Animals

Effective animal monitoring is essential for assessing health, behavior, and environmental interactions, particularly in research and welfare contexts. This study presents a low-cost, open-source system designed for non-invasive monitoring of budgerigars (Melopsittacus undulatus), a small parrot species frequently used in animal behavior research. The system integrates a perch-based scale for voluntary weight measurement, a temperature sensor, and a camera for image capture, all controlled by a Raspberry Pi. By leveraging fine-tuned neural networks, the system achieves automated individual recognition with high accuracy, eliminating the need for invasive tagging methods. The modular design ensures accessibility, scalability, and minimal disturbance to the animals, while the accompanying software streamlines data collection, processing including labeling, and visualization. This approach provides a comprehensive solution for continuous monitoring, offering valuable insights for research and husbandry while prioritizing animal welfare.

Recent advances in animal training increasingly emphasize welfare, positive experience and the reduction of stress. In the equine sector, however, such progress is complicated by the horse s dual role as both companion and performance animal. This study investigated whether an assent based training approach (ABT) has an effect on horse behavior and human-horse interaction quality compared to traditional equine training (TET) based on pressure and release. Two groups of horse-owner pairs (ABT and TET) participated in two behavioral tests. A stroking session evaluated horses' responses to human tactile interaction, while an obstacle path assessed horses' exploration of novel objects and refusal behaviors. Behavioral measures of exploration, avoidance, and owner-directed behaviors were analyzed alongside horse personality traits. A newly validated questionnaire was used to gather demography information, training habits and horse personality traits. During the stroking session, ABT horses displayed more positive human-directed behaviors, reflecting active engagement rather than passive tolerance. Sociability was associated with the overall frequency of human-directed behaviors, but did not predict their positive valence, which was instead linked to ABT training style. Horses trained mainly with ABT explored obstacles more and showed fewer refusal behaviors than traditionally trained horses, independently of anxiety traits derived from personality scores. These findings suggest that assent-based training practices are associated with increased confidence and cooperative engagement in horses, supporting the potential of agency oriented approaches to enhance both equine welfare and human-horse interaction quality.

The study of animal personality has gained increasing attention in recent years, as researchers recognize that non-human animals exhibit stable individual differences in behaviour. In dairy cattle, understanding personality traits holds potential for improving animal welfare, enhancing management practices, and supporting productivity outcomes. However, validating the behavioural tests used to assess these traits remains a significant challenge. The present study aimed to evaluate the consistency and validity of five commonly used behavioural tests in dairy cows: the Human Approach Test (HAT), Sudden Test (SUD), Novel Object Test (NOT), Open Field Test (OFT), and Novel Surface Test (NST). These tests were chosen for their potential to assess personality dimensions that parallel components of human personality, particularly Openness, Neuroticism, Extraversion, and Agreeableness. Repeated assessments were conducted across three time periods to evaluate both intra-test (temporal) and inter-test (contextual) consistency. Results revealed that only the SUD exhibited significant behavioural consistency across all periods, suggesting its potential as a reliable tool for personality assessment. Additionally, a moderate correlation between the HAT and SUD was observed, indicating that these tests may capture overlapping personality traits. In contrast, the remaining tests (NOT, OFT, NST) lacked consistent behavioural patterns over time and across contexts, raising questions about their reliability and the complexity of trait expression. These findings highlight the challenges of identifying stable personality traits in cattle and emphasize the need for more rigorous validation of behavioural tests. This research contributes to the growing field of animal personality by providing insights into trait stability, the limitations of current testing methods, and the potential application of personality assessment in future livestock management practices.

