Sarcoptic mange is the clinical disease caused by the burrowing mite Sarcoptes scabiei, an obligate ectoparasitic arthropod responsible for significant morbidity in both domestic and wild animals. The aim of the study was to investigate the serological prevalence of S. scabiei var. suis in pigs raised in the intensive system in Lombardy region, one of the most suitable regions in northern Italy for intensive pig farming, and to assess the influence of variables related to farm management on the exposure to mite infestation. 219 fattening pigs and 151 sows from 23 conventional farms in Lombardy were sampled; data on farm management were collected, and a biosecurity score was determined for each farm. Blood samples were analysed using a commercial indirect ELISA Kit; generalized linear models were developed to determine the influence of production category and sanitary score on the parasite infestation. At the farm level, 65.2% (15/23) of the selected farms were positive, i.e. 90.9% of those housing sows and 40% fattening pigs. At the individual level, 43 animals (43/370, Prevalence (P%) = 11.6%) were positive to S. scabiei antibodies with higher seroprevalence values in sows (35/151, P = 23.2%) if compared to fattening pigs (8/219, P = 3.6%). A higher seroprevalence was recorded in farms with poor or moderate scores (P = 100% and P = 64.3%, respectively) if compared to those with higher sanitary score (P = 44.4%). Statistical analysis revealed that production category and biosecurity score were significantly associated with the mite infestation. Sarcoptic mange can lead to significant economic losses in pig farming; besides, the zoonotic risk for human infestation due to handling of pig or carcasses should be considered.

Caryophyllidean tapeworms (Cestoda) are widespread parasites of suckers (Catostomidae) in North America, but their phylogenetic relationships remain poorly understood. This study presents molecular data on species of the recently established genus Pseudoglaridacris Oros, Uhrovič et Scholz, 2018. The type species, P. laruei (Lamont 1921), a very common parasite of the white sucker Catostomus commersonii (Catostomidae) in North America, is characterised both molecularly and morphologically based on recently collected, properly fixed specimens from the type host (C. commersonii) and four species of redhorse (Moxostoma spp.), including new host and geographical records from Canada and the United States. Pseudoglaridacris laruei differs from other species in the genus by its size, being the largest species (body length up to 12.7 mm), a high number of testes (62–119) and very few (0–6) postovarian vitelline follicles. Mackiewiczus etowanum from Hypentelium etowanum and Mackiewiczus rarus from Moxostoma poecilurum in Alabama are nomina nuda. The taxonomic status of P. confusa (Hunter 1929), which occurs in ictiobines, and of P. oligorchis (Haderlie 1953), which is most probably a junior synonym of P. laruei with a reduced number of testes, is also discussed, based on molecular data indicating the presence of a putative new species from ictiobines that has not yet been described.

Enterocytozoon bieneusi is the most frequently detected microsporidian in humans and infects a wide range of animals. Data integrating human, animal, and environmental compartments under a One Health framework remains scarce. We conducted a molecular survey in a rural area of Adana Province, south-central Türkiye (October–November 2023). A total of 394 samples were screened, including stool from apparently healthy individuals (n = 124) from 64 households and livestock such as cattle (n = 75), sheep (n = 95), goats (n = 60) and environmental samples (lake water, n = 24; mud, n = 16). Detection and genotyping targeted the Internal Transcribed Spacer (ITS) region by nested PCR and Sanger sequencing. No human or environmental samples were positive, this result may be influenced by sampling limitations, seasonality, and methodological sensitivity rather than reflecting true absence. Overall E. bieneusi prevalence in livestock was 5.2% (12/230; 95% CI, 2.6–8.6). By host, prevalence was 8.4% in sheep (8/95; 95% CI, 3.7–15.9), 3.3% in goats (2/60; 95% CI, 0.4–11.5), and 2.7% in cattle (2/75; 95% CI, 0.3–9.3); differences were not statistically significant. Sequence analysis identified three known genotypes: BEB6 (6/12), J (1/12), and Type IV (1/12), and two novel genotypes (ShTrEb1, ShTrEb2; 2/12 each). J and Type IV were restricted to cattle; BEB6 and ShTrEb1 occurred in sheep and goats; ShTrEb2 was detected only in sheep. Phylogenetic analysis placed Type IV in Group 1 and BEB6, J, ShTrEb1, and ShTrEb2 in Group 2. Although humans and environmental matrices tested negative in this study, the detection of genotypes in livestock should be interpreted carefully and highlights the need for further studies to clarify potential transmission pathways. Larger, seasonally stratified surveys with standardized environmental methods are warranted to better understand regional transmission dynamics.

Despite remarkable progress in global health and increased life expectancy in the 21st century, malaria remains a major parasitic disease-causing significant morbidity and mortality, particularly in sub-Saharan Africa and Southeast Asia. Traditional diagnostic methods such as rapid diagnostic tests (RDTs) and microscopy, though widely used, suffer from limitations including biomarker mutations, reduced sensitivity at low parasite counts, and operator dependency. These challenges underscore the need for intelligent, automated diagnostic solutions. Artificial intelligence (AI)-driven computer vision methods, especially deep learning (DL)-enabled object detection architectures, offer promising alternatives for automated parasite identification. This study aims to perform a comparative evaluation of YOLO variants (v3, cascade v3, scaled v4, v5, and v8) to determine the most suitable architecture for precise and efficient detection of malaria. The models were assessed with following parameters such as, precision, accuracy, F1-score, recall and mean Average Precision (mAP). This study proposes a novel DL framework that combines YOLOv3 with a modified MobileNetV2 backbone, augmented by a Transformed Convolutional Layer (TCL)exhibits multi-scale texture sensitivity and efficient feature extraction, making it particularly effective for analyzing dense thick smear images of Plasmodium vivax (P. vivax).These findings provide guidance for deploying AI-based malaria diagnostic tools across varied clinical and field settings.This approach aims to contribute toward developing a robust, scalable, and interpretable diagnostic framework for early malaria detection and improved disease management.

