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Background The worldwide increased difficulty to combat gastrointestinal nematode (GIN) infection in sheep, due to progressing anthelmintic resistance (AR), calls for an enhanced and standardized implementation of early detection of AR. This study provides a snapshot of the current AR status against benzimidazoles and macrocyclic lactones in southern Italy, generated with standardized techniques. Methods On 10 sheep farms, the efficacy of albendazole (ALB) and either eprinomectin (EPR) or ivermectin (IVM) was evaluated based on the faecal egg count reduction test (FECRT) performed with the Mini-FLOTAC. For each tested drug, 40 sheep were rectally sampled at D0 and sampled again 14 days after the treatment (D14). The FECRT was calculated from individual samples and pooled samples which consist of 5 individual samples. Efficacy was classified as ‘reduced, ‘suspected’ and ‘normal’. Coprocultures were set for D0 and D14 faecal samples of each group. From farms with FECR < 95%, an in vitro egg hatch test (EHT) and a follow-up FECRT using fenbendazole (FBZ) were conducted. Results Based on the FECR, high efficacy (from 95.7% to 100%) was observed for ALB and IVM in eight farms (Farms 3–10). On Farm 1 and Farm 2, the efficacy for the macrocyclic lactones was classified as ‘normal’, but ‘reduced’ efficacy was observed for ALB on Farm 1 (FECR = 75%) and ‘suspected’ efficacy on Farm 2 (FECR = 93.3%) with the predominant GIN genus Trichostrongylus followed by Haemonchus at D14. The FEC results of pooled samples strongly correlated with those of individual samples, for FEC at D0 ( r s = 0.984; P < 0.0001) and at D14 ( rs = 0.913; P < 0.0001). The classifications of efficacy in Farm 1 (FECR = 86.0%) and Farm 2 (FECR = 93.0%) in the follow-up FECRT with FBZ coincide with the main FECRT trial. The in vitro EHT confirmed AR in both farms (Farm 1: 89%; Farm 2: 74%). Conclusions In regions like southern Italy, where the negative impacts from AR have played a minor role, efficient monitoring of AR is important in order to evaluate potential risks and being able to promptly respond with countermeasures.

Soil-transmitted helminths infect about one fifth of the world's population and have a negative impact on health. The Kato-Katz technique is the recommended method to detect soil-transmitted helminth eggs in stool samples, particularly in programmatic settings. However, some questions in its procedure remain. Our study aimed to investigate the effect of storage time, storage temperature and stirring of stool samples on fecal egg counts (FECs). In the framework of a clinical trial on Pemba Island, United Republic of Tanzania, 488 stool samples were collected from schoolchildren. These samples were evaluated in three experiments. In the first experiment (n = 92), two Kato-Katz slides were prepared from the same stool sample, one was stored at room temperature, the other in a refrigerator for 50 hours, and each slide was analyzed at nine time points (20, 50, 80, 110, 140 minutes, 18, 26, 42 and 50 hours). In the second experiment (n = 340), whole stool samples were split into two, one part was stored at room temperature, and the other part was put in a refrigerator for 48 hours. From each part one Kato-Katz slide was prepared and analyzed at three time points over two days (0, 24 and 48 hours). In the third experiment (n = 56), whole stool samples where stirred for 15 seconds six times and at each time point a Kato-Katz slide was prepared and analyzed. Mean hookworm FECs of Kato-Katz slides stored at room temperature steadily decreased following slide preparation. After two hours, mean hookworm FECs decreased from 22 to 16, whereas no reduction was observed if Kato-Katz slides were stored in the refrigerator (19 vs 21). The time x storage interaction effect was statistically significant (coefficient 0.26, 95% CI: 0.17 to 0.35, p < 0.0001). After 24 hours mean hookworm FECs dropped close to zero, irrespective of the storage condition. Whole stool samples stored at room temperature for one day resulted in a mean hookworm FEC decrease of 23% (p < 0.0001), compared to a 13% reduction (p < 0.0001) if samples were stored in the refrigerator. Fecal egg counts of A. lumbricoides and T. trichiura remained stable over time regardless of storage temperature of whole stool samples. Finally, we found a significant reduction of the variation of hookworm and T. trichiura eggs with increasing rounds of stirring the sample, but not for A. lumbricoides. For hookworm we observed a simultaneous decrease in mean FECs, making it difficult to draw recommendations on stirring samples. Our findings suggest that stool samples (i) should be analyzed on the day of collection and (ii) should be analyzed between 20-30 minutes after slide preparation; if that is not possible, Kato-Katz slides can be stored in a refrigerator for a maximum of 110 minutes.