Object detection models based on deep learning are increasingly used to reduce the manual workload associated with the processing of video recordings in behavioural research, but reproducible workflows describing how ecologists can build such models themselves remain scarce. Here, we present a step-by-step workflow for constructing a species-specific detection model and apply it as a case study to the red-legged seriema (Cariama cristata), a widely distributed but poorly studied Neotropical bird. Using 60 videos recorded with camera traps as well as non-stop recording cameras at the campus of the Universidade Federal de Vicosa (Florestal, Minas Gerais, Brazil) between 2023 and 2026, we extracted and annotated 480 images to train a YOLO26-nano detection model. On the validation set, the model achieved a precision of 0.934 and a recall of 0.786 (mAP@50 = 0.870), while performance on the independent test set was slightly lower, with a precision of 0.865 and a recall of 0.740 (mAP@50 = 0.740). When applied to unseen footage, the model processed video at roughly 4.6 times real-time speed on a standard CPU and correctly classified all four test videos for the presence or absence of seriemas. Most missed detections involved seriemas that were distant, partially out of frame, or recorded with the lower-quality non-stop cameras. These results showed that a usable detection model can be built from a comparatively small curated dataset, and the accompanying workflow and code are intended to lower the barrier for ecologists seeking to apply object detection to their own study species.

Background: The yak (Bos grunniens) is an essential livestock species in high-altitude alpine ecosystems, serving key roles in meat, milk, and wool production as well as ecological maintenance. However, traditional yak breeding systems face several limitations, including fragmented herd data management, inefficient phenotypic collection, missing pedigree records, and high technical barriers to applying genomic technologies. These factors constrain the widespread application of modern genetic evaluation methods in yak breeding programs. Description: We developed the Yak Genomic Evaluation Platform (YGEP, https://yakbreeding.swun.edu.cn/en/), an integrated digital system for yak genetic selection and herd management. YGEP integrates three core analytical modules: pedigree reconstruction, genotype imputation and genomic breeding value estimation. Benchmarking on 706 yaks showed that GBLUP achieved a prediction accuracy of r = 0.96 for cannon bone circumference (CCB), and KBeagle reached 84.0% imputation accuracy with the combined reference panel. Conclusion: YGEP bridges the gap between advanced genomic analytics and practical yak breeding. By integrating pedigree reconstruction, genotype imputation, and GEBV estimation into a user-friendly cloud platform, YGEP effectively eliminates technical and data bottlenecks. Overall, it provides an accessible, scalable, and standardized solution to advance digital herd management and precision genetic improvement in alpine livestock.

The Siamese fighting fish (Betta splendens) is well-known for its high levels of aggression and complex, stereotyped displays, making it an ideal model for testing deep learning-based tools for high-throughput, unbiased quantification of aggressive behaviour. A deep-learning object recognition model (BettaAI) was developed to detect the species' aggressive displays, including threat (opercula opening and fin distension), attack (bites) behaviours, as well as surface air breathing, a behaviour correlated with the frequency and intensity of aggression. Videos of males confronting their mirror image were acquired simultaneously with synchronised top and side cameras. Two separate models were trained, with some behaviours identified from top-view frames and others from side-view frames; outputs from both models were combined and post-processed for final quantification. BettaAI performed with high accuracy: F1 scores were 0.99 for the top-view model and 0.93 for the side-view model. Average Precision (AP) at 0.5 IoU exceeded 0.98 for all categories except bites, a rare behaviour in the dataset, which reached 0.865. Comparisons with a manually curated "ground-truth" dataset from videos of 10 males showed strong concordance between automated quantification and manual annotations by expert observers across all behaviours. A case study on 461 males reacting either to a mirror or to a video playback of a conspecific demonstrated the high-throughput and unbiased advantages of BettaAI, with threat displays being more frequent toward the mirror image and attack rates not differing between treatments. This work underscores the potential of BettaAI for automated, bias-free quantification of aggressive displays in B. splendens.

