidence. Implicit trust is at work throughout this process. Trusting the expertise of others in clinical decision-making teams occurs while the members of the team are busy on other tasks, most importantly, building up a framework of common modes of seeing, and common ways of identifying and assessing evidence emerge. It is only in this way that trusting or mistrusting becomes meaningful in these contexts, and that a framework for epistemic dependence is established