Because the success of deworming programs targeting soil-transmitted helminths (STHs) is evaluated through the periodically assessment of prevalence and infection intensities, the use of the correct diagnostic method is of utmost importance. The STH community has recently published for each phase of a deworming program the minimal criteria that a potential diagnostic method needs to meet, the so-called target product profiles (TPPs). We compared the diagnostic performance of a single Kato-Katz (reference method) with that of other microscopy-based methods (duplicate Kato-Katz, Mini-FLOTAC and FECPAKG2) and one DNA-based method (qPCR) for the detection and quantification of STH infections in three drug efficacy trials in Ethiopia, Lao PDR, and Tanzania. Furthermore, we evaluated a selection of minimal diagnostic criteria of the TPPs. All diagnostic methods showed a clinical sensitivity of ≥90% for all STH infections of moderate-to-heavy intensities. For infections of very low intensity, only qPCR resulted in a sensitivity that was superior to a single Kato-Katz for all STHs. Compared to the reference method, both Mini-FLOTAC and FECPAKG2 resulted in significantly lower fecal egg counts for some STHs, leading to a substantial underestimation of the infection intensity. For qPCR, there was a positive significant correlation between the egg counts of a single Kato-Katz and the DNA concentration. Our results indicate that the diagnostic performance of a single Kato-Katz is underestimated by the community and that diagnostic specific thresholds to classify intensity of infection are warranted for Mini-FLOTAC, FECPAKG2 and qPCR. When we strictly apply the TPPs, Kato-Katz is the only microscopy-based method that meets the minimal diagnostic criteria for application in the planning, monitoring and evaluation phase of an STH program. qPCR is the only method that could be considered in the phase that aims to seek confirmation for cessation of program. ClinicalTrials.gov NCT03465488.

Chicken production has increased over the past decade, resulting in a concomitant rise in the demand for more humane options for poultry products including cage-free, free-range, and organic meat and eggs. These husbandry changes, however, have come hand-in-hand with increased prevalence of Ascaridia galli infection, which can cause clinical disease in chickens as well as the occasional appearance of worms in eggs. Additionally, development of anthelmintic resistance in closely related helminths of turkeys highlights the need for closely monitored anthelmintic treatment programs. Manual faecal egg counts (FECs) can be time-consuming and require specialist training. As such, this study sought to validate an automated FEC system for use in detection and quantification of A. galli eggs in chicken faeces. Automated counts using the Parasight System (PS) were compared to traditional manual McMaster counting for both precision and correlation between methods. Overall, ten repeated counts were performed on twenty individual samples for a total of 200 counts performed for each method. A strong, statistically significant correlation was found between methods (R2 = 0.7879, P < 0.0001), and PS counted more eggs and performed with statistically significant higher precision (P = 0.0391) than manual McMaster counting. This study suggests that PS is a good alternative method for performing A. galli FECs and provides a new tool for use in helminth treatment and control programs in chicken operations.