This study aimed to assess the efficacy of pyrethroid-based insecticides against Gasterophilus spp. egg-laying activity and to establish the seasonality patterns in the specific climatic area of Transylvania, Romania. To fulfil the aims of the study, a total of 40 horses were treated every 4weeks and inspected every 2weeks between 11 May and 6 November (Pilo et al. Parasitol Res 114:1693-1702,2024). Through this period, eggs were found between 24 June and 2 November. The eggs were found on 34 out of 40 horses (prevalence = 85%, CI 95% = 73.43-96.56%). Overall, a total of 50,029 Gasterophilus spp. eggs were counted during this study, and all were morphologically identified as G. intestinalis. Statistical analysis revealed no significant difference in prevalence and intensity between treated and control horses (p > 0.05). The number of laid eggs varied significantly across body regions (p < 0.05). The risk factors associated with increased egg-laying activity were significantly (p < 0.05) associated with dark-color coats, outside husbandry regime, and the month of exposure. No significant differences in egg numbers and prevalence were found across gender or age groups (p > 0.05). The applied statistical tests were as follows: the non-parametric Mann-Whitney U test, the Friedman test, Wilcoxon test corrected by the Bonferroni method, the Kruskal-Wallis test, and the Bonferroni correction for multiple comparisons. These results highlight gasterophilosis as an important parasite in horses. In conclusion, we recommend that, in order maintain a low prevalence of Gasterophilus spp., treatment should include the use of larvicidal drugs and the mechanical removal of the eggs.

Zoonotic helminths are responsible for the majority of helminthic infections occurring in humans globally. Environmental systems serve as a reservoir for zoonotic helminths, facilitating their transmission to humans and animals. Livestock farms may serve as hotspots for zoonotic transmission, increasing infection risk. Focusing on goat farms in Ratchaburi Province, Thailand, we aim to detect and identify zoonotic helminths present in the soil environment through morphological and molecular techniques. Soil samples (n = 270) were collected from 30 goat farms in Ratchaburi Province, and helminths were morphologically identified using a modified sedimentation and flotation method. Helminths were then molecularly identified using the nuclear 18S rRNA gene and the internal transcribed spacer 2 region. The helminths identified include human, livestock-parasitic nematodes, trematodes, cestodes, plant-parasitic nematodes, insect-parasitic nematodes, and free-living nematodes. Morphological and molecular detection show that 80% and 86% of the farms were positive for helminths, respectively. From 30 farms, 60% were positive for livestock- or human-parasitic helminths, with eight species detected. Moreover, 50% of farms were positive for either Haemonchus contortus or Trichostrongylus colubriformis. Utilizing soil as a non-invasive method for the detection and identification of helminths contaminated in the soil, this study demonstrated the presence of human- and animal-parasitic helminths with the soil matrix serving as a shared environment and reservoir for zoonotic transmission of helminthic infection, further emphasizing the importance of the One Health approach towards mitigating parasitic disease transmission. The findings showed significant implications for the incorporation of soil-based methods into sustainable helminth infection control programs.

Fasciola spp. infection is a significant zoonotic disease. Fasciola gigantica cathepsin L1H (FgCathL1H) is expressed across the life stages of Fasciola gigantica: newly excysted juvenile (NEJ), juvenile, and adult. An emerging tool for diagnosing fasciolosis in humans and cattle involves single-chain variable fragments (scFv) antibodies. These antibodies, consisting of linked variable regions of heavy chains (VHs) and light chains (VLs), retain binding specificity and affinity. This study aims to construct, express, and characterize an scFv antibody for use in a diagnostic kit for fasciolosis. The study successfully constructed and expressed recombinant scFv antibody genes derived from mouse spleen cells in Escherichia coli HB2151. Specific VH and VL fragments targeting recombinant FgCathL1H were amplified, inserted into a phagemid vector (pCANTAB5E), and transformed into E. coli TG1. Infection with the M13KO7 helper phage produced recombinant phages, and scFv clones with a high binding capacity were selected through three rounds of bio-panning. The expression of scFv proteins was induced with 1 mM IPTG, yielding antibodies detectable in the culture supernatant and periplasmic space. The indirect ELISA revealed strong binding in 10 scFv phage clones, which were sequenced and analyzed via computer-guided homology modeling and showed a similar classification to CDR1–3, consisting of VHs and VLs. The scFv DNA construct was approximately 747 bp in length. The SDS-PAGE, ELISA, and western blot confirmed the specificity of the scFv clone 1B, particularly at ~ 29 kDa. Docking studies showed epitopes on the scFv interacting with FgCathL1H. This scFv reacted specifically with F. gigantica antigens at 36 kDa (whole body (WB) of metacercaria and NEJ) and ~ 28 kDa (WB of 4-week-old juveniles and adults, and adult excretory–secretory protein (ES)). Immunolocalization showed positive staining in the cecal epithelium. Thus, scFv anti-rFgCathL1H shows promise for diagnosing fasciolosis.