Parasitic infection is one of the common health problems of livestock in Bangladesh. Due to the country's climate, heavy monsoon rainfall, low biosecurity in farms, and high humidity, along with presence of suitable vector organisms, gastrointestinal parasitism remains widespread in cattle and other livestock. The standard method of diagnosis is microscopic examination of fecal samples, but this depends on manual observation, which is time-consuming and can lead to human error, mainly because many parasite eggs look similar to each other and samples often contain contaminants that can be mistaken for eggs or cysts. In this study, we tried to apply the YOLOv8 deep learning model for automated detection of parasitic eggs and cysts from microscopic images of livestock fecal samples. Images of clinical cases were collected, annotated, and used to train the model in Python, with batch size 16, auto optimizer, learning rate 0.01, momentum 0.937 and weight decay 0.0005. Training was done using Google Colab, and the model was evaluated using precision, recall, F1-score, mAP50, and mAP50-95. The model achieved a precision of 56%, recall of 24%, F1-score of 33.6%, mAP50 of 33%, and mAP50-95 of 22%. The relatively low recall and F1-score indicate that the model still has considerable limitations, largely due to insufficient species-specific training data and presence of image artifacts. Underrepresentation of some parasite species, such as Trichuris spp., in the dataset also caused class imbalance, which affected the model's ability to detect these species reliably. Despite these limitations, the study indicates that YOLOv8 architecture has some potential to be used for detection of parasitic eggs and cysts from microscopic images, and that further work with larger and more balanced datasets may improve performance and applicability in veterinary diagnostics. Keywords: YOLOv8, livestock parasites, deep learning, microscopic image analysis, veterinary diagnostics, Bangladesh

Robotic herding offers a promising off-animal approach to controlling the spatial distribution of grazing livestock. Nevertheless, the habituation of cattle to herding stimuli remains a critical obstacle to its practical use. This study presents the first field investigation of behavioral responses of grazing cattle to herding by a quadruped robot. We compared the herding efficacy of a drone and a quadruped robot, and tracked daily changes in responsiveness during continuous herding. Trials were conducted in a 1.1-ha pasture with Japanese Black breeding cows from June to October 2023. The quadruped robot elicited stronger avoidance responses with shorter latencies than the drone, and herding was more successful with the robot. During consecutive daily herding with the robot, behavioral responsiveness declined progressively over the initial 5 days, at a markedly slower rate than previously reported for drone herding. Following a 24-day interruption, responsiveness partially increased, but declined rapidly again over the subsequent two days. These results indicate that the quadruped robot constitutes a more persistent aversive stimulus than a drone for grazing cattle, although habituation management strategies (such as diversifying stimuli or combining sensory modalities) will be necessary for sustained control of grazing distribution.

The maned wolf (Chrysocyon brachyurus) is a near-threatened canid species that suffers from gastrointestinal (GI) disease under human care. While the cause remains poorly understood, recent studies report that altered gut microbiota is linked to GI disease in the domestic dog. The goal of this study was to describe the relationship between gut bacteria and environmental factors, GI health, short chain fatty acid (SCFA) peaks, and genetic relatedness in maned wolves. Fresh fecal samples were collected twice from wolves (first collection n = 29; second collection n = 25) housed in six facilities in the United States. Fecal alpha-1 proteinase inhibitor (FA1PI), a biomarker for GI health in canids, and SCFA peaks were quantified. Information on diet, housing group and history of GI disease or inflammation was provided by the zoological facility for each wolf. We characterized gut microbiota using 16S rRNA gene amplicon sequencing with qPCR abundance corrections. We found that dietary fiber gross energy (GE), protein GE, and number of daily produce items influenced gut microbiota. Additionally, there was a negative relationship between dietary fiber GE and Fusobacterium sp. abundance, corroborating previous findings linking fiber to altered gut microbiome composition in canids. Lastly, fiber GE was negatively correlated with FA1PI, connecting fiber to GI health in the maned wolf. Findings from this study suggest that increasing dietary fiber GE changes the gut microbiome and may improve GI health in the maned wolf, highlighting important management decisions that can be considered to maintain a healthy zoo-managed maned wolf population. IMPORTANCEFindings from this study are important because gastrointestinal disease is a common health concern for maned wolves under human care, and the causes are not well understood. The current study found that diet, especially the amount of fiber gross energy, can affect gut bacteria and may support better gastrointestinal health. Diet alterations could be a practical tool for zoos to support management of gastrointestinal health issues in maned wolves. These findings also show the importance of carefully managing diets for a near-threatened species, since better gastrointestinal health may improve overall health and well-being and support reproduction. More research is needed to determine the best amount and type of fiber, but our results provide foundational information for improving care and supporting healthy zoo-managed maned wolf populations.