Background Faecal egg counts (FECs) are essential for diagnosing helminth infections and guiding treatment decisions. For camels, no evaluations of coproscopic methods regarding precision, sensitivity and correlation between individual and pooled faecal samples are currently available. Methods Here, 410 camel faecal samples were collected in 2022 from South Darfur State, Sudan, and analysed to compare the semi-quantitative flotation, McMaster and Mini-FLOTAC methods in terms of precision, sensitivity, inter-rater reliability and helminth egg count correlations, as well as the effects of pooling samples. Six samples were used to assess precision for McMaster and Mini-FLOTAC, while the remaining 404 samples were evaluated for sensitivity, inter-rater reliability and egg count correlations. Of these, 80 samples were used in pooling experiments. Results Six analyses of each sample ( n  = 6) using the McMaster and Mini-FLOTAC methods revealed no significant difference in the coefficient of variation between the two. For strongyle eggs, 48.8%, 52.7% and 68.6% were positive for McMaster, semi-quantitative flotation and Mini-FLOTAC, respectively. The sensitivity of the three methods showed only minimal improvement when three egg counts were performed on the same sample. McMaster and Mini-FLOTAC had similar sensitivity for Strongyloides spp. (3.5% frequency), while it was lower for semi-quantitative flotation at 2.5%. Mini-FLOTAC was more sensitive for Moniezia spp., detecting 7.7% of positives compared with 4.5% for semi-quantitative flotation and 2.2% for McMaster. For Trichuris spp., frequencies were 0.3% with Mini-FLOTAC, 0.7% with McMaster and 1.7% with semi-quantitative flotation. Mini-FLOTAC also detected higher strongyle eggs per gram (EPG) of faeces (mean 537.4) compared with McMaster (330.1). More samples exceeded treatment thresholds with Mini-FLOTAC, with 28.5% of animals having EPG ≥ 200 compared with 19.3% for McMaster, while 19.1% showed EPG ≥ 500 with Mini-FLOTAC compared with 12.1% with McMaster. There was no significant correlation between individual and pooled strongyle FECs, as indicated by Pearson correlation coefficients of r  ≥ 0.368 ( P  ≥ 0.113) and Spearman correlation. Conclusions Mini-FLOTAC outperformed semi-quantitative flotation and McMaster in diagnosing helminth infections in camels, offering greater sensitivity and detecting higher EPGs, particularly for strongyles, Strongyloides spp. and Moniezia spp. Thus, treatment decisions based on Mini-FLOTAC EPGs will lead to more treatments. Graphical Abstract

Background  Digital imaging combined with deep-learning-based computational image analysis is a growing area in medical diagnostics, including parasitology, where a number of automated analytical devices have been developed and are available for use in clinical practice. Methods The performance of Parasight All-in-One (AIO), a second-generation device, was evaluated by comparing it to a well-accepted research method (mini-FLOTAC) and to another commercially available test (Imagyst). Fifty-nine canine and feline infected fecal specimens were quantitatively analyzed by all three methods. Since some samples were positive for more than one parasite, the dataset consisted of 48 specimens positive for Ancylostoma spp., 13 for Toxocara spp. and 23 for Trichuris spp. Results The magnitude of Parasight AIO counts correlated well with those of mini-FLOTAC but not with those of Imagyst. Parasight AIO counted approximately 3.5-fold more ova of Ancylostoma spp. and Trichuris spp. and 4.6-fold more ova of Toxocara spp. than the mini-FLOTAC, and counted 27.9-, 17.1- and 10.2-fold more of these same ova than Imagyst, respectively. These differences translated into differences between the test sensitivities at low egg count levels (< 50 eggs/g), with Parasight AIO > mini-FLOTAC > Imagyst. At higher egg counts Parasight AIO and mini-FLOTAC performed with comparable precision (which was significantly higher that than Imagyst), whereas at lower counts (> 30 eggs/g) Parasight was more precise than both mini-FLOTAC and Imagyst, while the latter two methods did not significantly differ from each other. Conclusions In general, Parasight AIO analyses were both more precise and sensitive than mini-FLOTAC and Imagyst and quantitatively correlated well with mini-FLOTAC. While Parasight AIO produced lower raw counts in eggs-per-gram than mini-FLOTAC, these could be corrected using the data generated from these correlations. Graphical Abstract

