High-throughput detection of parasites and ova in stool using the fully automatic digital feces analyzer, orienter model fa280.

BACKGROUND: Intestinal parasitic infections can harm health by causing malnutrition, anemia, impaired growth and cognitive development, and alterations in microbiota composition and immune responses. Therefore, it is crucial to examine stool samples to diagnose parasitic infections. However, the traditional microscopic detection method is time-consuming, labor-intensive, and dependent on the expertise and training of microscopists. Hence, there is a need for a low-complexity, high-throughput, and cost-effective alternative to labor-intensive microscopic examinations. METHODS: This study aimed to compare the performance of a fully automatic digital feces analyzer, Orienter Model FA280 (People's Republic of China) with that of the formalin-ethyl acetate concentration technique (FECT). We assessed and compared the agreement between the FA280 and the FECT for parasite detection and species identification in stool samples. The first part of the study analyzed 200 fresh stool samples for parasite detection using the FECT and FA280. With the FA280, the automatic feces analyzer performed the testing, and the digital microscope images were uploaded and automatically evaluated using an artificial intelligence (AI) program. Additionally, a skilled medical technologist conducted a user audit of the FA280 findings. The second set of samples comprised 800 preserved stool samples (preserved in 10% formalin). These samples were examined for parasites using the FECT and FA280 with a user audit. RESULTS: For the first set of stool samples, there was no statistically significant difference in the pairwise agreements between the FECT and the FA280 with a user audit (exact binomial test, P = 1). However, there were statistically significant differences between the pairwise agreements for the FECT and the FA280 with the AI report (McNemar's test, P < 0.001). The agreement for the species identification of parasites between the FA280 with AI report and FECT showed fair agreement (overall agreement = 75.5%, kappa [κ] = 0.367, 95% CI 0.248-0.486). On the other hand, the user audit for the FA280 and FECT showed perfect agreement (overall agreement = 100%, κ = 1.00, 95% CI 1.00-1.00). For the second set of samples, the FECT detected significantly more positive samples for parasites than the FA280 with a user audit (McNemar's test, P < 0.001). The disparity in results may be attributed to the FECT using significantly larger stool samples than those used by the FA280. The larger sample size used by the FECT potentially contributed to the higher parasite detection rate. Regarding species identification, there was strong agreement between the FECT and the FA280 with a user audit for helminths (κ = 0.857, 95% CI 0.82-0.894). Similarly, there was perfect agreement for the species identification of protozoa between the FECT and the FA280 with user audit (κ = 1.00, 95% CI 1.00-1.00). CONCLUSIONS: Although the FA280 has advantages in terms of simplicity, shorter performance time, and reduced contamination in the laboratory, there are some limitations to consider. These include a higher cost per sample testing and a lower sensitivity compared to the FECT. However, the FA280 enables rapid, convenient, and safe stool examination of parasitic infections.

Declaration of nutrition information on and nutritional quality of Thai ready-to-eat packaged food products.

OBJECTIVE: The present study assessed the nutrition information displayed on ready-to-eat packaged foods and the nutritional quality of those food products in Thailand. DESIGN: In March 2015, the nutrition information panels and nutrition and health claims on ready-to-eat packaged foods were collected from the biggest store of each of the twelve major retailers, using protocols developed by the International Network for Food and Obesity/Non-communicable Diseases Research, Monitoring and Action Support (INFORMAS). The Thai Nutrient Profile Model was used to classify food products according to their nutritional quality as 'healthier' or 'less healthy'. RESULTS: In total, information from 7205 food products was collected across five broad food categories. Out of those products, 5707 (79·2 %), 2536 (35·2 %) and 1487 (20·6 %) carried a nutrition facts panel, a Guideline Daily Amount (GDA) label and health-related claims, respectively. Only 4691 (65·1 %) and 2484 (34·5 %) of the products that displayed the nutrition facts or a GDA label, respectively, followed the guidelines of the Thai Food and Drug Administration. In total, 4689 products (65·1 %) could be classified according to the Thai Nutrient Profile Model, of which 432 products (9·2 %) were classified as healthier. Moreover, among the 1487 products carrying health-related claims, 1219 (82·0 %) were classified as less healthy. Allowing less healthy food products to carry claims could mislead consumers and result in overconsumption of ready-to-eat food products. CONCLUSIONS: The findings suggest effective policies should be implemented to increase the relative availability of healthier ready-to-eat packaged foods, as well as to improve the provision of nutrition information on labels in Thailand.