While hamsters are commonly housed in groups within pet shops in Japan, small cages are often thought to restrict their physical activity, leading to arguments that larger cages should be provided. Although previous research has investigated how cage size and running wheel availability influence activity levels in individually housed hamsters, no studies to date have examined these specific effects in a social housing context. Therefore, this study investigated how cage size and the presence of a running wheel affect the activity levels of individual hamsters using the group-housing conditions with five hamsters. Video recordings were captured for 24 hours across four distinct cage environments using a camera installed directly above each cage. From these recordings, the distances traveled on both the cage floor and the running wheel were calculated for each hamster and statistically analyzed. The results revealed that overall activity levels were significantly higher in cages equipped with a running wheel than in those without. Although cage size did not yield a statistically significant difference, a marginal trend toward higher activity in larger cages was observed.

Individual encounter histories are central to capture-recapture models, but fisheries monitoring is often reduced to counts that do not account for variation in detection probability. This study presents a machine-vision workflow for converting long-term video surveillance of Atlantic salmon (Salmo salar) and sea trout (Salmo trutta) spawning runs into individual-level data for capture-recapture analysis. The workflow detects fish-positive frames, saves video clips, extracts fish-head regions of interest, and organizes cropped images for re-identification. A binary EfficientNetB0 fish detector achieved validation accuracy of 0.9918 and PR AUC of 0.9992; at a conservative threshold of 0.98, validation false positives were eliminated while retaining 94.3% recall. A YOLOv8n model localized fish-head regions, and an EfficientNetB0 ArcFace model trained on head images from 700 identities achieved 99.80% accuracy among accepted known matches and an image-weighted false-accept rate of 0.81% when non-training identities were treated as unknown. Zero-shot closed-set retrieval achieved 99.17% top-1 accuracy across 1,416 identities excluded from model training, demonstrating strong generalization to previously unseen identities.

Background: Flea infestation is an important companion-animal health problem and a prime source of zoonotic exposure. However, information on cat owners awareness and preventive behavior regarding fleas and flea-borne diseases (FBDs) in Bangladesh is limited. This study assessed the knowledge, attitudes and practices (KAP) of cat owners regarding flea infestation and flea-borne diseases in selected areas of central Bangladesh. Methods: A cross-sectional survey was conducted from November 2025 to July 2026 among 238 cat owners attending veterinary clinics in Savar, Dhamrai and Manikganj Upazila. Data were collected using a pretested structured questionnaire covering respondent characteristics, flea biology and transmission, perceived risks, and flea-prevention and control practices. Descriptive statistics were used to summarize the findings, and respondents were classified according to their overall KAP scores. Results: Of the respondents, 47.1% owned cats with outdoor access and 77.7% reported that their pets had previously experienced flea infestation. Although 65.5% used flea-control treatments, awareness of zoonotic and disease-transmission risks was limited. Only 14.7% recognized that fleas can parasitize humans, while 17.6% knew that fleas can transmit infectious agents. Overall, 83.2% of respondents had poor knowledge, whereas 69.7% demonstrated moderate attitudes and 63.9% showed moderate practices. Good knowledge and good practice were uncommon, accounting for only 3.8% and 4.6% of respondents, respectively. Veterinary recommendation was the most frequently reported motivation for using flea-control products. Conclusions: Cat owners attending in the surveyed areas frequently reported flea exposure and treatment use, but substantial gaps remained in their understanding of flea biology, zoonotic potential and comprehensive control. Targeted veterinary education emphasizing routine prevention, treatment of all susceptible household animals and environmental management is needed. These findings provide regional baseline evidence and should not be interpreted as nationally representative. Keywords: Bangladesh; cat owners; ectoparasites; flea-borne diseases; flea control; knowledge, attitudes and practices; One Health.