Background Current methods for obtaining fecal egg counts in horses are often inaccurate and variable depending on the analyst’s skill and experience. Automated digital scanning of fecal sample slides integrated with analysis by an artificial intelligence (AI) algorithm is a viable, emerging alternative that can mitigate operator variation compared to conventional methods in companion animal fecal parasite diagnostics. Vetscan Imagyst is a novel fecal parasite detection system that uploads the scanned image to the cloud where proprietary software analyzes captured images for diagnostic recognition by a deep learning, object detection AI algorithm. The study describes the use and validation of Vetscan Imagyst in equine parasitology. Methods The primary objective of the study was to evaluate the performance of the Vetscan Imagyst system in terms of diagnostic sensitivity and specificity in testing equine fecal samples ( n  = 108) for ova from two parasites that commonly infect horses, strongyles and Parascaris spp., compared to reference assays performed by expert parasitologists using a Mini-FLOTAC technique. Two different fecal flotation solutions were used to prepare the sample slides, NaNO 3 and Sheather’s sugar solution. Results Diagnostic sensitivity of the Vetscan Imagyst algorithm for strongyles versus the manual reference test was 99.2% for samples prepared with NaNO 3 solution and 100.0% for samples prepared with Sheather’s sugar solution. Sensitivity for Parascaris spp. was 88.9% and 99.9%, respectively, for samples prepared with NaNO 3 and Sheather’s sugar solutions. Diagnostic specificity for strongyles was 91.4% and 99.9%, respectively, for samples prepared with NaNO 3 and Sheather’s sugar solutions. Specificity for Parascaris spp. was 93.6% and 99.9%, respectively, for samples prepared with NaNO 3 and Sheather’s sugar solutions. Lin’s concordance correlation coefficients for VETSCAN IMAGYST eggs per gram counts versus those determined by the expert parasitologist were 0.924–0.978 for strongyles and 0.944–0.955 for Parascaris spp., depending on the flotation solution. Conclusions Sensitivity and specificity results for detecting strongyles and Parascaris spp. in equine fecal samples showed that Vetscan Imagyst can consistently provide diagnostic accuracy equivalent to manual evaluations by skilled parasitologists. As an automated method driven by a deep learning AI algorithm, VETSCAN IMAGYST has the potential to avoid variations in analyst characteristics, thus providing more consistent results in a timely manner, in either clinical or laboratory settings. Graphical Abstract

Infections by gastrointestinal parasites are found in a variety of animals worldwide. For the diagnosis of such infections, the flotation method is commonly used to detect parasitic microorganisms, such as oocysts or eggs, in feces. Instead of adding a flotation solution after the final centrifugation step and using a cover slip to collect the parasites, the method using a wire loop for the recovery of the organisms has been reported as one of alternative methods. However, the recovery rates of microorganisms from the flotation method have not been analysed. In the present study, the utility of a flotation method with the use of a wire loop of 8 mm in diameter (the loop method) was evaluated using different numbers of E. tenella oocysts and Heterakis gallinarum eggs, and chicken fecal samples collected at the farms. Consequently, we found that the oocysts and eggs in tubes could be collected at a ratio of 2.00 to 3.08. Thus, our results indicate that the loop method is a simple and time saving method, implicating the application for the estimated OPG/ EPG (Oocysts/Eggs per gram) of the samples. Graphical ► Utility of a flotation method with the use of a wire loop of 8 mm in diameter was evaluated. ► E. tenella oocysts and Heterakis gallinarum eggs in tubes could be collected at a ratio of 2.00 to 3.08. ► Our results may implicate the application for the estimated OPG/ EPG of the samples as a simple and time saving method.