Abstract The gayal (Bos frontalis) is an endangered semi-domesticated bovine species renowned for its high-quality beef. However, its semi-feral lifestyle, ongoing habitat fragmentation, and extensive genetic introgression from sympatric local cattle have led to dramatic population decline and severe erosion of purebred genetic integrity, posing substantial challenges to its conservation and utilization. To address the urgent demand for rapid, non-invasive, and field-compatible germplasm identification, we developed an integrated artificial intelligence (AI) framework that predicts genomic admixture composition from external morphological images. We constructed a comprehensive dataset comprising 6,245 morphological images and matched genomic sequences from 52 gayals maintained at the Yunnan Provincial Gayal Conservation Farms. Following a preliminary evaluation of nine deep learning models, five were incorporated into a anatomical segment-based multi-modal pipeline, among which Inception_V3 delivered the optimal overall performance. To enhance simultaneous extraction of local fine-grained features and global structural information, we further designed an innovative HybridInceptionViT model by integrating the multi-scale Inception module with the Vision Transformer (ViT) framework. This hybrid model significantly outperformed the baseline Inception_V3, boosting the accuracy of phenotype-derived prediction against genomic admixture estimate from 69.69% to 87.87% (absolute error <15%). This study establishes a practical, low-cost "phenotype-to-genotype" tool for rapid on-site gayal germplasm screening, offering a scalable strategy for the conservation and breeding management of endangered livestock, and holds broad application prospects for agricultural and livestock production systems.

Insect proteins represent a promising and more sustainable alternative to soybean meal in swine nutrition. However, high dietary inclusion levels often result in reduced animal performance, indicating that factors other than crude protein concentration should be considered. This study evaluated the protein quality and degradability of feed-grade defatted black soldier fly (BSF) meal in comparison with a conventional organic protein core for post-weaning piglets. Protein content, amino acid composition, reactive lysine, Maillard reaction markers, buffering capacity, and protein hydrolysability were determined. Our results showed that defatted BSF meal exhibited a protein content and amino acid profile comparable to those of the protein core but contained substantially higher levels of free amino acids. Accounting for free amino acids reduced the estimated lysine damage from 18.4% to 10.4%, highlighting the importance of considering free amino acids when determining reactive lysine. In addition, BSF meal exhibited a higher buffering capacity and lower protein degradability than the protein core. These findings provide new insights into the nutritional limitations of feed-grade BSF meal and suggest that a more accurate assessment of reactive lysine, together with dietary strategies to reduce buffering capacity, may improve its utilization in post-weaning piglet diets.

African swine fever (ASF) in wild boar poses major surveillance and control challenges, particularly in periurban and human-modified landscapes where ecological complexity, delayed detection, and heterogeneous host movements complicate out-break interpretation. In late 2025, ASF was detected in wild boar in Catalonia, Spain, creating a high-priority epidemiological scenario at the wildlife-urban interface. In this study, we analysed the 2025-2026 Catalonia outbreak using scenario-based spatial modelling with the WIMBOARD (Wild Integrated Movement Boar Outbreak and Risk Dynamics) framework. Simulations under baseline control conditions were used to interpret spread dynamics and support anticipatory surveillance. The results indicate that outbreak expansion was structured and directional rather than isotropic. Temporal outputs suggested delayed detectability between infection prevalence and mortality signals, whereas cumulative spatial risk maps, time-to-infection surfaces, and monthly infection-risk dynamics identified directional asymmetries and differentiated phases of spread. An early southward dispersal signal was consistent with initial field observations, while the north-northwest sector emerged as the most consequential expansion scenario because of its stronger functional connectivity and higher potential for regional amplification and persistence, while a later northeast-ward phase remained comparatively less influential within the 500-day simulation horizon. Monthly risk surfaces further showed that ASF spread behaved as a moving eco-epidemiological wavefront, allowing identification of shifting surveillance windows before mortality became apparent. These findings support the interpretation of the Catalonia outbreak as a landscape-mediated epidemiological process shaped by functional connectivity, wildlife behavioural adaptation, peri-urban ecological structure, and delayed detection. This study shows how spatially explicit eco-epidemiological modelling can support outbreak interpretation, surveillance prioritisation, and proactive wildlife disease management under complex field conditions.

Amphibians are among the most threatened vertebrates, yet assisted reproductive technologies (ARTs) remain underutilised in their conservation. We developed and evaluated a biologically relevant, non-lethal sperm collection protocol for Rana muscosa, a critically endangered frog in a long-term conservation breeding program. Thirteen hormone treatments were tested across six post-injection time points, and sperm quality was assessed via concentration, motility, osmolality, and pH. Generalised linear mixed models revealed that gonadotropin-releasing hormone (GnRHa) alone significantly outperformed hCG-based regimens. The 3 {micro}g/g GnRHa dose yielded the highest sperm concentration and sustained motility from 3 to 24 hours post-injection. Motility was highest under moderately acidic (pH 6.5-7.0) and hypoosmotic (75-100 mOsm/kg) conditions. To support decision-making, we applied a refined Wildlife Sperm Index (WSI) that weights motility and concentration as primary functional-yield traits, with motility given greater relative weight given its direct role in fertilisation, and treats pH and osmolality as secondary environmental-compatibility traits. Under this revised composite score, 3 {micro}g/g GnRHa achieved the highest overall WSI score, outperforming 2 {micro}g/g and 4 {micro}g/g GnRHa, which ranked second and third, respectively, despite their more favourable pH and osmolality profiles. These findings provide the first evidence-based ART protocol for R. muscosa and offer a transferable framework for optimising gamete collection, IVF, and cryopreservation in line with other amphibian species, advancing both genetic management and species recovery goals.

This study was carried out on two rabbit lines, each selected for a feed efficiency criterion (growth on restricted feed for the AlimR line or residual consumption on an adlibitum diet for the ConsR line), introduced into a facility by adoption of newborn kits by SPF (specific pathogen free) females. Following this break in symbiotic transmission, fecal samples from females were used to study the microbiota composition of the two lines over seven generations (17 females per line and per generation). The proportion of Firmicutes was significantly higher in the AlimR line than in the ConsR line (82.22% vs 78.21%, p<0.0001). Conversely, the proportion of Bacteroidota was significantly higher in the ConsR line than in the AlimR line (20.38% vs 16.50%, p<0.0001). The effect of generation was also significant for the abundance of Firmicutes and Bacteroidota (p=0.0009 and p<0.0001, respectively). The Shannon diversity index was significantly higher in the AlimR line than in the ConsR line (5.23 vs 5.14, p=0.02). The effect of generation was also significant for the Shannon index (p=0.003). Finally, a discriminant principal component analysis of the microbiota composition allowed us to distinguish both the two lines and the generations, in particular the 11th selected generation (animals adopted by SPF females) and the 18th generation.

Zoos and public aquariums serve as essential hubs for wildlife conservation, public education, and scientific research; however, the success of these missions depends upon maintaining high animal welfare standards despite constant human presence. A primary concern is the 'visitor effect': the alteration of animal behavior due to human presence. While this phenomenon is well-documented in captive mammals and has been explored in chondrichthyes, it remains largely unexamined in teleost fish, despite evidence of their sensitivity to human stimuli in natural environments. This study addresses this knowledge gap by investigating the behavioral responses of 13 teleost species to varying levels of crowd density, direct human solicitation, and ambient noise. Our multivariate analysis reveals that visitor density and visitor-induced disturbances are significant drivers of behavioral change, with species identity acting as the primary source of variance. We observed high inter-taxonomic variability: while several species (including Euxiphipops sextriatus, Dascyllus aruanus, and Zebrasoma flavescens) showed marked sensitivity through significant alterations in stress-coping, exploration, and aggression, others remained behaviorally stable. Furthermore, acoustic analysis indicates a complex soundscape where visitor density correlates with increased sound amplitude, particularly in the 100 Hz to 400 Hz range, a critical band for teleost hearing suggesting that visitor-induced noise is distinct from the aquarium's technical background noise. These findings underscore that the 'visitor effect' is not a uniform phenomenon but a complex interaction shaped by species-specific sensitivity and distinct anthropogenic stressors. Our results highlight the necessity of incorporating species-specific behavioral data and acoustic monitoring into welfare management protocols to better mitigate the impact of human presence on captive fish populations.