Background Intestinal parasitic infections are still a serious public health problem in developing countries, and the diagnosis of parasitic infections requires the first step of parasite/egg detection of samples. Automated detection can eliminate the dependence on professionals, but the current detection algorithms require large computational resources, which increases the lower limit of automated detection. Therefore, we have designed a lightweight deep-learning model, YAC-Net, to achieve rapid and accurate detection of parasitic eggs and reduce the cost of automation. Methods This paper uses the ICIP 2022 Challenge dataset for experiments, and the experiments are conducted using fivefold cross-validation. The YOLOv5n model is used as the baseline model, and then two improvements are made to the baseline model based on the specificity of the egg data. First, the neck of the YOLOv5n is modified to from a feature pyramid network (FPN) to an asymptotic feature pyramid network (AFPN) structure. Different from the FPN structure, which mainly integrates semantic feature information at adjacent levels, the hierarchical and asymptotic aggregation structure of AFPN can fully fuse the spatial contextual information of egg images, and its adaptive spatial feature fusion mode can help the model select beneficial feature and ignore redundant information, thereby reducing computational complexity and improving detection performance. Second, the C3 module of the backbone of the YOLOv5n is modified to a C2f module, which can enrich gradient information, improving the feature extraction capability of the backbone. Moreover, ablation studies are designed by us to verify the effectiveness of the AFPN and C2f modules in the process of model lightweighting. Results The experimental results show that compared with YOLOv5n, YAC-Net improves precision by 1.1%, recall by 2.8%, the F1 score by 0.0195, and mAP_0.5 by 0.0271 and reduces the parameters by one-fifth. Compared with some state-of-the-art detection methods, YAC-Net achieves the best performance in precision, F1 score, mAP_0.5, and parameters. The precision, recall, F1 score, mAP_0.5, and parameters of our method on the test set are 97.8%, 97.7%, 0.9773, 0.9913, and 1,924,302, respectively. Conclusions Compared with the baseline model, YAC-Net optimizes the model structure and simplifies the parameters while ensuring the detection performance. It helps to reduce the equipment requirements for performing automated detection and can be used to realize the automatic detection of parasite eggs under microscope images. Graphical Abstract

Conventional microscopy of Kato-Katz (KK1.0) thick smears, the primary method for diagnosing soil-transmitted helminth (STH) infections, has limited sensitivity and is error-prone. Artificial intelligence-based digital pathology (AI-DP) may overcome the constraints of traditional microscopy-based diagnostics. This study in Ucayali, a remote Amazonian region of Peru, compares the performance of AI-DP-based Kato-Katz (KK2.0) method to KK1.0 at diagnosing STH infections in school-aged children (SAC). In this prospective, non-interventional study, 510 stool samples from SAC (aged 5-14 years) were analyzed using KK1.0, KK2.0, and tube spontaneous sedimentation technique (TSET). KK1.0 and KK2.0 slides were evaluated at 30-minute and 24-hour timepoints for detection of Ascaris lumbricoides, Trichuris trichiura, and hookworms (at 30-minute only). Diagnostic performance was assessed by measuring STH eggs per gram of stool (EPG), sensitivity of methods, and agreement between the methods. KK2.0 detected more A. lumbricoides positive samples than KK1.0, with detection rates for T. trichiura and hookworms being comparable. At 30-minutes, 37.6%, 23.0%, and 2.6% of the samples tested positive based on KK1.0 for A. lumbricoides, T. trichiura, and hookworms, while this was 49.8%, 24.4%, and 1.9% for KK2.0. At 24-hours, 37.1% and 27.1% of the samples tested positive based on KK1.0 for A. lumbricoides and T. trichiura, while this was 45.8% and 24.1% for KK2.0. Mean EPG between KK2.0 and KK1.0 were not statistically different across STH species and timepoints, except for T. trichiura at 24-hours (higher mean EPG for KK1.0, p = 0.036). When considering infection intensity levels, KK2.0 identified 10% more of the total population as low-infection intensity samples of A. lumbricoides than KK1.0 (p ≤ 0.001, both timepoints) and similar to KK1.0 for T. trichiura and hookworms. Varying agreement existed between KK1.0 and KK2.0 in detecting STH eggs (A. lumbricoides: moderate; T. trichiura: substantial; hookworms: slight). However, these findings should be interpreted carefully as there are certain limitations that may have impacted the results of this study. This study demonstrates the potential of the AI-DP-based method for STH diagnosis. While similar to KK1.0, the AI-DP-based method outperforms it in certain aspects. These findings underscore the potential of advancing the AI-DP KK2.0 prototype for dependable STH diagnosis and furthering the development of automated digital microscopes in accordance with WHO guidelines for STH diagnosis.