Objective: Hyperthyroidism and hypothyroidism related to iodine deficiency are major public health concerns in Afghanistan. This study aimed to assess the frequency of thyroid dysfunction among male patients referred for thyroid testing and its association with age, and to examine monthly trends in thyroid dysfunction at Asia Med Laboratory in Herat, Afghanistan, from July 2021 to January 2022. Methods: A retrospective analysis was conducted on 250 male patients aged 0-69 years. We measured Serum TSH, total T4, and total T3 levels, and thyroid status was classified using age specific reference ranges. In addition, the frequency of thyroid dysfunction was analyzed across age groups with monthly trends of thyroid state. Results: Overall, the euthyroid state consisted of 69.2% of participants, 24.8% with overt hypothyroidism, 3.2% with overt hyperthyroidism, and 2.8% with subclinical hyperthyroidism. Thyroid status differed significantly by age (p = 0.0135), with hypothyroidism increasing in older age groups and reaching its highest proportion among men aged 60-69 years (55.6%). Euthyroidism predominated in patients aged 10-39 years, while hyperthyroidism across age groups remained relatively infrequent. After September 2021, a threefold increase was observed in the total number of male patients referred for thyroid testing. During this period, the proportion of hyperthyroidism increased slightly, whereas hypothyroidism cases declined. Conclusion: In conclusion, hypothyroidism was more frequent with older age. The rise in absolute case numbers after September 2021 likely reflects increased patient referrals, underscoring the need for ongoing monitoring of thyroid function. The study may assist in the early management of thyroid disorders and in reducing their complications.

RationaleOxidative stress, resulting from an imbalance between the production of reactive oxygen species (ROS) and antioxidant defence mechanisms, disrupts cellular redox homeostasis and contributes to damage of biomolecules, including nucleic acids, proteins and lipids. Such disturbances can impair intracellular signalling pathways and have been implicated in the pathophysiology of female reproductive disorders. Nitroblue Tetrazolium (NBT) is a distinctive dye that assesses cellular redox activity in neutrophils through the detection of superoxide anion (O2-). However, the relationship between neutrophil-derived oxidative stress and women infertility remains to be fully elucidated. Aim of the study: We aimed to investigate the role of neutrophil oxidative stress in women infertility using a novel Nitroblue Tetrazolium (NBT) method developed in our laboratory. Materials and methodsBlood and serum specimens were obtained from a total of 100 Libyan women, comprising healthy fertile women (n = 21; controls) and infertile women (n = 79). Superoxide anion (O2-) generation in neutrophils was assessed using the novel NBT method, while malondialdehyde (MDA), a marker of lipid peroxidation, was determined using the thiobarbituric acid reactive substances (TBARS) assay. ResultsA significant increase in both NBT-reactivity levels and the percentage of NBT-positive neutrophils was observed in infertile women compared with healthy fertile controls (P < 0.0001). In addition, MDA levels were significantly higher in infertile women than in the control group, indicating enhanced lipid peroxidation. MDA levels were positively correlated with NBT-reactivity levels (r = 0.410, P = 0.0001) and the percentage of NBT-positive neutrophils (r = 0.21, P = 0.047). A significant positive correlation was also observed between NBT-reactivity levels and the percentage of NBT-positive neutrophils (r = 0.510, P = 0.0001), demonstrating a close association between neutrophil oxidative activity and lipid peroxidation in women infertility. ConclusionThe present study demonstrates the utility of a novel NBT method for detecting reactive oxygen species (ROS), a marker of oxidative stress, in neutrophils from both blood and serum specimens. The findings demonstrate increased neutrophil-derived oxidative stress in infertile women and suggest that this method may have potential as a diagnostic tool for the assessment of women infertility. ImpactThis study provides evidence that neutrophil-derived oxidative stress is significantly increased in women infertility and demonstrates the application of a novel Nitroblue Tetrazolium (NBT) assay for assessing oxidative stress in both blood and serum specimens. The significant associations between NBT-reactivity, NBT-positive neutrophils and malondialdehyde levels provide further insight into the contribution of oxidative stress to female reproductive pathophysiology. These findings support the potential utility of the novel NBT method as a simple and reliable diagnostic approach for evaluating oxidative stress in women infertility and provide a foundation for future studies investigating oxidative stress biomarkers in reproductive medicine.